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Café Olé logoCafé OléHOSPITALITY

A hospitality group with 12 locations, one growth loop.

We connected POS, reservations and marketing into a single customer view and shipped a lifecycle program that lifted repeat visits by 31%.

Barista preparing coffee behind a specialty coffee bar under warm pendant lights
MODELHospitality group
LOCATIONS12
PRIMARY CHANNELWhatsApp + email
TEAM1 marketing manager
THE QUESTION

Can a multi-site hospitality group behave like a single brand to the guest, without replacing the systems each location already runs on?

+31%REPEAT VISITS
92%RESERVATION → VISIT
71%WHATSAPP OPT-IN
SERVICES
  • Data audit
  • Stack buildout
  • Growth ops
STACK
  • POS
  • PMS
  • WhatsApp Business
  • BigQuery

The problem

Twelve locations, four systems, and no single customer view. Marketing decisions were made on gut, not data. A guest who visited three sites in a month looked like three different people.

The constraint we worked inside

Replacing the POS was off the table: each location had operational reasons for its setup and the group had no appetite for a migration. So the work was to build a guest layer above the systems rather than consolidate the systems themselves.

What we built

  • Unified guest profile across locations, keyed on phone number.
  • Post-visit lifecycle on WhatsApp and email, with content driven by what was actually ordered.
  • Reservation reminders wired to POS behaviour, which cut no-shows.
  • A per-location weekly report that general managers read without asking marketing.

The result

Repeat visits rose 31% on matched cohorts and reservation-to-visit conversion reached 92%. WhatsApp became the highest-consent channel in the group at 71% opt-in, well above the email baseline.

HOW IT RAN, 5 MONTHS
  1. PHASE 1Diagnose

    Mapped four source systems across 12 sites. Established which identifier could actually join a guest across POS and reservations.

  2. PHASE 2Unify

    BigQuery guest profile, nightly ingestion from POS and PMS, deduplication on phone as primary key.

  3. PHASE 3Activate

    Post-visit lifecycle on WhatsApp and email, reservation reminders wired to actual POS behaviour, location-aware content.

  4. PHASE 4Operate

    Experiment cadence with the marketing manager, per-location reporting handed to general managers.

HOW WE MEASURED THIS

Repeat visit lift measured on matched guest cohorts in BigQuery, comparing 90 days pre-launch with 90 days post-launch across the same 12 locations. No-show rate from the reservation system. Client-approved.

Read our evidence standard

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