7 Excel Formulas to Make Paid Search Easier

In the world of Pay-Per-Click (PPC) advertising, digital marketers are constantly managing data, optimizing ad copy, and creating reports, usually in Microsoft Excel. Whether you are a digital marketing novice or an experienced PPC master, this blog explores seven essential Excel formulas that will help you work smarter, not harder.

1.      =LEN to Count Characters

When crafting ad copy, character limits matter. For example, when creating a responsive search ad (RSA), each headline can have a maximum of 30 characters and each description a maximum of 90 characters. The =LEN formula will help you ensure your text fits within the character limits of ad platforms like Google Ads, by outputting the character length of text in a given cell.

In this example, =LEN(A2) counts the character length of the text in cell A2.

2.      =TRIM to Remove Unnecessary Spaces

The =TRIM formula is valuable for PPC digital marketers because it enables you to efficiently remove leading and trailing spaces, ensuring consistency in your data. When writing ad copy or downloading large datasets, extraneous spaces can lead to discrepancies and errors in your campaigns. This formula is a quick way to clean up and normalize text data, saving yourself the hassle of errors down the road.

In this example, =TRIM(A2) removes the extraneous spaces in cell A2.

excel formula

3.      =PROPER to Capitalize Words

When drafting ad copy it is important to make sure your ad is professional and visually appealing. =PROPER allows you to automatically capitalize the first letter of each word, helping create polished and uniform ad copy. This not only improves the visual appeal of your ads, but often contributes to higher click-through-rates.

In this example, =PROPER(A2) capitalizes the first letter of each word in cell A2.

excel for paid search

4.      =IF to Make Logical Rules

Digital marketers often need to make strategic decisions based on various conditions, such as budget thresholds, click-through rates, or other conversion metrics. With =IF, you can create dynamic formulas that automatically evaluate these conditions and return different outcomes accordingly. The flexibility of this formula allows you to apply it to almost any data analysis, making it a go-to trick for many PPC marketers.

In this example, =IF(B4=“YES”,1,2) evaluates if cell B4 contains the word “YES”, returning a 1 if true or a 2 if false.

if function excel

5.      =SUMIF to Group Relevant Data

When working in Google Ads, you are constantly downloading Excel reports to analyze performance metrics for specific keywords, ad groups, or campaigns. If that is the case, =SUMIF might become your favorite formula. It enables you to sum up values only for the rows that meet specific conditions. This will help you quickly assess the effectiveness of different segments within your data, helping you identify key themes.

In this example, =SUMIF(A2:A8,D2,B2:B8) sums the values in column B when the corresponding value in column A matches the text in cell D2, in this case, “Apple”.

sumif function in excel

6.      =VLOOKUP to Quickly Find Data

VLOOKUP is a game-changer when you need to locate specific data within a large dataset. In the context of PPC campaigns, =VLOOKUP is particularly handy for matching keywords with corresponding performance metrics or other relevant information stored in different sheets. For example, you can use this formula to quickly retrieve information like keyword performance by matching performance metrics to a keyword in a specific column.

In this example, =VLOOKUP(A2,A5:C7,2,FALSE) searches for the value of cell A2, in this case “2”, within the first column of the range A5:C7, and returns the corresponding value in the second column of that range, in this case, “paper.” Optionally, you can specify TRUE for an approximate match or FALSE if you want to look for an exact match.

vlookup for excel

7.      =CONCATENATE to Join Cells Together

One of the most important steps in campaign creation is building out the initial keyword set. When you are putting together the list of target keywords, it is important to ensure the inclusion of all relevant keyword variations. The =CONCATENATE formula is useful for combining various keywords, adjectives, or modifiers into comprehensive keyword phrases.

In this example, =CONCATENATE(A2,B2) combines the text in cells A2 and B2 into one cell.

=concatenate in excel

What’s Next?

At the end of the day, there is no single correct way to use Microsoft Excel as a digital marketer. This blog explores just 7 of the 500+ unique formulas that Microsoft Excel has to offer, and new formulas are added every year. While it might be impossible to master all these shortcuts, learning and practicing these seven formulas will help you navigate a spreadsheet quickly and comfortably as you build your paid search expertise. Happy Excel-ing!

If you have any questions regarding Microsoft Excel or have more general paid search and digital marketing needs, please contact us by email at sales@synapsesem.com

4 Best AI Video Generators for Marketing in 2024

As businesses increasingly invest in video content, the numbers speak for themselves. According to HubSpot’s State of Marketing Report, 87% of video marketers confirm that incorporating video content has led to an increase in traffic to their websites. Additionally, 80% of video marketers say that incorporating video content has directly contributed to increased sales.

In light of these compelling statistics and the evolving landscape of content creation, AI video generators have emerged as transformative tools. An AI video generator can effectively simplify the video creation process by leveraging advanced algorithms to automate tasks from script analysis to visual editing. This transformative tool not only streamlines content creation but also enhances the overall quality of videos, enabling businesses to respond to the increasing demand for engaging visual content in today’s digital marketing landscape. In this guide, we will discuss some of the best AI video tools on the market today, their key features, pricing, and other functionalities you should be looking for if you’re interested in using AI to improve your video workflow.

Why Adopt an AI Video Tool to Streamline Video Creation?

AI enhances video creation by automating and streamlining various tasks, from script analysis to visual editing. This results in a considerable reduction in the time and effort traditionally required for video production. The benefits of integrating AI into the creative workflow are multifaceted. First and foremost is the remarkable speed at which AI can generate high-quality videos, enabling marketers to meet tight deadlines and keep up with the demands of a fast-paced digital landscape. Moreover, AI’s efficiency is evident in its capacity to handle repetitive tasks, allowing individual creators to focus on more strategic and creative aspects. Additionally, the customization capabilities of AI video generators empower marketers to tailor content to specific audiences, ensuring relevance and resonance. Overall, AI Video generators are both time and cost-efficient in producing personalized video content.

4 Best AI Video Generators

An AI video generator can be a valuable asset for your business and marketing strategy. However, with so many options out there, how can you choose the right tool for your needs? Below, we explore four standout AI video generators—Lumen5, InVideo AI, Biteable, and Synthesia. Each tool has earned its place in the spotlight for distinct reasons, ranging from user-friendly interfaces to advanced script automation, robust analytics capabilities, and cutting-edge AI avatar creation.

  • Lumen5: Best for its easy-to-use interface
  • InVideo AI: Best for script automation
  • Biteable: Best for robust analytics
  • Synthesia: Best for AI avatar creation


If you are just diving into the creative scene, Lumen5 is the ideal AI video generator with an easy-to-use interface that plays nicely with all skill levels. Lumen5 is particularly effective in emphasizing and visualizing text-based content, making it suitable for transforming articles and blog posts into video format using the blog link or any written content.


  • Text-to-Video: It excels at turning text content, such as your existing blog posts, into engaging videos, suitable for content repurposing.
  • AI Voices: Users can easily switch between over 40 different voices while creating their videos.


  • Limited Customization: While efficient, Lumen5’s customization options might be more limited compared to other platforms.
  • Considerable Delay on video playback/preview 


  • Community: $0 for up to five videos per month
  • Basic: $19 per month, billed yearly, or $29 billed monthly
  • Starter: $59 per month, billed yearly, or $79 billed monthly
  • Professional:$149 per month, billed yearly, $199 billed monthly 
  • Enterprise:  Custom pricing tailored to specific needs

InVideo AI

InVideo AI is renowned for its ability to generate impressive videos by automatically generating scripts based on the user’s text prompts. Simply convey your intentions in plain English, and the tool brings your vision to life. The more detailed your prompt, the better your results. Additionally, you can reference any blog post from the web to create your script. 


  • AI-Powered Script Generation: Generate scripts effortlessly using AI with basic text prompts
  • Effortless Clip Replacement: Seamlessly replace clips or scripts automatically generated by the AI tool with alternative options from the stock library or personal album
  • Easy Edit: Instead of manually editing the script or searching for additional images, users can provide comments to edit the video.


  • Considerable lag during export and video editing.
  • Limited script input: For any script or blog post, there is a 50-line cap when using InVideo’s AI-powered video generator. 


  • Free: $0 for 10 mins/week of AI generation and 4 videos per week with InVideo logo
  • Plus: $20 per month, billed monthly, or $240 billed yearly
  • Max: $48 per month, billed monthly, or $576 billed yearly


Compared to other AI-powered video generators, Biteable stands out by providing a robust analytics suite that offers real-time insights into viewer engagement, locations, and overall video performance. This feature empowers creators to refine their content strategy based on data-driven insights. Additionally, Biteable allows users to collaborate on video creation within the platform, streamlining the collaborative process.



  • Collaboration: Team members can create together within the platform.
  • Real-Time Analytics for Effective Video Marketing: The analytics suite includes viewer, engagement, and location insights, empowering creators to refine content based on performance and enhance overall video effectiveness.
  • Extensive Template Collection: With over 5,000 project templates tailored for specific occasions or purposes, such as  “thank you” messages, celebration videos, and education videos, users can choose from a diverse range of themes and options. Additionally, exclusive premium templates are accessible to Business and Unlimited plan users.


  • Challenging Editing Process: Editing the video is not as easy and intuitive as other alternatives on the market.
  • Pricing Tiers: Some advanced features might be available only in higher-priced plans.


  • Pro: $49 per month, billed monthly, or $588 billed yearly
  • Premium: $99 per month, billed monthly, or $1,188 billed yearly
  • Business: Custom pricing tailored to specific needs


Synthesia is best known for its AI avatars: users can choose between more than 140 AI avatars. Users can create their own avatars and gendered audio in more than 120 languages. This feature is particularly advantageous for companies aiming to establish a distinctive visual identity in a crowded digital space.


  • AI Avatars Selection: Natural-sounding AI avatars and extensive artificial intelligence avatar library, and collaborative elements, including over 140 AI avatars and more than 120 languages.
  • Customization Options: Tailor videos with customizable backgrounds and branding colors, providing a unique visual identity.
  • Collaborative Elements: Facilitate collaboration by easily sharing internal video links with other users for direct feedback on the platform’s feed.


  • Limited Emotional Expression: The avatars, lacking diverse facial expressions and the ability to convey human emotion, result in videos that may come across as robotic and clinical.
  • Limited Scalability: The manual production of each video limits scalability, posing challenges for users in terms of efficiently handling larger-scale video production tasks.


  • Starter: $22 per month, billed monthly, or $264 billed yearly
  • Creator: $67 per month, billed monthly, or $804 billed yearly
  • Enterprise: Custom pricing tailored to specific needs

What To Consider When Choosing an AI Video Creator

Each AI video generator presents unique strengths and considerations. Lumen5 excels in ease of use, InVideo AI stands out for its AI-powered script generation, Biteable offers versatility and real-time analytics, and Synthesia brings innovation with its extensive AI avatar library. Understanding the distinctive strengths and considerations of each AI video generator is crucial in selecting the right tool tailored to specific creative needs.

With capabilities that range from automating intricate editing tasks to providing efficient customization options, AI video generator becomes an asset in crafting valuable and impactful videos. This empowers businesses to generate high-quality videos swiftly and with enhanced customization options, saving both time and resources while ensuring a consistent and professional aesthetic across all video content. Therefore, we strongly encourage businesses to explore and experiment with various AI video generators to optimize their efficiency in video content creation. When choosing a platform, make sure to prioritize your specific objectives and needs. Consider factors such as the desired level of customization, collaboration features, and budget constraints before making a selection.

If you have any questions regarding AI-generated content or have more general content development and optimization needs, please contact us by email at sales@synapsesem.com.

What is Helpful Content? A Guide to Google’s Helpful Content Updates

You might ask yourself: “Helpful content? Who’s creating UNhelpful content?” Believe it or not, there are many websites out there designed to exploit Google’s ranking algorithms to make a quick buck.

Some good news: If you’re already concerned about keeping your website helpful, you probably don’t need to be concerned about these algorithm changes. Most established sites with dedicated SEO strategies are already generating helpful content.

Still, Google’s ongoing updates to its Helpful Content System can impact even the most helpful sites. This is why it’s so important to stay up-to-date on changing algorithms and search trends. As new algorithm updates roll out and Google’s ranking strategy continues to evolve, even the most established sites should remain focused on producing high-quality content.

Read more about Google’s Helpful Content Update below and learn how to use these updates to earn an organic boost for your website.

What is the Helpful Content Update?

In August 2022, Google rolled out its first algorithm update focused on promoting helpful content. The Helpful Content System, a suite of ranking factors Google uses to determine the “helpfulness” of content, was designed to improve the search landscape by:

  1. Elevating content that searchers find most informative, and 
  2. Flagging for penalty any content that doesn’t offer value to searchers.

An important note: Helpful content is a site-wide signal, meaning that any unhelpful content on your site can impact your entire site’s performance.

Since that first roll out, two other iterations of the Helpful Content System have been introduced, with the most recent edition coming live in September 2023. And with so much buzz around the system to this day, it seems likely that an emphasis on helpful content will remain relevant for the long term.

What is Helpful Content?

As defined by Google, helpful content is “original, helpful content created for people.” Generally, this means that your site content answers the questions that searchers are asking in Google Search and leaves a visitor feeling satisfied after visiting your site.

Experts at Search Engine Land have identified four main factors to consider when determining whether a site’s content is helpful:

  1. Content is designed with a specific purpose and audience in mind.
  2. Content relies on (and makes prominent) expertise on the topic.
  3. Content is trustworthy and credible.
  4. Content is designed to help searchers find what they’re looking for.

Keeping these factors in mind when developing new content, or auditing existing webpages, ensures that your site benefits searchers, maintains its search rankings, and drives more organic traffic.

4 Major Factors That Make for Helpful Content

Google has made it very clear that its Helpful Content System exists to meet the needs of searchers. But without clear guidance, it can be very difficult to know exactly how to judge your site’s content quality. These four criteria can help SEOs and content creators to understand exactly what that requires.

1. Designed for a Specific Audience

Optimizing a site for SEO is often a numbers game. Content marketers are always looking for high-search volume keywords to target, while remaining in a level of competition that makes sense for their brand and allows them to rank.

However, while a robust and varied content repository is important to have, sites must still be careful to “stay in their lane.” For example, if my website is about photography, I shouldn’t be writing articles about toy cars. It’s too far from the core topic of my site, and my target audience isn’t coming to my website to learn about toy cars.

Your website should have one, clear focus. Broadening your content base in that space is fine, but moving into completely different verticals can signal that your site is more focused on ranking for more keywords than helping your audience find what they’re looking for. And at the end of the day, writing content for people is most important anyways. Building winning content strategies requires a clear focus and robust supporting articles.

