$300M in system sales. Less than 15% of guests identified.
A national fast casual chain had made the right technology investments — Bikky for customer analytics, Thanx for loyalty execution, Olo for digital ordering. But the platforms weren’t connected. Bikky held order data. Thanx held loyalty data. Olo held digital transaction data. Nobody had built the layer that unified them into a single guest view.
The result: the brand was identifying fewer than 15% of its actual guests. The vast majority of transactions were anonymous. The marketing team had no way to distinguish their highest-value guests from one-time visitors, no way to identify who was at risk of churning, and no way to know which segments held the most untapped revenue potential.
The growth plateau: Promotions, LTOs, and loyalty spend were all executing — but growth had stalled. The data existed. What was missing was the orchestration layer that connected it to decisions.
Data foundation first. AI-powered CLV segmentation second. 60 days total.
Foundation (30 days): Rower audited all core systems — Olo, Aloha, Thanx, Punchh, Attentive, R365, Tattle — for guest, order, and loyalty data. Every field was mapped to Bikky’s schema. Guest IDs and menu items were normalized across platforms. Data was migrated into Bikky with CCPA/GDPR compliance confirmed and full data lineage documented. Validation target: Bikky generating 5+ actionable segments with 90%+ match rate to the Thanx loyalty base.
Insight (30 days): With the unified data foundation in place, Rower applied AI/ML to create CLV performance audiences — segmenting the entire guest database into top-value, mid-tier, at-risk, and lapsed cohorts. Each segment was profiled with quantified revenue potential per tier, recommended investment levels, channel mix, and offer strategy. The output was a strategic playbook securing executive alignment on budget allocation and campaign priorities for the next 12 months.
From anonymous transactions to a $25–30M revenue map.
- Guest identification rate increased from under 15% to over 90% — giving the marketing team a complete view of their customer base for the first time
- $25–30M revenue opportunity identified from a 10% improvement in visit frequency and spend among the top-tier loyal guest segment
- Four distinct CLV audience tiers built — enabling targeted investment decisions rather than broadcast spending across the full database
- Strategic playbook delivered with quantified revenue potential per segment, channel mix recommendations, and offer strategy
- Bikky validated at 90%+ match rate to the Thanx loyalty base — confirming the unified data model was ready for campaign activation
Starting point: ~$300–325M system sales across ~250–275 units. Thanx and Bikky already purchased. Growth plateaued despite executing promotions, LTOs, and loyalty spend — because the data wasn’t connected to execution.
Three friction points identified: loyalty insights not connected to offers (CLV), no scalable sign-up mechanism (enrollment), and no way to distinguish true incremental lift from margin cannibalization (LTO).
Three quantified levers: (1) Loyal guest spend — $25–30M from 10% visit/spend lift. (2) Loyalty sign-up automation — $10–20M from 5–10% enrollment rate lift. (3) LTO optimization — $2.5–5M from 5–10% performance improvement.
KR1 (Foundation, 30 days): Data audit across Olo, Aloha, Thanx, Punchh, Attentive, R365, Tattle. Schema mapping, ID normalization, CCPA/GDPR governance, Bikky validation at 90%+ match rate. KR2 (Insight, 30 days): CLV benchmarking, AI/ML segmentation modeling, strategic playbook with revenue per tier.
