In the first part of this series, I talked about how we ingested nearly a decade of raw business data into a structured intelligence layer.
But structured data is just a spreadsheet until you ask it the right questions.
We applied Recency, Frequency, and Monetary (RFM) scoring to segment the entire customer base. This is where the AI stopped being a filing cabinet and started being a strategist.
The Breakdown
The RFM segmentation revealed the actual health and structure of the customer base. We broke it down into clear groups:
- Champions: High value, recent, frequent buyers.
- Loyals: Consistent buyers.
- New Customers: First-time, recent buyers.
- Potentials: Moderate engagement.
- At Risk: Have not purchased recently.
- Lost: Long inactive.
The Insight That Changed Everything
When the AI finished the segmentation, the numbers told a story we had been missing.
We discovered that a massive percentage of our customers were one-time buyers. While our Champions and Loyals carry the business, the “At Risk” customers represented the highest-leverage opportunity for revenue recovery.
We had been marketing to everyone equally. The AI showed us exactly who to talk to, and what to say. This insight immediately directed our next marketing plays.
But to execute those plays autonomously, we needed a secure place for the AI to work. That is what we built next.
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Stay curious, my AI friend. It's the secret sauce - think like you are seven. - Ryan