This is why the popular pillar page strategy is so effective. A list of target keywords is broken into distinct topic clusters, and each topic cluster is then mapped to a unique blog article designed to rank for only those keywords. Pillar pages are those pages targeting a high-search-volume topic cluster core to the site’s purpose. This strategy allows your blog to cover more ground while staying focused on its main area of expertise.

2. Utilizes Expertise

Google has always placed an emphasis on real expertise when ranking content. In the early days, this meant the .gov and .edu sites got a leg up on many searches, as they were seen as more likely to be experts in their respective spaces.

Now, search engines look for content that refers to or quotes experts. My blog article about photography shot composure could have perfectly-optimized meta tags and content, but might still struggle to rank. Including a quote from an expert photographer, or linking out to their blog, can give my content a boost in rankings.

Additionally, first-hand expertise is incredibly valuable. If my blog article includes reviews of popular cameras, including proof that I have used each of the cameras I’m reviewing, my article will likely rank prominently. Google promotes content that relies on first-hand experience, so including any mentions of this can be incredibly powerful, especially in instances of review content.

Search engines want to see that content marketers are doing their research and getting their facts from reputable sources. Featuring this expertise in your content can therefore have large payoffs.

3. Trustworthy and Credible

Similar to the use of expertise, search engines want to feature content that searchers can trust. The same blog article published by two sources can rank differently based on the source’s reputation and established credibility.

This factor is a bit more difficult to impact than the others. Moz, creator of powerful SEO tools and an SEO thought leader, developed their Domain Authority score to measure this exact factor. A site’s Domain Authority is based on the site’s overall credibility, measured mainly by the number and quality of backlinks pointing to the site.

While Domain Authority can be difficult to quickly improve, writing articles on topics that your brand is known for can be a great way to ensure you’re getting the most out of your content. High-quality, authoritative, shareable content is more likely to attract backlinks from other domains, lending a boost to your site’s Domain Authority.

4. Helping Searchers Find What They’re Looking For

This last point may seem obvious, but it represents the core of Google’s Helpful Content System. Keeping your content focused on the altruistic purpose of the internet, helping users find information based on their search query, can be the best way to make sure your content ranks well.

So how do you do this?

Write content for people, content that gives useful information concisely. Avoid burying answers to questions in paragraphs of text, and make it clear, to search engines and people, what they can expect to find on each page. Your goal is to provide users with a satisfying experience, so consider your audience’s perspective when developing copy.

Why Should You Care About Helpful Content?

In addition to helping keep the web a productive and efficient place, keeping your website full of helpful content can have plenty of performance benefits. Helpful content is more likely to rank well for its target keywords, leading to more search traffic and more conversions.

With recent announcements and advances, many are wondering how AI will revolutionize content marketing. When deciding whether or not to use AI-generated content on your website, it’s wise to keep helpful content in mind.

While Google has made no mention of how AI content may impact helpfulness, keeping these four factors in mind when producing any new content will benefit your site. As Google has stated: “If you see AI as an essential way to help you produce content that is helpful and original, it might be useful to consider. If you see AI as an inexpensive, easy way to game search engine rankings, then no [you should not use AI to generate content].”

Want to learn more about these strategies and our comprehensive SEO services? Reach out to the team at sales@synapsesem.com.

When and How to Use Broad Match Keywords

The landscape of match types across paid search is constantly changing. More recently, Google has pushed users away from the traditional exact and phrase match types to the notoriously avoided broad match. For years, advertisers were content with utilizing phrase match and exact match terms because they were safe and often resulted in relevant queries. With the sunsetting of the broad match modifier, there is more pressure by Google to switch over your keyword match types to pure broad.

Is it time to stop ignoring those pesky messages saying your campaign is limited by search volume? Could broad match keywords actually help your campaigns improve? Well, your program’s KPIs, strategy, and budget could help dictate whether broad match is the right move. Discover when and how to use broad match keywords for your campaigns below.

When is it the Right Time to Test Broad Match Keywords?


Campaign Goals are Focused on Growth Not Efficiency:

Broad match keywords can be a great tool to generate growth in your account when there is additional budget to spend. Due to their generic nature, broad match keywords allow advertisers to “cast a wider net” into the search results by matching out to related terms. For example, if your account was focused on advertising “luxury watches,” your exact match terms would limit the search results to just “luxury” related terms. Broad match keywords could match out to “best watches,” “high end watches,” “Rolex watches,” etc.—generating more traffic to the site and the opportunity for greater conversion volume. According to a study from Search Engine Land, broad match often results in lower CPCs, even with instances of exact match terms driving $1 higher CPCs in comparison to broad match. Depending on conversion rates, broad match could be an opportunity to expand accounts and also influence traffic/sales across additional channels.

When Your Business is Easily Defined:

A pure broad match strategy relies on Google’s algorithm to properly define the true nature of your product. If your product is straight forward, like “luxury watches” it will be easily for Google to generate keywords relevant to your search. However, if your company is more restrictive like software specifically for web developers, there is a greater chance that Google could generate queries that are irrelevant to your product.

When You Need to Save Time:

A broad match strategy can result in fewer keywords, fewer expansions, and fewer optimizations which can save advertisers time in their marketing process. Because broad match terms loosely match out to various searches, you no longer have to devote time to keyword expansion. Time can even be saved on campaign builds as advertisers will likely spend less time building out tedious variations of terms like “best watches,” “high-end watches,” “expensive watches,” and more.

When you are Implementing RLSA Campaigns:

Broad match keywords can be an excellent component of RLSA campaigns where relevant audiences are already overlaid on top of search campaigns. Since we know the user is already targeted, or in some cases, has visited the site before, we can expand the keyword set to focus on less restrictive iterations of the targeted keyword set.

When your Account has Strong Conversion Volume:

The key to implementing any of Google’s bid strategies is ensuring that you have enough data for the system to work efficiently. Broad match works best in accounts that generate strong daily conversion volume. Since we recommend combining broad match with bid strategies, the system will begin to “learn” which iterations work best in generating conversion volume or revenue. Google recommends having at least 15 conversions per week for a successful smart bidding strategy.

How to Use Broad Match Keywords:

Broad match can make or break your search campaigns so it is important to understand the best methods of implementation before we open the gates to a pure broad match keyword strategy.

Negatives, Negatives, Negatives:

Quite possibly the most important element to incorporating broad match keywords into your Google Ads strategy is to not only keep an extremely close eye on the search query results but to also proactively and regularly add negative keywords to avoid any irrelevant traffic. We recommend keeping a daily eye on the search query results, particularly over the first 7 days of a new program utilizing broad match.

Smart Bidding:

Through testing and overall Google recommendations, the best way to apply broad match terms to any campaign is utilizing a smart bidding strategy. Broad match terms generate more data through clicks and conversions for Google which allows the automated bid strategy to have greater learning to make decisions. If conversion tracking is properly set up, the bid strategy will, over time, stop showing your ads for less relevant searches as it acquires better data. In general tests, we have found that broad match works best when combined with exact match terms and can even result in exact match CPCs and conversion rates improving.

Analyze Backend Data (for lead generation companies):

Maximizing conversions is great, but if it is not driving deeper funnel leads, it will not be a profitable strategy. It is important to always evaluate backend data when running any test, but especially with broad match terms that are likely to drive in more generic traffic. If possible, we recommend importing in any offline conversion data to feed into the system so that Google’s bid strategies can optimize off quality leads and conversions.

Set Restrictions with Target CPA or Target ROAS Goals:

A good strategy for adding broad match keywords to your account in a conservative manner is to launch with target CPA or ROAS goals. Google’s learning algorithms will begin to identify what is most efficient for your account in order to avoid overspending with these new terms.


If you have any questions regarding automation best practices, please contact us by email at sales@synapsesem.com to talk through your Google Ads optimization needs.

Guide to the GA4 BigQuery Export

The switch from Universal Analytics to Google Analytics 4 (GA4) has come with both benefits and challenges for marketers. One of the most exciting benefits on the data analysis and warehousing front is the free (no 360 required!) BigQuery link.  

This link allows you to seamlessly export your GA4 data into Google BigQuery—a powerful, fully managed, and serverless data warehouse in the Google Cloud Platform. By combining the capabilities of GA4 with the analytical prowess of BigQuery, you can unlock a wealth of possibilities for extracting valuable information from your data. 

In this guide, we’ll explain how to leverage the BigQuery GA4 Export to its fullest potential. You’ll explore its advantages and discover how to set up the export, understand its data schema, and harness the power of BigQuery SQL queries to derive meaningful insights from your GA4 data. 

Why Should I Export GA4 Data to BigQuery? 

In the world of digital analytics, collecting data is just the first step in the journey toward meaningful insights. The true power lies in your ability to extract valuable information, identify trends, and make informed decisions. GA4 is a powerful tool in its own right, but to supercharge your data analysis, you should consider exporting your GA4 data to Google BigQuery for the following reasons: 

  1. Integrate GA4 data with other sources: To gain a comprehensive view of your business performance, it’s best to combine your GA4 data with other sources. BigQuery offers seamless integration with various data connectors, making it possible to merge your GA4 data with advertising data from Google Ads, your CRM, or even external datasets. With all your data integrated, you can build customized audience segments, explore traffic attribution, and build simple machine learning models. 
  2. Accelerated Data Visualization: For those dealing with sluggish GA4 data load times in BI and data visualization tools like Google Data Studio, Google BigQuery is a game-changer. The BigQuery BI Engine smartly caches frequently used data, drastically speeding up SQL queries and boosting the efficiency of data visualization and Business Intelligence tools. This translates to faster insights, smoother interactions, and an overall more responsive experience. 
  3. Automate repetitive tasks: One of the biggest efficiency-boosters of using BigQuery is the ability to automate repetitive analyses and data pulls. By setting up automated queries and reports, you can eliminate the need for manual data extraction and analysis, saving valuable time and resources.  
  4. Advanced analysis:  BigQuery is a powerful tool that supports advanced analytics and machine learning applications, enabling you to delve deeper into your data. You can perform complex analyses, conduct predictive modeling, and identify trends that might have remained hidden.  
  5. Avoid sampling and thresholding: The BigQuery export contains raw data from GA4. This allows you to bypass data limitations you may see in the GA4 platform, such as sampling, cardinality, and thresholding. 

To fully reap the benefits of the GA4 BigQuery export, it’s essential to set up the link as soon as possible. The export isn’t retroactive, meaning the sooner you create your link, the sooner you start accumulating valuable historical data.  

How to Link GA4 and BigQuery 

The first step to exporting your GA4 data to BigQuery is setting up a Google Cloud account. Google Cloud offers a free tier that includes 10 GB of data storage and up to 1 TB of querying each month. For most small to medium-sized businesses, this free tier provides more than enough resources to get started with a GA4 export to BigQuery.  

Once you have your Google Cloud account set up, make sure that your Google account has “Owner” permissions in Google Cloud and at least “Editor” permissions in GA4. After you complete these initial steps, you can move forward with enabling the BigQuery link from the Google Analytics admin tab: 

  1. Navigate to BigQuery Links under the Product Links menu in your property settings.
    link ga4 to bigquery
  2. Click Link to create a new connection. 
    create bigquery ga4 link
  3. Click Choose a BigQuery project to see the list of projects you have access to. Select the project you want the export to be housed in and click Confirm.
    bigquery ga4 project
  4. Select a location for the data and click Next. 
  5. Configure your settings. You can choose which data streams to include with the export and specific events to exclude from the export under Configure data streams and events.
    ga4 data streams and events
  6. Choose the types of tables you want to export. The Event data export is event-scoped, whereas in the User data export, each row represents a unique user. You can also choose the frequency of your Event data export: “Daily” for once a day and optional “Streaming” where the current day’s data will be stored and can be accessed immediately.ga4 bigquery export types
  7. Review your settings, then click Submit to finish setting up your link. 

Once the link is created, it can take up to 24 hours for your data to appear in BigQuery. For daily exports, a new table will be exported each day that contains the previous day’s data.  

Understanding the Data Schema 

Now that you’ve set up your link, the next step to unlocking the benefits of the GA4 BigQuery export is understanding the structure of the data. 


For Event data exports, a table named events_YYYYMMDD is created each day if you have enabled the Daily export option. If you’ve also chosen to export streaming data, you’ll see another table named events_intraday_YYYYMMDD, which is continuously populated as events are recorded throughout the day.  

The User data export will create up to two new tables. The table named pseudonymous_users_YYYYMMDD contains rows for every pseudo user ID, excluding users who have not consented to cookies. If you’ve set up user ID collection for your website and are sending that data to GA4, you will also see users_YYYYMMDD tables, which include data for unconsented users. For both User data table types, rows are updated when there is a change to one of the fields. 

Data Schema 

The columns in each table type represent the parameters that are available for querying. Google has provided detailed explanations of each parameter for both the event data export and the user data export in their documentation. 

How to Query and Analyze Your BigQuery GA4 Data 

Now that you’ve set up your link and gained an understanding of data schema, it’s time to put your data to work. SQL is the language used to interact with the tables in your BigQuery dataset, and it offers a standardized way to communicate with your data. Here’s how to access the built-in query editor in BigQuery: 

  1. Login to Google Cloud Console: Go to the Google Cloud Console and sign in with your Google account. 
  2. Access BigQuery: In the Cloud Console, click on the navigation menu () in the top-left corner and select “BigQuery.” 
  3. Select Your Project: Ensure you have the correct Google Cloud project selected in the project dropdown at the top of the BigQuery Console. 
  4. Write SQL Queries: 
    • Click on your dataset on the left-hand panel, where you have your GA4 data stored. Select the table you want to query. 
    • Click the “Query” button. This opens a pane where you can write and execute SQL queries. 

If you’re just getting started with SQL, there are many free resources online to help you learn the language, such as Codeacademy and Datacamp. A great resource for generating GA4 BigQuery queries specifically, without writing any SQL of your own, is GA4 SQL. This tool allows you to select the metrics, dimensions, and filters you want to apply to the raw data export and paste them as-is into the query editor. Google has also provided some basic and advanced queries in their Query Cookbook for Google Analytics to help you get started analyzing your data. 

As you become more comfortable with SQL, you can modify and create custom queries tailored to your specific business needs. SQL is a versatile tool that empowers you to interact with your data and uncover valuable information, whether you’re a beginner or an experienced user. 

If you’re eager to harness the benefits of exporting your GA4 data to BigQuery, you can also reach out to Synapse SEM for help. Our team of experts can handle everything, from setting up the export to creating comprehensive reports and analyses that provide actionable insights. Contact us by email at sales@synapsesem.com or by phone at 781-591-0752 to get started. 

