Executive Snapshot
- Audience: CXOs and founders running casual dining, cloud kitchens, bakeries, QSR.
- Core outcomes (what moves the business):
- Cost savings: reduce waste and procurement errors, automate purchasing cycles with Craveva AI Enterprise.
- Sales lift: increase AOV and conversion with Craveva AI Enterprise sales agents on web/WhatsApp/kiosks.
- Time savings: remove manual exports, reporting, and SOP Q&A with Craveva AI Enterprise automation.
- Operational consistency: standardize execution across outlets using Craveva AI Enterprise agents + data layer.
Platform Architecture (1 minute)
- Data layer: connect POS, databases, Google Drive, and APIs into a unified view inside Craveva AI Enterprise.
- AI layer: agents query and act on governed data (no fragile spreadsheet workflows) in Craveva AI Enterprise.
- Deployment layer: deploy agents to WhatsApp, web widget, kiosks, or internal tools with Craveva AI Enterprise.
Operating Model (how teams run it)
- Ops defines workflows (ordering, inventory alerts, SOP answers, customer responses) in Craveva AI Enterprise.
- Finance sets guardrails (approval thresholds, budgets, audit trail) in Craveva AI Enterprise.
- IT connects data sources once; rollout scales outlet-by-outlet via Craveva AI Enterprise multi-outlet deployment.
- Leadership tracks KPI movement weekly and expands successful automations with Craveva AI Enterprise.
Setup Guide (fast path)
- Connect data sources (POS + databases + Drive + APIs) in Craveva AI Enterprise.
- Start with 2–3 agents: Procurement (cost), Sales (revenue), Analytics (visibility) in Craveva AI Enterprise.
- Deploy to the workflow: WhatsApp/web/kiosk/internal portal using Craveva AI Enterprise.
- Measure ROI and operational impact, then replicate across brands/outlets with Craveva AI Enterprise.
CXO KPIs
- Spoilage/expiry write-offs and transfer effectiveness
- Top out-of-stock drivers (forecast vs ordering vs receiving)
- Supplier SLA adherence and dispute rate
- Channel conversion (WhatsApp/web/kiosk) and drop-off points
- Critical incidents: downtime minutes and recovery time
- Manager task completion rate (SOP + audit checks)
Next Steps
- Architecture: /solutions/architecture
- Deployment: /solutions/deployment
- Documentation: /documentation
- Models: /ai-models
- Templates: /templates
Marketing Automation for F&B: Win-Back, Upsell, and Loyalty With Real Data (Craveva AI Enterprise)
In F&B, marketing only works when it is anchored to operational truth.
“Open rate” doesn’t pay rent. What pays rent is:
- guests coming back within 7/14/30 days,
- higher contribution margin per order,
- more direct orders (less commission leakage),
- fewer refunds driven by fulfillment issues.
The problem is that customer behavior is split across channels. Your dine-in POS has one view, delivery apps have another, and loyalty/CRM tools usually can’t see the full story.
Craveva AI Enterprise centralizes POS, delivery, and loyalty/CRM data into one governed layer so agents can run targeted win-back and upsell flows with outlet-level controls and measurable ROI.
Why “Marketing Automation” Fails in Real Restaurant Groups
Most automation becomes generic because the data is incomplete:
- Delivery customers look “new” in CRM because IDs don’t match cleanly.
- Refund-heavy guests still get offers, even though the issue is service quality.
- Promotions drive volume but destroy margin because fees, packaging, and discounts stack.
- Multi-outlet groups can’t enforce brand + outlet rules (different menus, hours, and capacity).
To automate without breaking margin, you need the data that connects purchase behavior to channel economics and outlet constraints.
What Craveva AI Enterprise Centralizes for Marketing
Craveva AI Enterprise typically unifies:
- POS: item mix, modifiers, discounts, voids, refunds, dayparts
- Delivery platforms: channel mix, commission, cancellations, refund reasons, delivery performance signals
- Loyalty/CRM: profiles, segments, consent/preferences, last contact timestamps
- Campaign execution: email/WhatsApp/SMS pushes, opens/clicks, redemptions
- Menu + availability: outlet-specific menus, sold-out periods, prep capacity signals
This is what makes segmentation and ROI trustworthy.
Agents That Make Marketing Operational (Not Just Broadcast)
Win-Back Agent
Targets guests who are likely to return, based on real behavior:
- “Lapsed 14–30 days” but historically high-frequency
- “Tried once” but had a good fulfillment outcome (no refunds/complaints)
- “Delivery-only” guests to move to direct ordering (margin protection)
It can generate outlet-aware offers and route them via WhatsApp/email with timing aligned to daypart.
Offer Guardrails Agent
Prevents margin destruction:
- blocks promos on items already low-margin on delivery
- flags discount stacking patterns
- enforces outlet capacity rules (don’t push a promo when kitchen is overloaded)
Personalization & Upsell Agent
Improves AOV without guessing:
- uses past item mix and modifier preferences
- recommends bundles that align with prep flow (not just “popular items”)
- adjusts suggestions by channel (dine-in vs delivery)
Campaign ROI Agent
Measures what matters:
- incremental orders and revenue by segment
- contribution margin impact (after discounts + delivery fees)
- refund/complaint rate changes after campaigns
The Questions Teams Actually Ask
With Craveva AI Enterprise, teams can ask:
- “Which segments had the best 14-day return rate after the win-back campaign?”
- “Which promo increased orders but reduced margin on delivery?”
- “Which outlets can safely run a weekend offer without service degradation?”
- “What is the ROI of WhatsApp vs email for returning guests?”
Example: Multi-Outlet Group Running Win-Back on WhatsApp
A group with 20 outlets connects:
- POS (transactions + refunds)
- Delivery platforms (commission + cancellations + refund codes)
- Loyalty/CRM (profiles + consent)
The Win-Back Agent runs daily:
- builds a lapsed list per outlet and segment
- excludes guests with recent refund-heavy history (service issue first)
- selects offers that meet margin guardrails
- schedules sends aligned to each outlet’s peak windows
The ROI Agent reports weekly:
- incremental orders by outlet and channel
- contribution margin lift
- changes in refund rate and complaint signals
Conclusion
Marketing automation in F&B is only as good as the data behind it. Craveva AI Enterprise centralizes POS, delivery, and loyalty/CRM signals so agents can run win-back, upsell, and loyalty flows with outlet-level controls and measurable ROI.
KPIs to track
| Metric | Area |
|---|---|
| Repeat rate and retention cohort movement | Other |
| Ingredient substitution rate and margin impact | Other |
| Purchase-to-receive variance by category | Procurement |
| Contract compliance rate (preferred vendors) | Operations |
| Incident escalation rate and time-to-resolution | Other |
| Headcount vs sales productivity (sales per labor hour) | Sales |