AI Assistant (Leat MCP)
July 20
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Program analytics
Know whether the program is working, not just how many people joined. Track growth against activity, earning against redemption, and how members move through every mechanic. Because every metric drills down to the customer behind it, a number that looks wrong is a few clicks from the reason why.
New members, by month, source, and location. Active members, defined the way your business defines active, whether that's a purchase this quarter or a visit this month. Members who went quiet and members who came back. Growth read against activity shows whether the program is adding customers who participate or a list that's getting longer, and the signup source shows which QR codes, campaigns, and stores are bringing in the ones who stay.
Points earned against points redeemed, and the rate between them. Time from earning to redemption. Balances sitting unused and how long they've sat. Stamp cards completed against stamp cards abandoned, and where in the card members stop. Points liability and how it moved this period. Earning without redemption is a program members aren't using; redemption without earning is one they're draining. The two read together say which.
How members are distributed across tiers and how they move between them. Membership signups and renewals. Referrals shared, completed, and rewarded. Challenges taken up and finished. Vouchers issued against vouchers used. Each mechanic reports its own health, so a program running five mechanics can see which three members actually engage with and which two exist on paper.
Every metric drills down: from the program to a location, from a location to a segment, from a segment to the members in it and what each of them did. A redemption rate that dropped this quarter becomes the stores where it dropped, the segment it dropped in, and the customers who stopped. Trends run over any period you choose, and what a user can see follows the scope of their role. When a number needs explaining, the explanation is a few clicks below it, and the deeper questions hand off to retention and cohort analysis, customer lifetime value, and incrementality measurement.
Program integrity
Keep stamps, points, and rewards worth what they're meant to be worth
Tier progression management
Move customers through tiers on complete spend rather than what one system saw
Lapsed customer recovery
Spot fading visit patterns across locations before a customer quietly stops coming back
Program change management
Change a rule once and have every campaign, channel, and decision honor it
Multi-location consistency
Run shared rules across sites, brands, and markets with local variation where it's needed