UA VS. GA4: A GA4 Guide for Beginners

Are you used to Universal Analytics and dreading learning the new GA4 interface? If you’re unsure of how to jump into the new platform, where to find reports, or how to analyze your site data, you’ve come to the right place. Read on to get an overview of the new analytics platform, including metric definitions, customizing your property, and how to analyze GA4 data vs. Universal Analytics data.

Default Property Setup
universal analytics vs GA4 guide
  1. Account and Property Name
  2. Explore reports
  3. Default Reports within the “reports” menu option
  4. Library used to customize collections and reports

Important Metric Definitions in GA4

Several metrics we are used to analyzing in Universal Analytics have new definitions within GA4 and are calculated differently. For this reason, if you are comparing UA numbers vs. GA4, you will notice discrepancies in your data. Below is an overview of some common metrics and their GA4 definitions.

GA4 Metric Definition Comparison to Universal Analytics
Total Users Total number of users. Compares to the “users” metric in UA.
Active Users Any user with an engaged session. The primary user metric of GA4. n/a
New Users Users who interacted with your site or app for the first time. New users to the site in UA.
Conversions Events that have been marked as a conversion. A “goal” in UA.
Views All pageviews plus screen views for an application. If you don’t have an app, it is just counting pageviews. Pageviews in UA.
Views per user The number of pageviews and screen views per user. The replacement metric of “pages per session.”
Engaged Session A session that lasts longer than 10 seconds, has a conversion event, or has at least 2 views (pageviews or screen views). n/a
Engagement Rate The percentage of sessions which were not engaged. n/a
Bounce A session that is not engaged Bounce existed in UA but was calculated differently and therefore cannot directly be compared to GA4.
Bounce Rate The inverse of engagement rate. The percentage of sessions that were not engaged. Bounce rate existed in UA but was calculated differently and therefore cannot directly be compared to GA4.

Common Analyses & Default Reports in GA4

One fault of Universal Analytics was that there were so many default reports, it was sometimes hard to find the one you were looking for. Within GA4, there are fewer defaults, but many of the high impact analyses still exist (and if they don’t, you can add them! See the next bullet).



The image to the left outlines the collection which houses several popular analyses. You’ll notice each topic has an overview under it. These overviews contain cards that act as a summary of each report within the topic (topics are the headlines such as Acquisition, Engagement, and Monetization).

1. Acquisition

User acquisition and traffic acquisition are the two default reports here with very similar setups. The core difference between these reports is user acquisition uses user data as the primary and secondary dimensions, whereas traffic acquisition uses session data (i.e., session default channel group).

2. Engagement

The engagement topic houses reports by event names, conversions, pageviews, and landing pages. The landing page report is commonly used.

3. Monetization

Monetization houses everything ecommerce-related, from performance by item (ecommerce purchases) to promotions (promos set up via Merchant Center).



Customizing Your GA4 Property

You may have noticed that there are fewer default reports within GA4 versus Universal Analytics. Instead, Google has given users the ability to customize their property to fit the needs of their organization. There are three, main types of customizations that can be made:

1. Add/delete reports within a collection:

  • In the library (#4 above), you can add or delete collections (groups of reports) or individual reports by clicking the three dots. If you add a new collection, be sure that you click the three dots again and click “publish,” otherwise it will remain unpublished and just visible within the library settings.
  • NOTE that customizations within the library or default reports are visible for all users who have access to the property. Consult the rest of your organization prior to making large edits.

2. Update the default dimensions and metrics within individual reports:

  • Updates to default metrics and dimensions can either be made within the library (find the specific report name and click the three dots on the right-hand side to edit the report), or on the specific report by clicking the “customize” pen icon. From there, use the right-hand rail to modify the report data.

3. Create Explore reports:

  • Explore reports are the new version of custom reports from Universal Analytics, #2 above. These reports are only visible for the user created them, unless shared. These reports are recommended for common analyses and data pulls.



This should be enough to get you a jump start into GA4! If you need additional assistance or would like help with your own property, please contact us by email at sales@synapsesem.com.

Content Marketing in the Age of AI: 5 Tips for SEO Specialists

In today’s digital landscape, content marketing is a critical component of any successful company strategy. According to the Content Marketing Institute, 73% of B2B marketers and 70% of B2C marketers use content marketing as part of their overall marketing strategy. However, to stand out in the vast sea of content, businesses and SEO specialists are turning to newly available artificial intelligence (AI) solutions to gain a competitive edge. They are using AI technology to streamline content creation, optimization, and distribution, making it more targeted and effective. In this article, we’ll explore five ways SEO specialists and marketing managers can leverage these innovative tools in the age of AI content marketing.

1. Leverage AI-Driven Keyword Research

AI tools, such as Frase.io, have the ability to identify high-impact keywords, taking into account relevance and competitiveness. By analyzing vast amounts of data and helping to identify the most relevant and high-traffic keywords in a fraction of the time it would take manually, artificial intelligence provides businesses with a competitive SEO edge. These tools can also provide valuable insights into user search patterns, helping companies understand their target audience’s preferences.

2. Optimize Content with AI-Generated Insights

AI can provide valuable insights on content optimization, such as recommended word count, readability, and much more. These insights can significantly enhance your on-page SEO. With the help of the insights gathered from AI SEO tools, digital marketing agencies can then use the data to fine-tune content to align with these insights, ensuring all content is optimized for search engines and user engagement.

3. Enhance Content Personalization with AI

Content personalization is crucial in today’s world of organic search, and AI content marketing tools have significantly enhanced the ability of SEO specialists, marketing managers, and writers to create tailored content. AI-driven content optimization solutions, such as SEO.ai, can provide relevant keyword and phrase recommendations that aid in making the content more appealing to a certain audience, leading to improved search engine rankings and visibility. For example, you can submit a drafted piece of writing to certain AI tools, and in return they will provide content tweaks and recommendations on how to further personalize and improve the initial draft. Additionally, these tools can also be used to recommend which types of content will resonate best with certain audiences and subjects.

4. AI for Monitoring and Adaptation

In the fast-paced digital world, continuous monitoring and adaptation are essential. AI can continuously monitor SEO trends and adapt your content strategy in real-time. This ensures your content remains relevant and engaging. Coupled with the power of AI, marketing agencies offer the agility and responsiveness needed in the AI-driven landscape to keep your content fresh and competitive.

5. A/B Testing and AI

A/B testing is a powerful tool to refine your content marketing strategy. These assessments can be used to evaluate rankings, traffic, time on page, conversions and overall engagement, which can help determine what makes Google and your target audience happiest. With AI tools such as Optimizely or RankScience, you can run A/B tests that are data-driven and help you make decisions based on performance insights.

Can SEO Content Be Written With AI?

In short, the answer is no. While AI content marketing tools can be incredibly helpful SEO assistants in conducting keyword research, generating topics, optimizing content, and evaluating performance, nothing can replace human writing (and no, you can’t fool Google either). Below are examples of human writing vs. AI-generated responses when asking the question “What are featured snippets?” Note how one answer is considerably more informative and flows better than the other.

Human Writing:

Featured Snippets are Google’s way of giving us fast answers to common questions, right in the search results. Often in the form of definitions, how-to instructions, and other answers/solutions, Featured Snippets are separate blocks of content that appear above the organic listings on the first search results page.

Featured Snippets present users with answers without having to navigate to a website. Extracted from a given web page, they contain a summary of an answer, a page title and URL, and a link to the corresponding source.


Featured snippets, also known as position zero or answer boxes, are a type of search result that is prominently displayed at the top of the search engine results page (SERP) when you perform a search on platforms like Google. These snippets are designed to provide users with a quick, concise, and direct answer to their query without the need to click on any of the search results. Featured snippets typically appear in a box just above the organic search results and are often accompanied by a brief excerpt from a web page that is considered a reliable source for the information.

The Power of AI-Driven Data Analysis for SEO and Content Marketing

The Influencer Marketing Hub reports that 61.4% of marketers have used AI in their 2023 marketing activities, and 44.4% have used AI for content production. One of the most significant benefits of AI in content marketing is its ability to process vast amounts of data and provide valuable insights. For digital marketing specialists and managers across a variety of industries, this means being able to identify trends, understand user behavior, and discover the most relevant keywords for optimization. However, managing this wealth of data without the right tools and expertise can be overwhelming.

Benefits of Working with a Performance Marketing Agency

While AI offers incredible capabilities in content marketing and SEO, it can also be complex and time-consuming to implement effectively. This is where working with a digital marketing agency can be a game-changer. Agencies provide a cost-effective and efficient solution for leveraging AI in your content marketing efforts. Some of the key benefits of collaborating with a performance marketing agency such as Synapse SEM include:

Access to Cutting-Edge AI Tools: Agencies often have access to advanced AI tools that may be too complex for individual businesses to implement. This technology can give your content marketing a competitive edge.

Expertise and Experience: Digital marketing agencies employ professionals who specialize in content marketing and SEO. They understand the intricacies of AI tools and can use them effectively to benefit your business.

Ongoing Support: Marketing agencies offer ongoing support and maintenance. As the AI landscape evolves, they can adapt your content marketing strategies (as well as the latest technology trends) to ensure you stay ahead of the competition.

AI is transforming the field of content marketing and SEO, offering powerful tools and insights to SEO specialists. However, it’s important to remember that no tool can replace the value of human-touch, and to use the proper solutions for certain needs. Embrace the power of AI and consider partnering with a performance marketing agency to unlock your business’ full potential. Your content marketing strategy will thank you for it.

Ramp Up Your SEO Strategy

Ready to supercharge your content marketing with AI SEO tools and expert guidance? Contact us today to explore how AI-driven content marketing and SEO can transform your online presence.

What You Need to Know About the Data-Driven Attribution Model In GA4

First click, linear, time decay, and position-based attribution models are going away across Google Ads and Google Analytics

  • Starting in May 2023, Google will remove the ability to select first click, linear, time decay, and position-based attribution models for conversion actions in Google Ads that do not already use one of these models.
  • Starting in September 2023, these four rule-based attribution models will be removed from Google Ads and Google Analytics.

What happens to conversion actions if these attribution models are removed?

Once these four attribution models are removed in September 2023, they will also be removed from the reporting throughout the rest of Google Analytics, including the Overview page and the Model comparison report within the Attribution tab.

Any conversion actions still using these models will be switching automatically to data-driven attribution, the default attribution model moving forward. If you want to continue using the last-click attribution model, you have the option to manually switch to the last-click model. To do that, you would need to access the Attribution section in GA4, which can be found in the Admin tab.

google analytics attribution model

What is the Data-Driven Attribution model?

Data-driven attribution takes into account the actual data collected on customer interactions and behaviors to determine the impact of each touchpoint on the conversion or desired outcome. It utilizes statistical models and machine learning to analyze large sets of data and identify the relative contribution of each touchpoint.

Attribution Reportings in GA4

There are two main reports in GA4, the model comparison tool and the conversion paths report, which can be found in the attribution reports sections.

With the model comparison tool, users can analyze how conversion credit shifts under different attribution models and assess how these models impact the evaluation of different marketing channels. The tool presents data in a table format for conversions and revenue, offering a clear view of these metrics across different channels and different attribution models. For instance, one can compare data from the Last-Click Model with that of the Data-Driven Attribution Model. The model comparison report can help users understand how different models attribute conversions to various touchpoints, before altering the attribution settings in GA4.

google analytics attribution model

The conversion paths report, similar to the funnel report in Universal Analytics, provides the option to switch between various attribution models. This report offers valuable insights into the channels within a multi-channel conversion path, allowing for a deeper understanding of customer journeys.

google analytics attribution model

Potential Concerns Regarding the Attribution Model Update in GA4

The key advantage of data-driven attribution is its ability to provide a more accurate and granular understanding of the customer journey. By considering multiple touchpoints and their interactions, it can reveal the true influence and value of each touchpoint in driving conversions or desired outcomes.

In the meantime, we believe that removing the four attribution models and defaulting to the GA4 data-driven model may lead to an increase in reporting complexity. Rule-based attribution models provide clear and straightforward insights into the contribution of specific touchpoints. They offer a simplified view that makes it easier to understand and communicate with stakeholders. On the other hand, data-driven attribution models can be more complex and make it challenging to pinpoint the channel that is truly driving conversions. Furthermore, since these models necessitate advanced statistical analysis, they may require a substantial amount of data to deliver the most accurate results. 

Other Challenges

The removal of these attribution models may pose challenges in comparing future data with past performance, as the change in the attribution model could introduce discrepancies. The discrepancy in data resulting from the change in the attribution model could hinder the ability to make “apple-to-apple” comparisons and evaluate the effectiveness of marketing efforts over time.

As new features, such as the attribution models and reports, emerged with the new GA4 platform, it is strongly recommended to set up your GA4 prior to the deadline and familiarize yourself with the platform. If you require any assistance in migrating to GA4, please feel free to reach out to us using this form.

How Much Automation is TOO Much in Google Ads?

It is no secret that the entire world is moving towards a more automated way of life. There are now cars that can parallel park themselves, grocery stores with no cashiers, and apps that can use AI to make Elvis sing Taylor Swift songs. The same shift is happening across the digital marketing world with Google becoming more aggressive in pushing their automated recommendations across their advertising platform. While some strategies, like smart bidding can save an advertiser time, others can create an even larger headache leading to unexplained increases in spend, irrelevant asset creation, and unqualified lead generation.

Auto Applied Recommendations:

Google Ads Automation

Google provides an array of standard recommendations that will be automatically applied to your account if you do not opt out of settings. These settings can drastically impact your account performance, account spend, and efficiency. Below includes several settings that we recommend opting out of.

Add Broad Match Keywords:

Perhaps one of Google’s biggest pushes of 2023 is implementing broad match keywords. This will allow keywords to match out to more variations, leading to higher traffic volume and growth. However, the drawback is that many of the queries will likely be irrelevant to your business and they could dominate the budget. For example, if you are running on the keyword “luxury watches” in broad match, you can likely match out to all kinds of jewelry related iterations even “wedding rings.” It is important when launching new accounts or optimizing existing accounts to be weary of Google’s push for broad match and to ensure you have unselected this setting in the recommendations tab before testing.  If you do consider testing broad match, we recommend considering the following before implementing an A/B test.

  • Ensure that you have the budget available to test this expansion.
  • Expansive negatives to account for broader queries coming through.
    • We also recommend keeping a close eye on search term performance daily.
  • Broad match campaign should use automated bidding to work best.
  • CPA should be efficient to begin with as conversion rates will likely be lower.

