Implementing Segmented ROI Analysis
By Mark Casali
To succeed in online marketing, an agency must be committed to adaptation, innovation, and, of course, optimization. The industry seems to produce a never ending array of methods to improve and refine account performance, but as search marketers, our very own measure of success remains a stagnant and undeveloped concept. Return on Investment, or “ROI,” is typically applied as a blanket-metric, and only assessed at the account level. This evaluation of ROI is distorting goals and leaving perhaps the most obvious optimization opportunities unexposed. In an industry that survives on advancements, it is essential that we begin assessing value and success with more comprehensive and revealing measures.
The easiest method of improving the ROI measurement is to move away from an account level assessment. Regardless of how the marketer ultimately defines ROI, each product/service category should be tracked with an individual return on investment goal. Consider a sporting goods store that has a mature paid search marketing account to promote baseball, football, and soccer ball sales. The store incurs $1,000 of engine spend on each of the three product categories. Revenue earned by the paid search account is $2,500, $2,000, and $800, for baseball, football, and soccer balls, respectively. The store has identified an ROI goal of 1.5 as their break-even threshold; this goal includes variables such as product cost, growth strategies, and lifetime value. Account level ROI is calculated as $5,300 of total revenue divided by a total $3,000 of engine spend, for a return of 1.8.
Most agencies will look at this data and determine that the account is healthy with an ROI well over their goal of 1.5. Additional optimization techniques could be performed within the account to improve click through rates, strengthen conversion rates, and refine cost per click bids. These strategies may well benefit account performance, however, there is a more immediate problem that will be exposed by refining our ROI calculation. If category level ROI metrics are analyzed, the marketer will determine that returns equal 2.5, 2.0, and 0.8 for baseballs, footballs, and soccer balls, respectively. With an ROI less than 1.5, the client is earning additional incremental revenue in the soccer balls channel, but they are detracting from their overall profitability. In fact, the soccer balls product channel would have to nearly double revenue to reach the desired ROI goal. It is unlikely that traditional optimization techniques bridge this gap, especially in a mature campaign. In reality, traditional optimization in this account is insignificant. Segmented ROI analysis has revealed a far more pressing performance issue, and until the soccer ball campaign is suspended, the account, from a profitability standpoint, will significantly underachieve.
This example is admittedly basic, but the underlying principle of identifying and striving towards multiple ROI goals is a powerful optimization technique. The sporting goods store has a simple product offering of three different types of equipment, but actual companies market countless amounts of products and services. Logically, the marketing campaigns promoting these products and services will achieve various levels of success, and some will even fail. So, with such drastic levels of performance across an account, it seems counterintuitive to optimize around a one-size-fits-all ROI goal. A better approach is to calculate separate ROI objectives for each product/service category. This strategy is very much in line with the way search marketers update bids based on keyword performance. The marketer would never bid on a keyword with a negative contribution margin; why then would they apply budget to an entire product category that loses money? This granular approach of assessing ROI on a category/product level is applicable to companies ranging from full scale e-retailers with numerous product lines to institutions of higher education with multiple programs of study.
Once marketers move towards a more segmented ROI analysis, they should also reconsider how they set performance goals. When establishing an ROI goal, the agency or client should develop customized objectives for each product/service category based on a variety of variables including historical performance, the product costs and gross margins of the related products/services, growth strategies, and the assessed lifetime value of a customer associated with a product/service. For example, a marketer may determine that a particular campaign drives so many recurring purchases that a return on investment goal under 1.0 could, in fact, be appropriate and representative of long-term profitability. When establishing ROI goals, the marketer or client should also acknowledge the motives of the campaign. If the ROI goal is set too high, the profitability of the account will be strong, but the volume and reach of the campaign will be restricted. Conversely, if the ROI goal is too low, the campaign will see stronger volume but lower margins.
Overall, the limitations of an account level return on investment assessment are becoming more and more problematic for marketers. Optimization opportunities are lost, and agencies are left striving towards goals that may or may not be advantageous to the client. To correct this problem, companies should track performance for each product/service category and even identify separate financial goals for each of these categories. If this level of granularity is already available, the data should be shared with the company’s search agency so the paid search campaigns can be managed more accurately. The resulting account will offer a deeper level of visibility into performance and help online marketers quickly and easily improve profitability. This is one of the last pieces of low hanging fruit available to paid search advertisers; don’t let it go to waste.