Restaurant Analytics: what to measure, how to measure it, what to do with it.
The metrics, dashboards and operating cadence GlobalRestaurantHub uses to turn restaurant data into weekly decisions on covers, marketing spend and operations.
Most restaurants in 2026 collect more data than they use. The POS, the reservation system, the online ordering platform, the website, the social accounts and the aggregators all produce reports. The successful restaurants are the ones who stop reading the reports and start running a single dashboard against a defined operating cadence.
This page covers the GlobalRestaurantHub restaurant analytics framework — the metrics we track, the dashboards we build, the cohorts we run, and the weekly meeting that ties data to action.
The minimum useful restaurant dashboard
Most restaurant dashboards either have too many metrics or measure the wrong ones. The minimum useful weekly dashboard contains 9 KPIs.
| Metric | Cadence | Healthy zone |
|---|---|---|
| Covers | Daily / weekly | Trend YoY |
| Average ticket | Weekly | +2–4% YoY |
| Repeat rate (90-day) | Weekly | 24–38% |
| Second-visit conversion | Monthly | >32% |
| Direct-order share | Weekly | >30% |
| CAC by channel | Monthly | Channel-dependent |
| LCP / Core Web Vitals | Weekly | <1.5s |
| Online review rolling 90d | Weekly | 4.5+ |
| AEO/GEO citation rate | Monthly | Trend |
Cohort analysis for restaurants
Cohort analysis groups diners by month of first visit and tracks retention curves. The shape of the curve tells you whether your CX is improving (curves flatten over time as service consistency improves) or eroding (curves steepen). It is the single most useful chart in restaurant analytics, and almost no restaurant tracks it.
RFM segmentation
RFM — Recency, Frequency, Monetary — is the standard segmentation framework for restaurant CRM. Diners are scored on how recent their last visit was, how frequently they visit and how much they spend. Marketing campaigns are tuned to each segment: 'champions' get loyalty perks, 'at risk' get win-back campaigns, 'new' get a structured second-visit nudge.
Marketing attribution that works
Marketing attribution is notoriously hard in restaurants because most diners do not click through — they remember a Reel and book later, or they hear about you in a podcast and search you directly. We use a blended model: deterministic where possible (UTM, CRM source field), and a media-mix model for the channels with no click trail (AEO/GEO, PR, brand campaigns).
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Contribution margin by dish
Most restaurants price menus on food cost percentage. The better approach is contribution margin — the absolute dollars each dish contributes after variable cost. A dish at 28% food cost making $14 contribution is better than one at 22% making $9. We run contribution-margin analysis quarterly to inform menu engineering.
The weekly analytics meeting
Analytics is useful only when it informs a decision. We anchor every client engagement with a weekly 60-minute analytics meeting — 9 KPIs reviewed, three decisions made, an action log. The cadence is the discipline.
Tools and stack
Tooling-wise: POS analytics (built into Toast / Square / Lightspeed), Google Analytics 4 for the website, Looker Studio or Metabase for the dashboard, and a CDP (Bikky / Punchh) or warehouse (Snowflake / BigQuery) for advanced cohort work. We pick the simplest stack that produces the dashboard above.
Grow Your Restaurant Business From Just $15/Day.
Everything needed to strengthen your digital presence and generate more customers.
Frequently asked questions
How much restaurant analytics is enough?
Which is the most important restaurant analytics metric?
Do we need a data warehouse to run restaurant analytics?
How do you attribute marketing to covers in a restaurant?
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