Add Responsive Search Ads:

While it is a no brainer that everyone should be fully using Responsive Search Ads, we want to avoid Google creating and launching their own ads based on your performance. Not only will this cause issues with unapproved content running, but it also can generate lower quality recommendations. In the past, Google’s headline and description recommendations have included assets with no CTAs, irrelevant content, and very low character counts. We recommend testing and creating all iterations of ad assets without opting into Google’s auto recommendations. With standard RSAs we recommend pinning at least 3 keyword-specific, similar headlines to position 1, so that Google can still use its algorithms to showcase the ad most likely to generate the highest click-through-rate while ensuring your headline is highly relevant to the search term.

Use Display Expansion:

If you are consistently not meeting your search budget, Google might automatically opt your search campaigns into the display network. This means that Google will create ads based on your search ads to run on placements within the display network. Text ads, lacking imagery, across display often result in spam traffic and unqualified lead volume because the targeting is far broader than search. Therefore, to utilize unused budget across the display network, we recommend creating separate display campaigns, with their own responsive display ads. Also, we recommend applying additional layers of targeting onto the campaigns in terms of audiences, custom segments, and placement targeting.

Optimized Targeting in Display:

Optimized targeting is automatically applied to all display, discovery, and video campaigns. Optimized targeting allows Google to expand your audience beyond your targeted reach. The goal of this setting is to broaden your campaign’s reach to similar users based on your targeting settings. However, this setting can have some negative consequences. For example, if you were running a retargeting campaign across display but were opted into optimized targeting, Google would also show ads to users they deem “similar” but have not previously visited your site before. We have seen these audiences eat up the entirety of budgets in display campaigns with minimal conversion volume. When starting out in display, we highly recommend opting out of this setting if able to generate decent traffic volume.

Google’s best practices are not necessarily the best practice designed for your account’s specific goals. This can be the case when it comes to automation. Our ultimate take on automation is that some strategies can be beneficial like automated bidding, however we strongly recommend opting out of the above auto applied recommendations that will mostly lead to increased spend and poor efficiency. It is important to know your account goals and what options make sense for you. Google is constantly changing their platform and the auto apply settings. We recommended reviewing the settings on a monthly cadence and opting out of any option that does not make sense for your business goals. If you have any questions regarding automation best practices, please contact us by email at sales@synapsesem.com to talk through your Google Ads optimizing needs.


The Evolution of Google Ads Match Types

In the realm of online advertising, Google Ads has long been a cornerstone for businesses seeking to connect with their target audience through Pay-Per-Click (PPC) campaigns. Over time, Google has continually refined its advertising platform, including the evolution of match types. While match types initially provided advertisers with greater control and precision, there has been a noticeable shift towards automation, leading to concerns over diminishing advertiser control. In this article, we will explore the journey of Google Ads match types, examine the impact on advertisers, discuss the challenges they face, and review the opportunity this has created for advertisers to grow.

1. Broad, Phrase, and Exact Match

The introduction of broad match marked the beginning of a journey for Google Ads advertisers. Advertisers were excited about the prospect of reaching a wider audience and gaining visibility. However, as broad match keywords cast a wide net, advertisers soon realized that this came at the cost of control and relevance. Ads were displayed for a plethora of unrelated searches, leading to wasted ad spend and diluted campaign performance. 

This is where phrase and exact match keywords came in, with the goal of restoring control and precision for advertisers. Phrase match allowed advertisers to target keyword phrases in a specific order by using quotation marks, while exact match ensured ads only appeared for exact keyword matches. Advertisers created many variations of their keywords to ensure they would show up for all relevant searches, including singular and plural variants, as well as common misspellings.

With phrase match and exact match, advertisers could fine-tune their campaigns, reaching a more relevant audience and optimizing their budget for maximum impact. Advertisers gained a sense of control over their PPC campaigns, resulting in improved click-through rates and higher conversion rates.

2. Broad Match Modifiers

Recognizing the need for a middle ground between reach and relevance, Google introduced modified broad match. This match type offered advertisers the ability to include specific keywords within broad match by adding a plus sign (+) before them. While broad match modified expanded reach, it still provided a certain level of control over ad targeting. Advertisers could cast a wider net while maintaining some relevance, striking a delicate balance. However, it was the last significant update that retained a semblance of control before Google’s subsequent emphasis on automation.

3. Close Variants

With the introduction of close variants, Google expanded the boundaries of match types. While this expansion seemed advantageous at first glance, it signified a shift towards automation. Close variants allowed ads to appear for searches that included variations of target keywords, such as misspellings or singular/plural forms. If the keyword the user searched had a similar meaning to the keyword you were bidding on, then your ad would appear. This applied to all three match types, which was significant as that meant exact match keywords were no longer an “exact” match. This decreased advertiser control as searches that may seem like close variants were matching out to keywords that were designed to only match out to an exact variation. This caused a significant increase in the importance of well-managed negative keyword sets.

4. User Intent

With the integration of user intent into the matching process, advertisers now rely on Google’s algorithms to decipher the context and intent behind search queries, matching them to relevant keyword bids. This shift towards automation means that advertisers must trust Google to accurately interpret user intent and deliver their ads to the right audience. While this automated approach brings efficiency and scalability, it also requires advertisers to have faith in Google’s algorithms and data-driven decision-making. Advertisers are encouraged by Google to embrace the role of strategic overseers, focusing on ad copy, targeting strategies, and understanding their audience, while entrusting Google to optimize the matching process based on user intent.

As Google increasingly focuses on automation and machine learning, advertisers have pivoted to taking on a more strategic role in account management. Google’s algorithms take the reins, making decisions on when and where ads appear. This automation brings efficiency and ease of management for advertisers as this allows them to focus on deeper analysis of campaign performance. The evolving landscape of Google Ads match types, coupled with automation, has led to several implications for advertisers:

  1. Reduced Precision: Advertisers have less control over which specific keywords trigger their ads. As a result, there is a risk of displaying ads to less relevant or unqualified audiences, potentially leading to lower conversion rates.
  2. Limited Budget Control: With automation playing a more significant role, advertisers may find it challenging to allocate their budget effectively. Automated bidding strategies can quickly deplete budgets without clear visibility into the decision-making process.
  3. Dependency on Machine Learning: Advertisers must adapt to Google’s increasing reliance on machine learning algorithms. This entails learning to optimize campaigns within the constraints of automated systems, embracing performance insights, and making data-driven adjustments.
  4. Emphasis on Copy and Strategy: As control over match types diminishes, advertisers need to focus on developing compelling ad copy and refining their targeting strategies to maximize the impact of their campaigns
  5. Importance of Negative Keywords: With a broader range of search terms being matched    out to, effective negative keyword management is critical to success. This ensures that ads are displayed to the most relevant audience, which increases the likelihood of attracting qualified leads and potential customers. 

The evolution of Google Ads match types has brought both benefits and challenges for advertisers. While the initial match types provided control and precision, Google’s emphasis on automation and the introduction of close variants have allowed advertisers to save time by not having to build out extremely granular keyword sets that constantly need to be refined. While there is less control by advertisers, there are still ways to ensure they are reaching their target audience through well thought out match type strategies and negative keyword management. Relying on Google to accurately identify user intent has given advertisers more time to focus on strategic initiatives, ad copy development, landing page optimization, and more. Advertisers must adapt to the changing landscape, navigating the complexities of automated systems while finding new ways to optimize their campaigns. Balancing the benefits of automation with the need for customized targeting and precision remains a key challenge in the world of PPC advertising.

Want to learn more about how to navigate the increasingly complex world of PPC advertising? Reach out to the team at sales@synapsesem.com to learn more about our comprehensive services.

Reels. Shorts. TikToks. How The Consumption of Video is Evolving

In today’s digital age, video content has become an integral part of our daily lives. In fact, 93% of social media marketers say video is a vital component of their social media strategy. Video has been a buzzword in marketing for years, and today brands are using it to establish a clear voice and devoted followings on social media. From the rise of YouTube to the emergence of social media platforms like Instagram and TikTok, the way we consume video has undergone a significant transformation. The introduction of short-form videos, such as Reels, Shorts, and TikToks, has revolutionized the way we create, share, and engage with visual content. Keep reading as we explore how the consumption of video is evolving and the impact it has on our online experience.

The Rise of Short-Form Video Content

Short-form videos have gained immense popularity in recent years, capturing the attention of millions worldwide. Platforms like Instagram Reels, YouTube Shorts, and TikTok have allowed users to create and share bite-sized videos that are typically under a minute in length. This format presents an opportunity for content creators to tell engaging stories, share quick tutorials, showcase talent, and entertain their audience in a concise and visually appealing manner. Did you know users will retain 95% of a message watched in a video as opposed to just 10% read in text? This is just one of the reasons that over 54% of marketers argue video is the most valuable content type for achieving social media marketing goals.

Short-Form Video Appeals to Short Attention Spans

One of the driving factors behind the success of short-form videos is the shrinking attention spans of modern audiences. In an era where information is constantly being thrown at us, capturing an audience’s attention quickly is crucial. A recent study from Vidyard found that 58% of viewers will watch the entirety of a business’ video if it’s less than 60 seconds long. Short videos cater to this demand by delivering content that is easily digestible and captivating within seconds. This format encourages creators to be creative and concise, resulting in content that is entertaining and memorable.

Engagement and Interactivity

Another aspect that sets short-form videos apart from other content is the high level of engagement they promote. Social media platforms like TikTok have introduced features such as duets, stitches, and challenges, allowing users to collaborate, remix, and respond to existing content. This interactive nature of short videos fosters a sense of community, encourages user participation, and provides opportunities for creators to collaborate and connect with their audience in unique ways. Viewers feel more connected and invested in the content when they can actively engage with it. In fact, The Sprout Social Index found that 66% of consumers report short-form video to be the most engaging type of social media content in 2022, up from 50% in 2020.

The Democratization of Content Creation

The rise of short-form videos has also democratized content creation. Previously, creating professional-quality videos required expensive equipment, technical skills, and significant resources. However, the accessibility of smartphones with high-quality cameras and user-friendly editing apps has empowered individuals from all walks of life to become content creators. Not to mention the ring light. This new era of content creation has allowed for a diverse range of voices and perspectives to be heard and has opened up new avenues for creativity and self-expression.

How Short-Form Video is Changing the Social Media Landscape

Short-form videos have had a profound impact on the social media landscape. Platforms that were primarily focused on static images and text-based updates are now incorporating video as a central component of their user experience. Instagram introduced Reels as a direct response to the popularity of TikTok. YouTube optimized its platform for shorter videos called “Shorts”. Facebook took a similar approach, introducing their own version of Reels. This shift demonstrates how platforms are adapting to changing user preferences and investing in short-form video content to retain and attract users. Due to higher retention and engagement rates and stronger SEO performance, everyone is vying to be the top platform delivering short-form video content.

The Influence of the Algorithm

Have you ever felt like your social platforms are listening to you? Algorithmic feeds play a crucial role in shaping the consumption of video content. Platforms like TikTok and Instagram use sophisticated algorithms to curate personalized video feeds based on user preferences, behavior, and engagement patterns. By analyzing user interactions, the algorithms present a stream of videos tailored to each individual’s interests, making it easier to discover content that resonates with them. This approach increases the chances of content creators reaching a wider audience, fostering diversity, and exposing users to a variety of video content.

Video Content Monetization Opportunities

The evolution of video consumption has also introduced new avenues for monetization. Short-form videos have provided content creators, or “influencers”, with opportunities to earn income through sponsorships, brand partnerships, and advertising. Influencers and creators with substantial following can generate revenue by promoting products or services within their videos. Additionally, platforms themselves have introduced monetization features, such as YouTube’s Partner Program and TikTok’s Creator Fund, which enable creators to earn money based on views, engagement, and ad placements.

Future Implications for TikToks, Shorts and Reels

As the consumption of video continues to evolve, we can expect further innovations and advancements in the field. Augmented reality (AR) and virtual reality (VR) are likely to play a more significant role in the creation and consumption of video content in upcoming years. Live streaming and real-time interactions may become more integrated into short-form videos as well, enabling audiences to engage with creators and influencers in real-time. Furthermore, as technology progresses, we can expect to see improvements in video quality, editing capabilities, and overall user experience. This will likely trigger an even further dependency on short-form video content than we are seeing now. If you want to stand out on social and diversify your social media strategy with video, we recommend being consistent, tracking your performance, and experimenting to see what type of content resonates with your audience.

TikToks. Shorts. Reels. Oh My!

The consumption of video content has evolved significantly in recent years, driven by the popularity of short-form videos, and we can expect to see it continue to dominate. Reels, Shorts, TikToks, and other bite-sized videos have captured our attention, thanks to their succinctness, interactivity, and engagement. These formats cater to the demands of modern audiences, providing easily digestible and captivating content. As platforms adapt to these changes, creators and users alike can look forward to a dynamic and immersive video landscape, where creativity and connection thrive. To ensure you are maximizing the engagement on your videos across platforms, contact us today!

Google Ads Experiments: Key Features & Best Practices

It’s no secret that a/b testing is imperative to a successful paid search program—but what does that mean, and what can it look like? There are several approaches you can take when running tests for your paid search campaigns. Maybe you are testing landing pages, running new ad copy, or trying to determine the best CTA for your target audience. In any case, even the seemingly-smallest Google Ads tests can pay off.

So why exactly should you conduct tests? Below we have outlined some of the benefits of a/b testing for your paid search strategy. We also discuss why running an experiment within Google Ads is a great option, and some of the top considerations when determining the best PPC testing strategy for your organization.

Key Benefits of Google Ads Experiments

  1. Continue to Improve Upon Your Paid Search Program:

Not all tests are guaranteed to drive profound and statistically significant results, but the greatest goal and benefit of testing is to identify what works and continue to make it better. Whether your main KPI is impression volume, traffic, conversions, or revenue, running experiments within Google Ads allow you to test things such as ad copy, landing pages, keyword strategy, bidding strategies, extensions, and more. One Synapse client tested a new CTA in their ad copy and landing page messaging and found the new CTA had a 90% higher conversion rate than the original CTA/message.

  1. Stay Ahead of Your Competition:

In an ever-changing paid search landscape, your organization must continue to test to get ahead of competition. If you continue doing what you have always done, you will likely start to see declining performance as your competitors are capturing and converting a larger portion of traffic. Use features in Google Ads such as Auction Insights to keep track of how aggressively your competition is bidding on your keyword set and how that aggression changes over time. Other tools such as SEMrush or Google’s new Ads Transparency Center can help you monitor the specific language competitors are using in their ads.

Google Ads Experiment Features:

  1. Google’s New “Sync” Feature

In January 2022, Google announced they were reconfiguring the experiment process within Google Ads. With that, they rolled out the “experiment sync” feature, in which, any update made within the control campaign would automatically be made in the test campaign (if opted in). Because it is imperative to keep experiments as even as possible and mitigate extra variables, this feature is great. It keeps your campaigns synced and won’t let a minor adjustment (e.g. a bid optimization) influence the results.

