The challenge
Peet's had an existing Peetnik app and loyalty program, but app data alone could not show how opting into loyalty related to real visit behavior.
Dormant members were a blind spot. Peet's could not see how dormant app users behaved or what re-engaging them was worth.
The solution
1. Guest WiFi: Detect customer visits on premise
Guest WiFi detected customer visits in Peet's stores. Customer Data turned those visits into profiles.
The profiles became on-premise data to fuel marketing and grow the loyalty CRM.
2. POS matchback: Tie member visits to spend
Peet's integrated its POS with its loyalty partner. That tied each member's visits to what they spent, matched to POS data.
3. Foot Traffic Analytics: Compare three groups on verified visits
Audience Segmentation split guests into active members, dormant members, and non-members.
Foot Traffic Analytics measured each group against verified in-store visits rather than app activity. The result is a comparison, not proof that joining loyalty caused additional visits.
The results
- 5x/month active member visits, versus 3x for dormant members and 2.6x for non-members
- 2x active member revenue, versus non-members
- 1.67x revenue from active members versus dormant members