Strategy

Understanding Comparison Shopping Performance Metrics

 

Once your Comparison Shopping Engine campaigns are up and running, you'll quickly want to start evaluating your results. It is important not only to regularly measure your performance, but also to understand how the different metrics relate to each other as well as what options you have to improve your campaign performance.

Prerequisites


The following topics should be reviewed before completing this task

Performance Metrics


 

Many retailers measure their online marketing campaigns through performance metrics such as return on ad spend (ROAS: defined as revenue divided by marketing cost) or Effective Revenue Share (ERS: defined as marketing cost divided by revenue. ERS is also referred to as CAPS or E:A ratio). These efficiency measurements are important to understanding the effectiveness of the campaigns and driving future decisions on changes that may need to be made.

The key to understanding success on comparison shopping engines is to break down the definition of these components into their parts, understand how those subcomponents interact with one another, and then identify steps that can be taken to influence those sub components.

The image below shows ERS (which is the inverse of ROAS) broken down into primary metrics.

ERS Equation
As you can see, traffic level (clicks) is a component of both sides of this ratio. This means that the remaining three elements relate to each other the same way regardless the traffic volume of the campaign. Because CSEs have relatively flat pricing, meaning the cost for every click is generally the same for any one product or category, the average CPC is not expected to fluctuate much but rather to stay generally flat. It can fluctuate if you change your bid levels regularly, or if your products cover a wide range of categories with very different CPC rates. If the latter is the case, then the average CPC is not expected to change much within a single category so this assumption of flat CPC will still apply within one category or even a group of categories with similar CPC rates.

The average order value of a merchant's business can fluctuate as well, but over time it usually does not fluctuate much unless again, the range of categories is vast, or something is done to encourage users to adjust their order values, such as promotions. Because these two metrics are likely to remain relatively flat, the conversion rate becomes a very important metric to watch. One can use conversion rate as a proxy for overall account efficiency, unless fluctuations in the average CPC or average order value are expected.


 
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