  1. Easily Apply Experiment Results in One Click

Along with the experiment updates rolled out in early 2022, Google also made it much easier to adopt testing results with an “apply experiment” button after you have ended your test. To make this decision, Google assists by telling you if you have reached statistical significance, as shown in the image below.google ads testing benefits and features

  1. Keep Messaging Consistent

If you are testing landing pages with a different call to action or overall theme, it is important that users are exposed to that type of language throughout all steps of their sales journey. This includes Google Ads ad copy, whether it be a responsive search ad or display ad. Ad copy and landing page continuity is critical for user experience and minimizing factors when analyzing your test results.

  1. No Reliance on IT or a 3rd Party Platform

One common bottleneck of a/b testing for organizations is the reliance on IT or a 3rd party testing platform to set up a test on the backend. One major benefit of Google Ads Experiments is that you can create experiments within the platform (and your agency partner can completely handle the setup)..

Top Considerations for Google Ads Experiments

Now you’re ready to run with your first Google Ads experiment, but there are still things you have to consider and determine to run your test well. Whether you are just testing the waters with paid search, or looking to level-up your paid search strategy with Experiments, here are a few key considerations to keep top of mind when starting out:

  1. Have you run any tests before? If so, how did they go?
  2. What is the main goal of the test?
  3. What are your competitors doing?
  4. Do you have enough traffic to generate statistical significance within a reasonable amount of time?

Consider these questions carefully as you determine how to run your next Google Ads experiment. What types of tests have worked well for you in the past? Are there any learnings from prior tests that you can apply to a new test?  Think about what you want to accomplish and be sure to prioritize your experiments by estimated impact.


Google Ads Experiments are a great way to conduct a/b tests for your paid search strategy. If you need help setting up your experiment or a consultation on your paid search strategy, please contact us by email at sales@synapsesem.com to talk through your Google Ads testing needs.

How Google’s Infinite Scroll Impacted the SERP for Good

“No one clicks over to Page 2”. We’ve all heard this timeless quip, that no one in their right mind would ever be so bold as to want more than 10 options to find what they’re looking for. Publishers and brands would fight for their page 1 rankings, as this, we were told, was the only way to get in front of organic search audiences.

Until recently, Page 2 of Google was an overlooked vestige of search marketing.

But things have changed. In December 2022, Google introduced an infinite scroll feature, which automatically loads new results as you approach the end of the page. While this may be a convenient update for users, it’s causing quite a stir among website owners who rely on page 1 click-through rates for traffic. In this article, we’ll delve into the effects of Google’s infinite scroll update and its potential impact on SEO click-through rates and traffic.

What is infinite scroll?

Infinite scroll, or more accurately continuous scroll, is Google’s new SERP functionality that allows searchers to scroll through results past position #10. While not quite infinite – this new functionality requires searchers to click “See More” after the first 60 or so results – this core SERP format update has far-reaching implications for searchers and publishers alike.

This update wasn’t Google’s first foray into the world of stretched SERPs. In October 2021, Google began testing a continuous scroll functionality for mobile devices that would allow cellphone searchers to explore an unending SERP.

How does infinite scroll impact organic CTR?

In the past, Page 1 keyword rankings were the name of the game. The logic went that if it wasn’t on Page 1 of Google, it simply didn’t exist. When applied to large brands and their SEO content, this rightfully concerned anyone aiming to improve their organic search performance. Sure, ranking in position #11 was better than not ranking at all, but data shows that as of November 2022, only 8% of desktop users were clicking on results from Page 2. With the barrier to lower-ranked results now gone, it’s possible your page ranking in position #11 might now generate significantly more traffic. 

Continuous Scroll

The internet is flush with references to the obscurity of Page 2 results.


Whether searchers enjoy Google’s new infinite scroll functionality is still yet to be seen. However, as the curious digital marketers we are, the Synapse team set out to answer a glaring question: how does infinite scroll impact click-through rates by position?

How to Determine Infinite Scroll Click-Through Rates

We devised a plan to answer this question the only way we knew how: by crunching the numbers. (If there’s one thing we love here at Synapse, it’s data-driven insights!). We downloaded two sets of desktop search data from our clients’ Google Search Console profiles: 6 months before the desktop infinite scroll update launched and 6 months after. For each timeframe, we compiled a list of over 80,000 queries, their position, and their CTR. To avoid inflating the data, we filtered out branded queries (including close variants) and any query with fewer than 10 impressions over the 6 month period to avoid any one-search-one-click 100% CTR data points.

We used this data to calculate the average desktop CTR for each position in the SERP. By grouping all non-brand queries ranked in position #3, for example, we could determine the average CTR for this position. A quick pivot table later and we had the average CTR for each rank position charted on a line graph.

The Results

So what did we find? Surprisingly, it doesn’t seem that CTRs for formerly-page 2 positions changed all that much. A quick look at the chart shows that after position #6, the pre- and post-update data look about the same. What did change was CTRs for the top 3 positions. Position #1 seems to have experienced a -33% decrease in its organic click-through rate. Similar trends were seen for most other positions up to #6.

Infinite Scroll CTR

Our analysis suggests that while CTR for positions 1-6 fell on average by 20.8%, the rest of the SERP was mostly unaffected.


Before the update hit desktop browsers, position #1 enjoyed an 11.9% click-through rate, according to our data. In the 6 months that followed, its average CTR fell to 7.8%. Similar narratives played out across the top 6 positions, with each position’s CTR falling, on average, -20.8%.

Conclusion: How Did Desktop Infinite Scroll Impact CTR?

Surprisingly, click-through rates for positions previously located on page 2 seem to have not been affected by the infinite scroll functionality. However, our data suggest that positions #1-#6 now experience decreased click-through rates.

So what happened? While it might be impossible to say for sure, it’s possible that as searchers are faced with more information directly in the SERP – featured snippets and quick answers, but also more titles and meta descriptions – they’re less likely to click on any links at all. The zero-click trend is something search analysts have been discussing for years. This October 2022 analysis from Marcus Tober at SEMrush delves into the growing zero-click search trend in great detail. Our data would support this growing trend, as the total CTR for the top 20 positions decreased from 46.8% to 36.6% after the update.

Regardless, changing click-through rates and increased zero-click searches are trends we’re continuing to monitor at Synapse.  In fact, we’re implementing new strategies designed to improve CTRs to help offset any negative impact from zero-click searches. Want to learn more about these strategies and our comprehensive SEO services? Reach out to the team at sales@synapsesem.com.

GA4 POV: Top 3 Benefits and Challenges

Have you recently migrated to GA4 but are still getting up to speed on the actual differences (the good and the bad) between GA4 and Universal Analytics? If so, this blog is for you!

By now we’ve all heard of Google Analytics 4 (GA4) and a majority of us have spent hours and resources migrating to this new and improved platform, but what now? Sometimes change can be difficult and taking the time to learn a new platform when you already have a full plate can be overwhelming. At Synapse, we began migrating our clients to GA4 over a year ago and have taken the time to identify some of the main benefits of this new platform. While we have identified strengths of GA4, those don’t come without challenges which we’re sure you’ll also identify (or already have).

Below we have listed out the top three benefits of GA4 along with the top three challenges we have identified, and what we’re doing to get the most out of the new platform.

Top 3 Benefits of GA4

While many of us are still struggling to learn the ins and outs of this new platform setup, there are some great benefits to GA4 that will up your analytics game:

#1. Customizable Reporting Attribution Model Settings

In GA4 you’re able to choose the attribution model that is best for your business from a list of pre-defined options:

  • Data-driven (recommended & default)
  • Last Click (cross-channel)
  • First Click
  • Linear
  • Position-based
  • Time Decay
  • Last Click (ads-preferred)

If you remember, the default attribution model of Universal Analytics is/was last non-direct click and only GA360 users had the opportunity to analyze data via other attribution models in all reporting (outside the model comparison tool). This update with GA4 allows users to pick the attribution method that best aligns with their company goals and how any back-end data is being tracked. The attribution model each company picks for their new GA4 property will apply to all of the data within the property (rather than just model comparison). This is significant as users will be able to analyze large amounts of data and various dimensions using their preferred attribution, rather than relying on the limitations of UA’s model comparison tool.

#2. Sophisticated Conversion Path Exploration Reports

Universal Analytics had conversion funnel path exploration reports, but GA4 brings these reports to a new level. While you have access to the “conversion paths” report within the “advertising” section, you can also utilize the Path Exploration template within the explore reports section. This report is extremely helpful and has similar functionality to a normal explore report in that you can add segments, dimensions, and metrics, but there is one feature that takes the cake: reverse path exploration. Within your report, click “start over” in the upper righthand corner. This brings you to a blank screen in which you can “start” the report by identifying your ending point first and follow the conversion path backwards, a long-awaited Google Analytics capability. For example, you can now view who filled out a free trial form on your site and exactly which actions they took and pages they visited leading up to this conversion. These findings can aid in marketing decisions, site testing, and much more.

#3. Highly Customizable Interface

While UA’s “Custom Reports” have been replaced with “Explore” reports (more on this later), you can also customize the entire left-hand rail of the Reports section. Are there certain views you constantly look up and you need the ability to drill down? You can go to the “library” and create your own reports under the Lifestyle section, User section, or a net new section (called a Collection). In addition to adding new reports, you can update what is brought into the default reports or even delete reports altogether. For some of our clients, we have hidden the revenue/e-commerce reports as they don’t apply to their business. These reports will be visible to everyone with access to the property so customizations should be fully thought out.

Honorable Mentions:

  • You can track your website and app (if applicable) in the same property (previously a combination of UA and Firebase).
  • Access and own your raw data via a free BigQuery export. Standard properties can export 1 million events into BigQuery without incurring costs, after which the user owns that data and is able to manage, manipulate, and use it after the data retention period set within GA4 has passed.
  • GA4 is set up with better and more intelligent user privacy capabilities. Some features GA4 rolled out to protect user privacy are IP anonymization and the ability to opt in/out of several data collecting mechanisms like ads personalization.

Top 3 Challenges of GA4 (and what to do about them)

We’ve gone over some of the main benefits of GA4 but in full transparency there still are some challenges with the platform. Before we get too set on these challenges, though, know that GA4 is still new and Google has consistently been rolling out updates and improved functionality, so they may not be challenges forever! Let’s get into it:

#1. Explore Reports Can’t Drill Down

If you’re like me, I used to use Custom Reports in UA for almost everything to assure I was only looking at what I wanted and could drill down to very specific data points. This isn’t as easy with explore reports as drill-down functionality doesn’t yet exist, meaning each of your dimensions must be visible at the same time. Because of this, we recommend being very strategic with filters applied to your explore report to negate the data you don’t care about. If the analysis is something you are likely to use often, we also recommend updating the available reports via the library, as discussed previously.

#2: Conversions Are Counted Differently

If you’re comparing conversions between GA4 vs. GA3, you may notice that GA4 is reporting a higher number. This is partially because all conversions within GA4 are events and are defaulted to count “every” event versus each unique event. Recently Google rolled out the option to change the counting method to “once per session” for events marked as conversions which we recommend switching to for most sites. If you do not switch to this counting method, we recommend you analyze conversion volume by analyzing sessions where a conversion event occurred (filtering for event name), rather than relying on the “conversion” metric, to assure you are analyzing unique conversions.

#3: No Google-Supported Way of Preserving Your UA Data

Google has announced that non-360 Universal Analytics accounts will stop collecting new data in July 2023 and that they will delete the Universal Analytics data in July 2024. Users have been forced to migrate to GA on their own and figure out what to do about losing their data. Luckily there is something you can do about this to assure your data is not lost! At Synapse we have developed ADE, Analytics Data Extractor. With this system, we can extract five years (or more) of your Universal Analytics data, house it within BigQuery and populate Looker Studio reports to assure you have access to your historical data. Accessing this data is important for several reasons, the biggest being context into past performance and anomalies to explain and guide future marketing decisions.



Google Analytics 4 is here to stay and while it may be a learning curve there are a lot of great benefits from the platform! If you or your organization need help with your GA4 migration, please reach out to us through the contact form on our website! Further, if you are interested in saving your Universal Analytics data, schedule a demo with our team to learn more about our process and schedule your extraction date!

Top 5 AI SEO Tools of 2023 (+ How to Use AI for SEO and Content Marketing)

No matter where you stand on AI, it’s no longer something we can ignore. In 2022 alone, AI companies received $1.37 billion in venture capital — which is more than in the previous five years combined. And businesses are taking note. According to a recent survey from IBM, 77 percent of businesses used or explored AI solutions in 2022. Around half of these organizations were already seeing the benefits of AI-powered tools to automate business processes, increase efficiencies, and provide better experiences for their customers, across a variety of industries.

In sales and marketing specifically, 30 percent of adopters reported up to a 10 percent increase in revenue after implementing AI technology.

As technology advances, so too must our digital marketing strategies. Because let’s face it: AI has transformed the search experience. Google uses AI in its algorithms. AI bots like ChatGPT are putting quick answers—and research—right at our fingertips. And AI-powered writing assistants are becoming increasingly popular to create web-based content and improve efficiencies across marketing teams.

Synapse SEM has investigated, trialed, and tested several popular AI tools on the market, to understand their value and potential application in the search engine optimization (SEO) space. We’ve also explored Google’s perspective on AI in relation to content creation for SEO, and compiled recommendations for how to use AI effectively in your SEO strategy. Let’s dive in.

5 Ways Businesses Can Use AI to Enhance Their SEO Strategy

Before delving into the possible AI tools that marketing professionals can use, let’s first cover what they can be used for. Here are some of the many use cases we’ve identified for AI-powered platforms in the world of search engine optimization.

  1. Early Keyword Research

AI SEO tools can be used to curate lists of popular keywords related to a given topic. Depending on the platform being used, there may be a dedicated feature for keyword research. Or, if you are using an AI chatbot like ChatGPT, you can simply ask it to generate a list of keywords related to your query. However, there are limitations to this, which is why we suggested “early” keyword research. These tools can provide a jumping point for keyword ideas but should be supplemented with KPIs like search volume, historical conversions, and difficulty.

  1. Topic Generation and Outlines

Similarly, AI tools can assist in developing blog topic ideas, as well as outlines to support them. For example, you can command an AI bot to craft a catchy headline for a blog post. An AI tool can also generate an outline for you, providing key bullet points to hit on in your article, and suggesting various subheadings to use throughout. However, it’s important to remember that these tools do not provide data-driven recommendations. They do not always know the full competitive landscape around a topic, or the search volume behind semantic keyword phrases. Therefore, use these tools for inspiration—but consider some outside research, too.

