Built around the
everyday stop.
Frequency, basket, store, occasion and time of day. Convenience retail lives on short visits; the question is what brings people back at the right moment.
Unlike general retail, convenience is decided in minutes: a coffee on the way, lunch near the office, essentials at night. The store and the daypart matter as much as the customer.
- Visit frequency
- Basket size and composition
- Store and location
- Occasion, promotion and daypart
Questions you can ask
- Which promotions increased basket size?
- What products are often purchased together?
- Which customers are losing purchase frequency?
- What offer should we activate around lunch?
Data that becomes useful
- Tickets and products
- Time and store
- Promotions
- Identified customer, when it exists
Most physical purchases are anonymous. Frequency by customer applies only to loyalty-linked tickets; the rest is read by store and daypart.
Prepare the lunch offer for this audience.
RadianHere is the channel plan, the creative mapped to each channel and the test design. Review the audience and timing before activation.
Output Operational summary — Ready for review
What the agents can do
01 / UnderstandNexusAnalyze baskets and frequency by store, occasion and time of day.
02 / DefineAuraBuild the eligible audience for a daypart, with contact permission.
03 / CreatePrismWrite an offer and creative that fit the moment.
04 / ActivateRadianPrepare a contact plan by zone and occasion, ready for review.
- 05 / LearnShared system
Review basket, frequency, margin and redemption within a defined scope.
↺ Returns to Understand
How learning closes the loop
Each offer is read against a comparable period or group, with its scope stated: which stores, which hours, which customers. What is learned feeds the next daypart decision.
What is measured- Basket size
- Visit frequency
- Margin
- Redemption
Qualitative hypotheses for three missions.
Start with the moment of the visit.
Explore how a basket and a time of day shape the next invitation.