Guest Retention & Offer Targeting
Losing a regular guest rarely happens all at once. It shows up first as a slightly longer gap between visits, easy to miss without looking at the data, until that gap turns into a guest who's stopped coming in altogether. By the time it's obvious, a blanket discount sent to the entire guest list is a blunt, expensive way to try to win them back, and it rewards guests who never stopped visiting in the first place.
Strela analyzes guest purchase history to identify at-risk customers and recommend targeted offers that bring them back.
Service Areas
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Purchase history segmentation by recency and frequency. Guests get segmented based on how recently and how often they've visited, surfacing patterns a single glance at the guest list won't show.
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At-risk and lapsed guest identification. Guests whose visit pattern is slipping, or who've stopped visiting entirely, get identified before they're gone for good.
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Targeted offer design by segment. Offers get built around each specific segment's behavior, rather than one generic discount sent to everyone.
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Timing recommendations for outreach. Offers go out at the point they're most likely to bring a guest back, not on a fixed schedule disconnected from actual behavior.
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Post-offer performance tracking. Results get tracked after each offer goes out, so what works can be repeated and what doesn't, can be adjusted.
The Outcome
At-risk guests get identified and re-engaged before they're gone for good, with offers targeted enough to bring them back without discounting guests who never stopped visiting. Retention becomes something the business actively manages, not something it only notices after the numbers have already dropped.