  1. Content Generation

There are a variety of AI content generators out there now, that can literally write content for you. From Jasper.ai to Frase.io, these tools have the power to write long-form content with a little guidance from the user. You can say, “Write a blog post about the impact of AI on SEO” or, “Write a paragraph about popular AI writing tools.” An AI bot will quickly gather and process content from all corners of the web, to put together a one-of-a-kind piece that you can use for marketing purposes. However, be aware: These tools are borrowing information from other web pages. While they will not copy content word-for-word, they will create summaries of what others are saying. They may not provide the real value you are looking for (or the real value that you need to rank highly in Google today). Further, it is not possible to know whether the information they provide is accurate. AI writers have the potential to fill your content with inaccurate, unreliable, or simply uncited research – therefore requiring a human-grade QA.

  1. Meta Tags and Website Coding

Several SEO-focused AI tools are familiar with the basic best practices of meta tag generation. For example, Frase and Jasper both have tools that can craft meta descriptions for your page, with just a little direction provided. They will provide a handful of options, within the recommended character count, for your selection, using the same logic as their writing assistants. Other AI tools, ChatGPT being one example, can help you with the development of code to use on the back-end of a website. For example, I asked ChatGPT to provide me with the HTML code for a meta description. It said:

However, a meta description is just one example of the many codes ChatGPT can provide. You can also ask this AI chatbot about Schema Markup, noindex and nofollow tags, Robots.txt coding, and more. Always be sure to QA what the AI tool provides you, though, as ChatGPT bases its recommendations only on learnings from other web results (and they may not be accurate).

  1. Content Syndication and Link Building

Just as AI-assisting writing tools can build content for your website, they can also build content for your social media posts. How does this impact SEO, you might ask? Sharing your content on social media is an important part of increasing your brand’s visibility, and has the potential to attract backlinks to your site. You can use AI to help craft engaging social media posts that feature your content. Jasper.ai and Frase.io both have tools to aid in Instagram captions, for example.

Social syndication isn’t the only means of building links, either. Email outreach is another way to get your content in front of a larger audience, and build links back to your brand. You can use an AI-powered platform to develop professional email outreach templates to promote your content, request backlinks, or ask about guest blogging opportunities.

5 Examples of AI SEO Tools that Marketers Love

There are an extensive number of AI-powered tools available to businesses and agencies today. ChatGPT is perhaps one of the latest to hit this list, but the general concepts behind these technologies are similar. For marketing professionals, AI tools are being used to increase efficiencies in content development, ad generation, and website optimization purposes. Here are some examples of the most popular AI tools we came across for SEO purposes:

1.     ChatGPT:

ChatGPT is an AI-powered chatbot that was designed to simulate online customer care. However, even that definition is an understatement. Launched in November 2022 by OpenAI, this chatbot has already taken the world by storm. In fact, this AI tool set the record for the fastest-growing platform within just two months of being launched, and recently became one of the 50 most visited websites in the world.

ChatGPT has the power to answer complex questions quickly and perform in-depth tasks, such as generating website code, drafting outreach emails, and—yes—writing content.

The tool is rooted in GPT (Generative Pre-trained Transformer) architecture. This means it has been trained on a large dataset of text and statistics from the internet, and further programmed to accurately craft sentences, generate answers, write articles, as well as learn from its users. It is designed to mirror human-like dialogue.

Of course, I put ChatGPT to the test. When asked how ChatGPT can be leveraged for SEO, it replied:

Thanks, ChatGPT! Overall, I found that the tool – when it was accessible (it’s frequently at capacity) – was a great way to get quick answers and topic ideas. For content creators, ChatGPT could be an excellent resource for overcoming writer’s block, generating catchy headlines for blogs, or even developing an outline or bullet points for a forthcoming blog article. However, I would not recommend relying on it for content writing or optimization. This is for two main reasons:

  • ChatGPT essentially summarizes what else is on the web. It does not provide uniquely valuable content and may not provide the most helpful content for your readers. Similarly, it may not provide the most accurate information or research, because it’s borrowing from other corners of the web.
  • It does not apply competitor insights or best practices to the content it creates. It does not assess the top-ranking websites, understand which headlines would be most effective, or utilize semantic keywords to help your content rank.

With that, I would recommend utilizing ChatGPT as a guiding point for SEO tasks like:

  • Blog ideas. ChatGPT can generate outlines, headlines, bullet points, and even statistics to help guide your blog content.
  • Code generation. ChatGPT has a good grasp on things like noindex tags, structured data, and meta descriptions. Just remember to QA what ChatGPT recommends—it’s not always accurate.
  • Short content inspiration. We don’t want to ignore its content development features, but take them with a grain of salt. Try using ChatGPT to create short snippets, such as for a new Facebook post, product description, or quick blurb to try and get that Featured Snippet.
  • Email generation. The content produced by ChatGPT doesn’t need to be applied to websites, but could also be used to craft emails quickly—especially ones being sent in bulk.

2.     Jasper AI:

Jasper is an impressive AI platform that generates content about 10 times faster than a human writer. Its primary purpose is for copywriting, but that can be applied to various functions: generating product descriptions, creating listicles for articles, writing introductions and conclusions, developing YouTube topic ideas, creating captions for Instagram, and coming up with compelling headlines for your blog posts. The tool also creates personalized cold emails, develops meta tags for various page types, and features a variety of advertising assistance, such as:

  • Generates headlines and descriptions for Google Ads
  • Develops headlines and primary text for Facebook Ads
  • Creates posts and descriptions for Google My Business
  • Drafts unique real estate listings
  • Builds Tweets and TikTok captions

I couldn’t begin to describe the 50+ features that Jasper offers, but they all work in a similar fashion. Users input some basic information (i.e. about your brand, product, or blog topic) and the AI software will generate the content at the click of a button. You can also request the tool “regenerate” the content if you don’t like it, or give it more specific direction using “commands.”

So, I also put Jasper to the test. And my first impression was great – the tool is easy to use, intuitive, and full of useful templates to try. I found it especially helpful for overcoming writer’s block when I was stuck on a section of an article, and coming up with captivating headlines for my posts. It also was valuable when creating an outline for a blog, with it providing unique angles on a given subject. However, the more I used it, the more I became frustrated with the tool’s output.

Simply put, it was not giving me human-quality content. Jasper often wrote multiple paragraphs of content around the same topic, reinforcing the same exact points in different words, without offering unique value. When I commanded it to find a statistic to incorporate, I found some figures were outdated and I was not given a link to confirm the sources. Occasionally, the tool would go astray and off-topic from the core points of my article, pull in typos, or gather bizarre verbiage from the web.

Because the tool relies on the web to extract and create content, its sources are wide and vast. This is great in that it’s evaluating many different types of content out there; however, it also poses a high risk of compiling misinformation about your topic. The internet is full of misinformation, and when Jasper generates content, it’s hard to know what’s fact and what’s fiction.

With that in mind, I’d recommend using Jasper for:

  • Content writing inspiration
  • Blog outline development
  • Headline ideas
  • Short snippets of content, including ad and social post development

But, be wary of longer-form text, statistics, and other information compiled by the tool. Always QA!

3.     Frase.io:

Frase is an AI SEO tool that is very similar to Jasper, in that it’s essentially a content writing assistant powered by AI. The system offers a diverse range of SEO and content-focused tools, including (but not limited to):

  • An article writer
  • Blog title idea generator
  • How-to blog post generator
  • Blog outline generator
  • Meta description developer
  • Content re-writer
  • Semantic topic research
  • Listicle creator, for questions, bullet points, and more
  • Product description generator

Frase also offers some additional features for SEO optimization, such as a long-tail keyword research tool, based on SERP analyses, and a Content Analytics feature, based on Google Search Console insights.

As an SEO-focused AI writing assistant, Frase works a little differently than Jasper. Frase actually does some competitive research for you, suggesting and creating content based on the top-ranking search results for your target keyword. Frase also shows you the competitors that are ranking on your topic and enables you to create a content brief or outline inspired by the most successful competitors.

When I put Frase IO to the test, I was impressed with its ease of use, multitude of features, and SEO capabilities. The content it generated for me also read very well and sounded relatively human. However, I still ran into some of the same challenges that I did with Jasper: I questioned whether the content was fully accurate, and more significantly, I was not blown away by the content output.

I ran into very few grammatical issues with Frase, but ultimately found that it contained a lot of “fluff.” Similar to Jasper, there was not a lot of intention and meaning behind the paragraphs. The tool occasionally went astray from what I was hoping to convey in my article. I needed to remove and re-work many of the paragraphs it generated. At the end of the day, I am confident that with a little more time, I could’ve written a much better article from scratch.

With that, I would still recommend using Frase to overcome content hurdles and improve efficiencies when developing an SEO content plan. Specifically, my favorite use cases of Frase were as follows:

  • Creating content outlines – Frase not only suggests headlines and subsections for your article, but also bases these suggestions on competitive insights and real-time SERP results. Frase also allows you to pull in statistics, frequently asked questions, semantic keywords, and more into your content briefs – which can be very helpful for freelance writers.
  • Overcoming writer’s block – Similar to the other tools mentioned here, Frase IO is great for getting quick blurbs of content created when you feel stuck. This does not only apply to blogs; Frase could also be used to come up with social media post ideas, product descriptions, taglines, YouTube video headlines, and more.
  • Developing Featured Snippet blurbs – Frase offers a few different tools that can be useful when going after a Featured Snippet result. It has a tool that generates definitions (enter that all-performing “What is…” pillar page) as well as tools for generating numbered lists, pros and cons, summary bullets, and more. With about 15 percent of all queries showing a Featured Snippet in Google, and with Featured Snippets capturing about 35 percent of total clicks, these Frase features are worth trying out. (Again, with a little QA, of course.)

4.     Surfer SEO

Surfer is an automated SEO tool designed to help content creators research, write, and optimize their content for organic search. It is positioned as an “all-in-one” SEO tool that uses artificial intelligence to provide easy-to-understand recommendations for digital marketers. At a glance, however, the tool feels less focused on content generation and more concentrated on the optimization process of web content.

I tried out a few of the key features of Surfer SEO, after taking some time to learn the ropes. Here is a breakdown of the primary tools available in Surfer SEO:

Content Editor

This allows you to optimize your content for SEO purposes. It is not an AI writing tool in its entirety, but rather, an AI-powered editor that is aimed at boosting your search engine rankings. The tool allows you to input your content or article and then scores it on various aspects like word count, headings, number of paragraphs, images, and semantic keyword usage. What I particularly enjoyed was that, on top of the score, it provides you with suggestions for improvement in these areas. It suggests your ideal word count (based on the search results), the types of headings you should be utilizing in your article, and semantic keyword phrases to utilize based on natural language processing.

Surfer’s Content Editor does provide you with unique, snippets of text that you can add to your article, assisting the writing process. For example, for the topic of “AI and SEO,” the tool provided me with suggested content around questions like ‘Will SEO be taken over by AI?’ and ‘How is AI used in SEO?’ In addition, the Content Editor provided competitors that I might reference while writing the article – an important part of any content outline – as well as a review of the content to ensure your article is fully unique (no plagiarism detected!).

Ultimately, I see Surfer’s Content Editor as a wonderful addition to any SEO or content writing toolkit—because it is optimization-focused. It can help you create SEO-focused outlines and refresh old articles that do not meet SEO best practices. However, these features do overlap with previously mentioned tools, like Frase.io, so I would recommend playing with each to decide on your use cases, and which UX you prefer.

Keyword Research

In addition to its robust content editing features, Surfer offers an automated keyword research tool. You type in a focal keyword for your article, and it will generate a range of related topics and topic clusters that you can incorporate into your content. Upon researching “AI and SEO” in this tool, I was given topic clusters relating to AI content generation, machine learning and SEO, how to automate SEO, and more. The tool also allows you to filter by intent and search volume, to help you get the most out of the recommendations. Overall, I found this to be very helpful for another “all-in-one” keyword research tool, but the information provided does overlap with what other SEO tools (like MOZ and SEMRush) provide.

SEO Audit Tool

Surfer’s Audit tool allows you to input any page on the web, as well as focal keywords for that page, and quickly receive recommendations for improved SEO optimization. The Audit tool is AI-driven in that it analyzes data from the top-performing pages in the search results, and provides uniquely tailored SEO recommendations based on those insights. The Audit provides recommendations related to backlink opportunities, internal linking strategy, keyword usage, word count of page, structure of content, load times, and more. This could be a very valuable tool for SEO professionals to find everything all-in-one place. However, the insights might overlap with what you’d find in other solutions, like MOZ, SEMRush, and others.

From my Surfer SEO trial, I found that this could be a great AI-powered SEO tool for existing content optimization, with supplemental features for keyword and competitor research. This tool is definitely geared more towards content creators seeking to better SEO optimize their web pages quickly. However, Surfer is not an entirely “all-in-one” solution. When thinking about all angles of SEO, it falls short of providing in-depth competitor analyses, structured content outlines, internal linking recommendations (and other writing components), coding and schema updates, and more.

5.     Grammarly

Grammarly is an AI-powered online writing assistant that has quickly become a part of my trusted content marketing toolkit. Historically, the tool was not an AI content generator but rather a content editor. Grammarly has long-been an excellent tool for reviewing content for spelling, grammar, syntax, clarity, and delivery mistakes. It ensures you are producing high-quality, mistake-free content. And it does this quickly and easily.

All you need to do is paste your content into Grammarly’s online application, and the AI-powered tool gets to work. It underscores any potential grammar, spelling, or punctuation issues, and lets you know when a sentence is not concise. But this is just at the basic level. An upgraded version of Grammarly can provide you with suggestions to enhance the vocabulary and tone used in your article. It can also assess the formality and fluency of the content, re-write unclear sentences for you, and flag any content that is plagiarized. While the free Grammarly plan is limited to very basic and critical content issues, the Premium version offers over 400 types of checks and feedback in real-time.

For the savvy writers looking to create excellent content, Grammarly is a unique and (in my opinion) essential AI content writing editor that will truly hold your work to high quality standards—which, as we’ll get into next, is essential for strong organic rankings.

Recently, Grammarly did launch the beta version of a new tool called GrammarlyGO, which is worth highlighting here. GrammarlyGO integrates into the traditional Grammarly dashboard, whether you have the free or premium version, and provides AI-assisted content ideas when you’re facing writer’s block. You can use it to generate headline and outline ideas for your blog post, or even to craft paragraphs of text. Below are some examples of output I received for this article, from this easy-to-use tool:

GrammarlyGO’s AI writing assistant can help you to:

  • Generate ideas for a blog post
  • Write a thank you note
  • Craft an engaging email
  • Respond to a customer complaint
  • Write a marketing proposal
  • Draft a sales report
  • Announce a new product or service
  • Tell a story

And so much more. You can also adjust the tone, level of formality, and goals of the content within this AI tool. However, similar to the other tools listed here, GrammarlyGO does not appear to be founded in SEO best practices. It also does not share its sources of content, which could cause you to question its reliability.

