Section 1 : Strategy Alignment

Section 2 : Data infra & management 

Customer segments are clearly defined using data and performance analysis

Segmentation is informed by some data, but decisions often rely on assumptions or intuition.

Budget allocation is based on data-driven performance and ROI analysis.

Some data is used, but allocation is often done by experience or intuition.

Budget allocation is inconsistent, with little reliance on data.

We track key metrics (e.g., CLTV, conversion rates, ROI) for each channel to optimize our acquisition strategy.

We track basic metrics, but don’t connect them to long-term customer value.

We don’t have a clear framework for measuring customer acquisition effectiveness.

We have personalized retention strategies, such as loyalty programs and targeted communications, based on customer data.

We use general retention strategies but don’t specifically prioritize high-value customers.

Retention efforts are inconsistent, with no targeted strategies for high-value customers.

We use predictive analytics and behavioral data (e.g., decreased engagement or reduced purchases) to identify at-risk high-value customers.

We rely on manual observation or general trends to spot potential churn.

We don’t have a system for identifying at-risk high-value customers.