At CourtAvenue, we use a KPI framework that aims to simplify format, provide a balance of metrics, and allow for scalability across channels and experiences. All while introducing the customer journey into the mix.

The core portion of the KPI framework includes three basic layers to act as balance. Performing well for one of these layers is nice, two is good, and three is considered great. The exact metrics chosen for each layer may differ based on channel, but the concept of balance remains the same.

For experiences, such as a brand website, we select Satisfaction, Volume, and Movement as the three layers. This combination keeps the customer front-and-center by measuring their satisfaction in their own words and ratings, understanding if these customers represent meaningful volume to the business, and finally, if these customers are being moved across their shopper journey as a sign of meeting their needs and delivering business value. For example, moving a consumer from a Shopping phase to Selection.

For media, such as a retail media campaign, we select Effectiveness, Efficiency, and Volume to achieve our three layer balance. This combination helps measure if a campaign’s combination of channel, targeting, and creative is able to effectively achieve its purpose, while an efficiency metric such as Return on Ad Spend determines if this is being achieved profitably. The Volume metric determines the importance and ability to scale a budget up or down based on its effectiveness and efficiency performance.

This three-layer approach is then repeated across a shopper journey for which a channel serves. This offers the ability to see where customers and/or media spend is focused, including possible differences in satisfaction and performance based on existing experiences. Alignment of metrics to the journey can occur based on where a consumer is engaging with an experience or by directly asking where each respondent considers themselves in the journey.

While we never include metrics such as bounce rate within the core section of our KPI framework, more traditional diagnostic metrics may be used within a support layer where analysts can dig deeper into the causes of movement within the metrics. Based on findings, these metrics may be elevated on an ad-hoc basis into a conversational delivery of findings and leading to testing and optimization. Outcomes from these optimizations – including good or bad – and industry recognition may also be elevated alongside the framework as moments of proof, or mini case studies that help visualize and document improvements and learnings.