Summary of AI SEO Tools and Use Cases

Use Case ChatGPT Jasper AI Frase Surfer SEO Grammarly
Keyword Research Average Not Available Great! Great! Not Available
Headline Generation Average Great! Great! Good Good
Content Outlines Average Great! Great! Good Good
Competitive Research Suboptimal Not Available Great! Great! Not Available
Content Writing Average Good Good Not Available Good
Content Editing Good Good Good Not Available Great!
SEO Content Optimization Suboptimal Great! Great! Great! Not Available
Meta Tag Creation Good Great! Great! Great! Not Available
Technical SEO Average Not Available Not Available Not Available Not Available
Social and Email Copy Generation Average Great! Great! Not Available Not Available

What Does Google Have to Say About AI and SEO?

Google recently released updated guidance about AI-generated content. In this February 2023 release, they confirmed that automation has long been used to generate useful content, and that there can be value in using AI tools to create helpful, exciting content for your website. However, Google discourages the use of AI tools for creating content for SEO’s sake: “If you see AI as an essential way to help you produce content that is helpful and original, it might be useful to consider. If you see AI as an inexpensive, easy way to game search engine rankings, then no [you should not use AI to generate content].”

Here are some key snippets of Google’s 2023 statement on AI content generation:

“When it comes to automatically generated content, our guidance has been consistent for years. Using automation—including AI—to generate content with the primary purpose of manipulating ranking in search results is a violation of our spam policies

“This said, it’s important to recognize that not all use of automation, including AI generation, is spam. Automation has long been used to generate helpful content, such as sports scores, weather forecasts, and transcripts. AI has the ability to power new levels of expression and creativity, and to serve as a critical tool to help people create great content for the web…

“Google’s ranking systems aim to reward original, high-quality content that demonstrates qualities of what we call E-E-A-T: expertise, experience, authoritativeness, and trustworthiness… Our focus on the quality of content, rather than how content is produced, is a useful guide that has helped us deliver reliable, high quality results to users for years.”

With this, Google suggests that content creators continue to assess (and prioritize) their work’s quality, authority, and trustworthiness. Quality content is the content that will rank well for SEO, whether it’s generated by a human or by an automated tool. However, when AI-generated content is used to manipulate search engine rankings, that would be against Google’s official Webmaster Guidelines.

Google’s Guidelines for Automatically Generated Content

Google Search Central defines automatically generated content as content that’s been generated programmatically, where it’s intended to manipulate search engine rankings. This might include:

  • Text that makes no sense to the reader but which may contain search keywords.
  • Text translated by an automated tool without human review or curation before publishing.
  • Text generated through automated processes.
  • Text generated using automated synonymizing or obfuscation techniques.
  • Text generated from scraping Atom/RSS feeds or search results.
  • Stitching or combining content from different web pages without adding sufficient value.

If your content falls into any of these categories, Google might flag it as spam. And you might see an effect on your content’s organic visibility (or lack thereof).

Google has a variety of systems, including SpamBrain, that help to detect spam content, however it is produced (by a human or by AI). However, during an Office Hours session in April 2022, John Mueller, Search Advocate at Google, revealed that Google cannot yet tell the difference between AI-generated content and human-written content. If AI-generated content is high-quality and informative (even if it was written for SEO purposes), it can rank very well.

What Google Looks for in Content (No Matter How It’s Produced)

Whether it’s written by AI bots or experienced human writers, Google seeks to rank content that is valuable and informative.

“Focusing on rewarding quality content has been core to Google since we began. It continues today, including through our ranking systems designed to surface reliable information and our helpful content system. The helpful content system was introduced last year to better ensure those searching get content created primarily for people, rather than for search ranking purposes,” writes Google in their 2023 blog post.

Danny Sullivan, a Public Liaison for Search at Google, agreed with this sentiment on Twitter, reminding us: “For anyone who uses *any method* to generate a lot of content primarily for search rankings, our core systems look at many signals to reward content clearly demonstrating E-E-A-T (experience, expertise, authoritativeness, and trustworthiness).”

Google’s Helpful Content Update Aimed at Relegating AI-Written Content

Google has consistently expressed a preference for unique, valuable, and authoritative content. It seeks to rank content that showcases expertise on a given topic and offers a learning experience for its readers. It looks for content that is people-first, designed to educate human readers.

Hence, the release of the “Helpful Content Update,” which was first rolled out in August 2022. The Helpful Content Update is a new, automated, sitewide ranking signal that Google now uses to:

  1. Demote low-value content that is not particularly helpful to users, and
  2. Reward websites with high-value, helpful, and people-first content.

The August 2022 roll-out was the first of many Helpful Content Updates. A second was released in December 2022, and Google has stated that more may be on the way: “Over the coming months, we will continue refining how the classifier detects unhelpful content and launch further efforts to better reward people-first content.”

The key word here is “people-first.” Google will devalue websites that have created content primarily for search engines and search traffic, if they are not providing value to real, human readers. The search giant explains: “SEO is a helpful activity when it’s applied to people-first content. However, content created primarily for search engine traffic is strongly correlated with content that searchers find unsatisfying.”

This brings us back to the topic of AI content generation. Why are we using AI? To optimize our content marketing and SEO strategies, right? To churn out more content faster, and meet the growing demands of CMOs to drive organic traffic? At the end of the day, this is the reality. This is how AI is being used. We just have to be careful in how we use it. If AI-generated content isn’t great content—if it’s not helpful, intentional, and unique—it could end up hindering a website’s rankings.

So, how can you assess whether your content is “helpful”? Google suggests asking yourself these questions:

  • Is the content primarily to attract people from search engines, rather than made for humans?
  • Are you producing lots of content on different topics in hopes that some of it might perform well in search results?
  • Are you mainly summarizing what others have to say without adding much value?
  • Are you writing about things simply because they seem trending and not because you’d write about them otherwise for your existing audience?
  • Does your content leave readers feeling like they need to search again to get better information from other sources?
  • Are you writing to a particular word count because you’ve heard or read that Google has a preferred word count?
  • Did you decide to enter some niche topic area without any real expertise, but instead mainly because you thought you’d get search traffic?
  • Does your content promise to answer a question that actually has no answer?
  • Are you using extensive automation to produce content on many topics?

If you answered yes to any of the above, take it as a signal to re-assess your content approach.

Final Recommendations for Using AI in Your SEO Strategy

At the end of the day, it’s safe to say that AI has changed SEO as we know it—and businesses who adopt AI tools to support their marketing strategies are likely to reap the benefits. In the realm of search engine optimization, AI can help to streamline content writing processes and reduce the time it takes to develop SEO-focused topic ideas, article outlines, email outreach, and even coding tasks.

However, after trying out these tools, my stance remains the same. AI-powered content writers and SEO platforms are great assistants. They are helpful support systems. But they are not replacements for humans. AI content writing tools, in particular, are not going to be your token to improved SEO rankings. Google desires content that is written by people, for people—Content that offers unique value, so that readers can walk away feeling their question has been answered. For now, AI is not producing that quality of work. It still needs the human touch.

For the record, I really tried to use AI content writers to compile this article. While I was generally impressed with the ease of use and topic ideas offered by each AI writing assistant, I found the content itself containing a bit too much “fluff.” In other words, the content was not unique. While the AI tools avoided plagiarism, and structured content in a logical way, I was not getting a lot of meaning or purpose behind the paragraphs of text. They felt more like summaries of everything else out there, without driving any single point home. This is, again, because of the way these AI tools work. They compile information from various websites and data sources to create unique content for you. However, AI bots, and specifically AI writing assistants, do not always know how to synthesize that information to develop a coherent story and conclusion.

AI tools also do not (to my knowledge) have a way to ensure accurate information, or ignore bad information—making it difficult for me, the writer, to trust the final output. ChatGPT even admitted this:

I’ll leave you with this conclusion, an example, written by Jasper AI:

While AI tools can be great writing assistants, they cannot replace human writers. This is especially true when it comes to producing high quality content that meets Google’s standards. Always fact check what AI tools suggest and don’t hesitate to get more professional help if you need it.

Do you want more advice about how to leverage AI or improve your SEO processes? Our team of experts are happy to help you plan your next steps.

If you’re interested in enhancing your SEO strategy, including leveraging AI tools, please contact Synapse by email at sales@synapsesem.com.

What is the Google Product Reviews System, and What Does it Mean for Your Digital Marketing Strategy?

Reviews are incredibly impactful – and essential – for business marketing and profitability. According to a recent study, over 99% of online shoppers refer to reviews when making purchase decisions, making them the top factor impacting consumer choices. (Source: Power Reviews)

However, reviews don’t just influence buying behavior – they can also boost your business’ online visibility. Reviews have become a significant component of both paid and organic search marketing strategies, with Google rolling out a series of updates that reward review content in search results.

If you want to stay ahead of the competition, it’s time to start prioritizing reviews in your marketing strategy. In this guide, we review Google’s product reviews system, its impact on digital marketing, and how you can make the most of this algorithm update.

What is the Product Reviews System?

The Google product reviews system is designed to reward review content that is most helpful and useful to searchers. Periodically, Google releases an update to the system, called a product reviews update. The latest February 2023 product review update is the sixth in a series of releases that date back to April 2021.

According to Google’s documentation, the product reviews system is aimed at providing searchers with reviews that include “in-depth research, rather than thin content that simply summarizes a bunch of products.” Rankings may improve after a product reviews update if Google deems the product review as having “content that provides insightful analysis and original research” written by “experts or enthusiasts who know the topic well.”

Any site that publishes review content may be impacted, including:

  • Merchant sites with shopper guides
  • Independent blogs
  • News or other publishing sites

Currently, the product reviews system affects searches in the following languages globally: English, Spanish, German, French, Italian, Vietnamese, Indonesian, Russian, Dutch, Portuguese, and Polish. These updates do not consider user-generated content, like reviews on a product page.

How Does the Product Reviews System Work?

The product reviews system is based on Google’s machine learning algorithm, which uses hundreds of signals to identify “helpful” reviews. Many of these signals are focused on the quality of the review content. According to a blog post from Google software engineer Perry Liu, the system is designed to reward content that:

  • Includes helpful in-depth details, like the benefits or drawbacks of a certain item, specifics on how a product performs, or how the product differs from previous versions.
  • Comes from people who have actually used the products, and show what the product is like physically or how it’s used.
  • Includes unique information beyond what the manufacturer provides — like visuals, audio, or links to other content detailing the reviewer’s experience.
  • Covers comparable products, or explains what sets a product apart from its competitors.

The product reviews system machine learning algorithm may use structured data to understand if a site includes review content. However, structured data is optional and not the only indicator used to identify reviews online.

Content is evaluated by search engine crawlers primarily on a page-level basis. However, site-wide assessments may be made on domains that contain a high percentage of product review content. In other words, if your website does not have many reviews, you’ll only see pages that contain this type of content rewarded by these updates.

The product reviews system requires a periodic refresh from Google. In the past, updates have been anywhere from two to eight months apart. This means you might not see immediate improvements after improving or creating new content. Rather, sites need to make changes and wait for the next update to see rankings improve. Google’s John Muller also explained that the product reviews algorithm might be incorporated into the overall web search rankings at some point. In this case, we should expect to see quality reviews be rewarded on a more consistent basis.

How Can you Benefit from the Most Recent Product Reviews Update?

The most recent February 2023 update to product reviews system has shown a preference for review content across many high-volume, product-focused queries. Since its release, we’ve seen robust review content monopolizing the first-page search results. For one B2B software client, 70% of the SERP on their top sales-driving keyword is review content. This has created a higher level of competition on the SERP.

Even if your website does not focus on review content, you may still be able to take advantage of the next product review update to gain visibility on key terms for your business. There are two ways to benefit from review content as a business selling a product:

  1. Have your products featured on existing 3rd party review websites, such as Capterra or Software Advice
  2. Create your own review content to rank on Google organically

1. Using Capterra to Benefit from the Product Reviews Updates

Capterra is a comprehensive database and search engine that customers can use to browse software options and read user reviews. As one of the largest and most trusted websites dedicated to software reviews, it’s no surprise that Capterra has been affected by product reviews updates. You’ll find Capterra, or other Gartner websites like Software Advice or GetApp, ranking on page one of Google for pretty much any “best” software query.

product review update capterra

The chart below shows an increase in estimated traffic to the Capterra website right after the release of the September 2022 product reviews update.

product review update trafficSource: Semrush

Software companies can take advantage of Capterra’s rankings by running paid ads on their review pages. The Capterra Ads program allows you to bid on the top positions for their software category pages.

product review update resultsSource: Capterra

Advertisers set their bid to receive clicks to their website, with the highest bidders shown in the highest positions on Capterra’s page. Organic listings for products within the category are still present, but they appear further down on the category page. Capterra’s highly specific categories and large user base make it an excellent option for lead generation, especially as the product reviews system continues to reward their website with top rankings on Google.

2. Creating Review Content on Your Own Product

If you want to grow organic traffic to your website, and stay afloat in the current search landscape, you may consider producing your own review content to rank on Google. With the most recent product reviews updates, we’ve seen companies rank with their own high-quality review content that features their products.

For example, A/B testing software provider HubSpot has been able to rank in the #1 position for the following query as of March 2023.

product review system search result

In the ranking article, HubSpot recommends their tool at the top of the list of products, with reasons why a potential customer should choose their product over others. The article then mentions their competitors in a ranked list, with the benefits and drawbacks of each software.

Of course, there are risks to mentioning competitors’ products in an article like this. Just remember that, when creating your own content, you get to control the narrative.

For Google to recognize your content as high-quality and valuable to customers, you must thoroughly discuss each option with in-depth research. This means that you must examine each competitor’s benefits, and not just the drawbacks, which may give customers reasons to choose the competitor’s product over your own.

On the other hand, creating high-quality review content may bring increased visibility to your website with the next product reviews updates release. You can also control messaging on your product and your competitors, directly speaking to why a customer might choose your product over others.

If you choose to create your own product review content, we recommend that you:

  • Follow Google’s best practices for high-quality review content (more on this below).
  • Be thoughtful about which competitors you choose. Since Google recommends you include in-depth research for each option, consider choosing indirect competitors you would not mind discussing in detail. These competitors may fit only partially into your product’s category, have a product that does not include all the features your product does, or do not target your business’s key audiences.
  • Review other listings in the SERP to identify key sections to include and new areas to focus on (that others aren’t doing already).
  • Include informational sections (such as a “What is…” intro or an FAQ section) to establish your expertise and include additional content for SEO purposes.
  • Target a word count of at least 1,000 to 2,000 words.

