CPA Vs. ROI Optimization: What’s The Best Practice?

Performance measure on a CPA basis is usually is a limitation of tracking – the advertiser cannot associate true revenue with the conversion. Managing to an ROI, and moreover, managing to maximize profit margin for each keyword will open up new doors for PPC efficiency.

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Whenever I’m asked to audit a paid search account for a current or prospective client, my first question to the advertiser is: how do you measure performance? It’s a simple question and the usual response is CPA (cost per acquisition) or ROI (return on investment).

If the answer is CPA, then there are some follow-up questions: how many products or services are offered? And if the answer is more than one, then does each product cost the same? Moreover, is each product worth the same? What I’m getting at is that performance measure on a CPA basis is usually is a limitation of tracking—the advertiser cannot associate true revenue with the conversion. Managing to an ROI, and moreover, managing to maximize profit margin for each keyword will open up new doors for PPC efficiency.

Clients managing to CPA goals generally have several products or services. To see the underlying issue with CPA optimization, consider the situation where we have two possible conversions: one worth $20 and one worth $40. If we optimize to an average CPA of $30, we may be only selling $20 products and losing money. But if CPA optimization is the only option then there are a few best practices to find a good CPA to set as a goal: if the transactions occur online, then calculate the average order value and subtract the average variable cost to the advertiser—this is the max CPA. If the online conversion is a lead which requires offline sales, then multiply this CPA by the average offline conversion rate to define the eCPA (effective CPA).

Whether or not tracking is in place, advertisers are calculating a return on ad cost… so why not put the tracking in place to manage PPC account to the required return? In fact, revenue tracking is available for free in Google Analytics and can easily be merged with AdWords to provide ROI within the AdWords interface. While CPA optimization is a good way to get off the ground, it goes to another level when revenue dollars are brought into the equation.

The first step in ROI or ROAS (return on ad spend) optimization is to define the ROI goal. It will become abundantly clear which terms are ROI profitable versus which are ROI negative. Subsequently, as optimizers, we can try to make ROI negative terms profitable and if unsuccessful remove them. With an ROI goal set, we can manage individual keywords, keyword clusters, and the entire account to a goal ROI using basic logic. But we can take optimization one step further by combining CPA optimization logic with an ROI model to manage to gross profit margin.

Each keyword has a unique average order value (AOV) and it’s logical that any advertiser wants to maximize sales on keywords with the highest AOVs. Simply shifting budget toward the terms with the highest AOVs should maximize ROI. Taking a quick trip back to intro to microeconomics, at some point marginal cost will become greater than marginal revenue—in other words at some point the CPA is greater than the revenue being driven by that conversion. The goal is to identify this point of diminishing returns for each keyword. While this statistical model may be impossible to create perfectly due to noise in the data set, it lays out the groundwork and process for fundamentally sound gross profit margin optimization.

The backbone of a successful PPC account is business intelligence. The more data that can be associated and merged with search engine data, the better. In the end, the less business intelligence an advertiser has, the more money they are wasting. Why waste money when the solution is free?


Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.


About the author

Benny Blum
Contributor
Benny Blum is the Vice President of Performance Marketing & Analytics at sellpoints, the first online sales orchestrator, and is based in the San Francisco bay area.

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