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Marketing ROI Modeling

Customer Retention Intelligence System

We built a retention intelligence system for Shopify brands to identify where customer value was being created, lost, and recovered.

It analyzed post-purchase behavior (repeat-purchase likelihood, churn risk, lifetime value, and segment-level opportunity) to separate high-value customers, at-risk customers, and those most likely to respond to retention campaigns.

Marketing ROIRetentionShopify

The challenge

Most businesses spend heavily to acquire customers but lack a clear system for knowing which are likely to return, which are slipping away, and which segments deserve the most attention.

We connected retention analytics to execution by identifying segments that could be synced straight into email and SMS tools for targeted follow-up.

What it modeled

  • Repeat purchase behavior
  • Churn risk
  • Customer lifetime value
  • Customer segmentation
  • Retention opportunity
  • Post-purchase marketing potential
  • Email and SMS audience targeting
  • Revenue tied to customer behavior

Why it matters

Marketing ROI is determined by whether a customer buys again, stays engaged, and grows in value over time. Modeling behavior after purchase lets brands stop treating retention as a guessing game and start making data-backed decisions.

Core insight

The most profitable customer is not always the newest one.

In many businesses, the highest-value opportunity is hidden inside the customer base they already paid to acquire.

Have a decision worth modeling?

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