Best Practices for Creating Product Review Content

When creating product review content to rank on Google, it’s important to ensure that it contains in-depth, helpful research. Low-quality content that simply summarizes the information you can find on the manufacturer’s website will not be rewarded by a product reviews updates. Google has provided the following list of guidelines for writing product reviews:

google product review system guidelinesSource: Google

To make adhering to these best practices easy, we recommend following this structure:

  1. Establish your expertise: Discuss the general features of the product category and identify the key features that users should be looking for.
  2. Recommend your product as the best option: Include supporting evidence and showcase the things that make your product stand out from the crowd.
  3. Rank your competitors: Briefly mention the pros and elaborate on why their cons make their product subpar or consider using indirect competitors to avoid mentioning competition directly.
  4. Recommend your product again: Discuss again why your product is the best overall, as evidenced from your ranking list. Use additional credibility boosters, such as customer quotes. Include links for users to convert.

If you have any questions about the product reviews system, or if you’d like assistance creating review content or managing a Capterra campaign, you can also contact Synapse SEM. Contact us by email at sales@synapsesem.com or by phone at 781-591-0752.

How to Export Google Analytics Data to BigQuery

Google has announced that Universal Analytics will be sunsetting on July 1, 2023.  Per their website, “On July 1, 2023, standard Universal Analytics properties will no longer process data.” On top of the challenge of learning an entirely new analytics platform in GA4, digital marketers are also facing the daunting prospect of losing their historical Universal Analytics data.  Google states:

  • Until July 1, 2023, you can continue to use and collect new data in your Universal Analytics properties.
  • After July 1, 2023, you’ll be able to access your previously processed data in your Universal Analytics property for at least six months. We know your data is important to you, and we strongly encourage you to export your historical reports during this time.

While the exact data deletion date is not yet announced, Google is encouraging advertisers to take action and export their historical data in anticipation of this date.

The “exporting” process is unfortunately easier said than done. Google recommends exporting data in Excel/CSV files, but when we tried to do that for our clients, we quickly realized that that process would not be feasible.  Specifically, we ran into the following issues:

  • To pull unsampled data for multiple years, we had to run hundreds of smaller reports and stitch them together.
  • Attempting to stitch together hundreds of reports took significant time (too much time to complete), and it ultimately crashed Excel and exceeded Google Sheets’ data limits.
  • Most exported data for long date ranges was sampled, making it highly inaccurate.

Ideally, we’d be able to export and download our historical Universal Analytics data directly to Google’s cloud-based data warehouse, BigQuery.  Unfortunately, only paid GA360 accounts have API access to BigQuery (this will become a standard GA feature in GA4), so in standard analytics, data needs to first be extracted into some other type of file format like CSV, TSV or Excel before it can be uploaded to Google BigQuery.  That leaves us right back where we started and facing the issues listed above.

Terrified at the prospect of losing all of our hard-earned data, we’ve spent the last six months working to develop a solution that can export accurate and complete data to Google BigQuery in automated fashion.

We’re excited to announce the launch of our new Analytics Data Extractor (ADE), which:

  • Accurately backs-up 5 years of data with no-sampling and 100% data accuracy.
  • Archives and store data in a cloud-based database (Google BigQuery).
  • Links archived historical GA3 data directly to Google’s Looker Studio (formerly Google Data Studio), where both pre-formatted and custom reports (with Excel exports) will be available.

For more information on how to back-up your Google Analytics data and store it in BigQuery, visit our Analytics Data Extractor website here!



How to Avoid Sampling When Exporting Universal Analytics Data

Synopsis: Options are limited if you’re looking to avoid sampling when exporting your historical universal analytics data in preparation of the migration to GA4.  Our new tool, the Analytics Data Extractor (ADE), reliably and accurately extracts, stores and visualizes your historical Universal Analytics data and prevents your data from being lost.  Learn how you can back-up 5 years (or more) of accurate, completely unsampled data today!

What is Sampling in Google Analytics?

In Google Analytics, sampling is the process of selecting a subset of data from a larger set of data for analysis. This is done to speed up processing time and to reduce the amount of data that needs to be analyzed.

For example, if you have a website with millions of pageviews per month and you want to analyze user behavior on a specific page, Google Analytics may only sample a percentage of the total pageviews for that page. This allows the data to be processed more quickly, but it also means that the analysis is based on a smaller sample size and may not be as accurate as analyzing the entire dataset. In our agency’s experience, even a nominal amount of sampling can lead to significant discrepancies between the reported and actual data sets.

By default, Google Analytics will use sampling when analyzing large datasets, but you can adjust the sampling rate to get more accurate results. This is particularly important if you’re analyzing smaller subsets of data, such as specific user segments or conversion paths, where sampling can have a bigger impact on the accuracy of your analysis. To adjust the sampling rate, you can use the Sampling Level option in the report settings, but keep in mind, this option is only available in the Google Analytics interface.  It’s not an option that is available when exporting data to Excel, and that brings us to a much bigger issue facing digital marketers in 2023.

Sampling and the GA4 Migration

Google’s Universal Analytics will stop collecting data on July 1, 2023, and data will be permanently removed following the close of 2023 (the exact deletion date is TBD). Google is currently urging customers to export historical reports to prevent permanently losing their data.  

Unless you’re a GA360 customer, Google suggests manually downloading your GA data via Excel/CSV.  This is problematic because:

  • To pull unsampled data for multiple years, you would need to run hundreds of smaller reports and stitch them together.
  • Attempting to stitch together hundreds of reports would take significant time, and it will ultimately crash Excel and exceed Google Sheets’ data limits.
  • Most exported data for long date ranges will be sampled, making it highly inaccurate.

How to Avoid Data Sampling?

To combat this issue, we’ve spent the last six months trying to develop a solution to back-up historical Universal Analytics data while automatically avoiding sampling.  We’re excited to announce the launch of our new Analytics Data Extractor (ADE), which:

  • Accurately backs-up 5 years of data with no-sampling and 100% data accuracy.
  • Archives and store data in a cloud-based database (Google BigQuery).
  • Links archived historical GA3 data directly to Google’s Looker Studio (formerly Google Data Studio), where both pre-formatted and custom reports (with Excel exports) will be available.

Historical Universal Analytics data will be safely preserved and fully accessible through GDS for a large number of custom queries and entirely customizable date ranges.  The extraction process can be initiated as soon as you’ve made the switch to use GA4 as your primary reporting platform.  We estimate that most advertisers will be doing that in the April – June time period, and we are currently offering reservations to secure a date for the backup process. We have 5 critical data sets we’ve identified that will be backed up for 5 years, and additional custom data sets (up to 6 dimensions and 10 metrics per data set) can be extracted for an additional fee.

Learn more about how to avoid data sampling while exporting your historical universal analytics data at extractor.synapsesem.com.




How to Use Impression Share to Project PPC Budget

PPC advertising budgets can be one of the most difficult tasks for marketers to figure out as there are many factors affecting this decision. But don’t worry, Synapse is here to help. While it may seem daunting, there are a number of valuable (yet often overlooked) metrics that can be instrumental in figuring out the optimal advertising budget based on your business and your goals. These include impression share and impression share lost due to budget:

  • Impression share: The impressions you’ve received divided by the estimated number of impressions you were eligible to receive.
  • Lost IS (Budget): The percentage of time that your ads were not shown on the Search Network due to insufficient budget.

Using these key metrics, we can project out PPC budgets based on your goals, to ensure your advertising efforts are effective and efficient. Here’s a step-by-step guide to help get you started:

Determine Your Advertising Goals

Are you looking to increase brand awareness, drive traffic to your website, or generate leads? Your advertising goals will help you determine how much you should be spending on advertising each month. Answering these questions can help determine how aggressive you want to be with your budgets.

Gather All Relevant Data

Pull the following data from the “Campaigns” tab (make sure to add any columns that are not already showing) for the last complete month of data to ensure you are using the most up-to-date statistics for your projection.

  • Search Lost IS (Budget)
  • Search Lost IS (Rank)
  • Search Impression Share
  • Impressions
  • Clicks
  • CTR
  • Avg CPC
  • Cost

Adjust Data to Create Average Monthly Numbers

Each month has a different number of days, and seeing that we are projecting an average month of budget, we need to proportionally adjust the data to create a true monthly projection. This applies to impressions, clicks, and cost:

       Ex. (Impressions divided by number of days in the month) multiplied by 30.4 (average number of days in a month)

Calculate Actual Impression Numbers

In order to figure out the amount of spend needed to capture impressions lost due to low budgets, we need to figure out the actual number of eligible impressions:

       Total Eligible Impressions = Impressions divided by Search Impression Share

       Search Lost IS budget number = Search Lost IS Budget Percentage multiplied by Total Impressions Eligible For

       Search Lost IS Rank number = Search Lost IS Rank Percentage multiplied by Total Impressions Eligible For 

Calculate Uncapped Spend

Now we are ready to create projections based on the total number of eligible impressions:

       Total Impressions Uncapped Budget = Impressions divided by Total Impressions Eligible For

Now that we have calculated these metrics, we can get a much clearer picture of how increasing the budget will impact performance. Your final inputs should look something like this:

From here, we can create monthly projections to see how increasing impression share through budget increases will impact clicks, conversions, and revenue:

In this example, we can see impressions, clicks, cost, conversions, customers, and revenue all increase by 50%. While the actual numbers increase, the metrics (CTR, CPC, CVR, etc.) stay the same. In reality, the actual numbers would likely not all increase at the exact same rate, but the purpose of this exercise is to provide an estimate of how increasing budget and impression share will affect overall performance.


One method of calculation to beware of is adding the percentage of impression share lost due to budget back to your current impressions. For example, if your campaign received 1000 impressions last month at a 50% impression share and you lost 25% due to budget, it may seem logical to take 25% of 1000 (250) and add that to your total impressions (1000+250=1250). This method is incorrect as it bases the Lost IS (Budget) number on impressions you received, not total eligible impressions. If you received 1000 impressions at a 50% impression share, that means you were eligible for 2000 total impressions. Therefore, the Lost IS (Budget) of 25% actually comes out to 500 lost impressions. So, if you add back the 500 lost impressions to the 1000 impressions you received, you can project to receive 1500 impressions by increasing your budget.


Understanding the metrics of impression share and impression share lost due to budget can be crucial in projecting PPC budgets and optimizing advertising efforts. By following the steps outlined in this guide, marketers can gather all relevant data, calculate actual impression share numbers, and ultimately create projections based on the total number of eligible impressions. Marketers can use these metrics to estimate how increasing budget and impression share will affect overall performance. By doing so, they can make informed decisions about advertising spend and achieve their advertising goals.

Contact us at paul@synapsesem.com if you’d like to subscribe to the Synapse SEM newsletter, or to learn more about our evolving search engine marketing services.

The Benefits of Investing in B2B Paid Review Sites Like Gartner’s Digital Market

It’s no secret that reviews are pivotal to the success of your business, regardless of the industry. Whether you are shopping for a birthday gift on Amazon or looking for a design team to revamp your company’s website, reviews are paramount in influencing a purchase.

In 2022, Google released a series of Product Review Updates, designed to prioritize valuable review content and research right within the organic search results. As more review articles enter the SERP, a site’s organic visibility has the potential to drop. And that’s where paid marketing can come into play.

According to Gartner, 71% of B2B buyers start their research with a generic search for products or services, and then explore directories and ranking sites to find the best fit for their needs. It is important for B2B companies to opt into these review site partners like Capterra, GetApp, and Software Advice not only to bolster their SEO presence but also as an alternative lead gen strategy to paid search. Websites like Capterra are exclusive to B2B software solutions and attract visitors who are further down the conversion funnel, since they are comparing software and looking for rankings.

Pay-Per-Click vs. Pay-Per-Lead on Review Sites:

Gartner Digital Market’s Capterra, GetApp, and Software Advice offer both pay-per-click (PPC) and pay-per-lead (PPL) solutions for advertisers through their vendor portals. By upgrading your free basic listing to a paid account, you can opt into “bidding” through the PPC program. Like Google search, PPC programs use max CPC bids to show your Capterra listing across 1,200 different software categories. The higher your bid, the higher your listing will rank across dedicated software category pages. You can then view click, cost, position, and conversion data. You will only be charged when a user clicks off the Capterra domain and onto your landing page. Therefore, you can also improve overall brand awareness and credibility of your site.

The pay-per-lead (PPL) program offers marketers an alternative way to reach the right software customers and generate sales qualified leads. When a user opts into the PPL program through Software Advice, they participate in an overview with a Gartner rep who will work with the team to determine targeted buyer profiles. They can then set max CPC bids, like the PPC program, on the leads they want to purchase. These leads have already been pre-screened by free dedicated sales representatives who are experts in the targeted industry to ensure that the lead best fits the organization’s target customer profile. Once approved, the hot lead is sent to the appropriate sales team for further nurturing.

The Benefits of Investing in Gartner Digital Markets:

Efficient Cost/Lead and CPCs:

In most cases, conversion rates across Gartner Digital Market sites are stronger than Google search, leading to a more efficient cost/lead. This is likely due to the user being more targeted and further down the funnel, looking for a B2B software solution. Consider the data below, from an organization that completely shifted away from Google due to high CPCs within their industry and devoted their full marketing budget to the Capterra PPC program.

Global Reach:

Every month, 9 million highly invested B2B customers visit review sites looking for software solutions. Additionally, listings are available in 60 different countries.

Strong Customer Service:

Once you opt into a paid listing within Gartner Digital Markets, you are linked with a dedicated service representative. These reps are available for phone call meetings, budget projections, optimization recommendations and general consulting needs.

Landing Page Creation:

Gartner’s team of experts offers services to create conversion-optimized landing pages for PPC clients. Depending on the package type, these landing pages can be translated into different languages and will connect with your CRM system to funnel lead volume.

Easy to Manage:

The vendor portal platform within Capterra is easy to use and manage. Bid management for all three sites (Capterra, GetApp, and Software Advice) are located under one view. The bid simulator will give estimated positions which can better help determine bids.

Strong Competitor Insights:

With the help of your rep, you can perform deep-dive competitive analyses to see which competitors have opted into paid listings and which categories they are actively bidding on.

As a lead gen focused agency, we are constantly looking for methods to better improve our lead volume to drive qualified, targeted opportunities for our clients. For more information about review site paid efforts, please contact us by email at sales@synapsesem.com or phone at 781-591-0752.