A multi-platform, venue-level time series of the delivery economy: every restaurant on the major apps, every day — presence, ratings, review volume and churn, joined by a stable cross-platform merchant identity.
Consumer-transaction datasets measure demand. We measure the supply side — the asset base the platforms monetize: how many restaurants are listed where, how they're performing, and when they leave.
Each merchant is matched across platforms into a canonical ID — chain-safe, city-aware. See the same restaurant on Wolt, Uber Eats and Just Eat at once, and watch it move between them.
Per venue × platform × day:
Aggregates ship too: market-level counts, new listings, and a daily verified merchant-churn metric.
Merchant-base counts per market are a leading indicator for platform revenue — visible in days, not quarters.
Two very different events, one honest split: full closure (left the market) vs platform switch (moved to another app). Every candidate is re-probed live before it counts.
Rating drift and review velocity per venue — plus detection of new openings from unrated-venue state, months before they appear in any registry.
Which merchants run on one app and which run on several — with 14,000+ cross-platform matches already resolved. Platform overlap and share shifts become measurable.
A daily origination screen over the entire restaurant universe: operators worth approaching now — healthy enough to buy, weak enough to want the conversation.
Merchants with sustained demand momentum loss — review velocity declining vs. their own baseline and vs. a healthy market — plus rating drift and thinning platform presence. Filtered for independence, recent activity, and confirmed still operating.
Build a ranked universe of struggling-but-alive restaurant and SMB businesses, refreshed daily. Approach founders with current, verified store-level facts — not a directory scrape.
Origination pipelines months ahead of brokers. Chain & brand footprint views for buy-and-build programs. Proof-of-life verification before any call is made.
This is a demand-momentum screen, not a bankruptcy oracle. Distress leads 6–18 months — we flag the decline curve and verify the merchant is trading now; your diligence layers the rest.
Independent operators preferred, chains filtered out. Each candidate carries its current rating trajectory and review volume — the conversation opener is specific, not generic.
The same lens works after close: track how acquired stores perform, market by market, against every comparable in the network.
Your book's restaurant and food-SMB names rarely file anything useful before they fail. Their delivery footprint is a live, public operating proxy that updates every day.
Per-counterparty monitoring at portfolio scale: review velocity stalling, rating drift, venues going dark or leaving platforms, cross-platform presence shrinking — compared against the market baseline.
Watch the whole book on one dashboard. Adjust limits, pricing and intervention on evidence — not on lagged financial filings or payment patterns that arrive too late.
Early warning measured in months, not days. A defensible, dated evidence trail for limit decisions and, when needed, claims.
Every observation is timestamped. Reconstruct exactly what a merchant's network looked like on any date — your side of any dispute is documented from day one.
Canonical merchant IDs mean one counterparty, one profile — even when it trades on two, three or four apps at once.
400+ markets across 30+ countries, EU-deep. If your insureds trade on food-delivery apps, they're in the dataset.
For coverage of Uber, DoorDash, Just Eat Takeaway, Delivery Hero, Deliveroo, Wolt — the merchant network is the asset base those valuations rest on. We make it observable daily.
Merchant-base growth and churn per platform × market; new listings; multi-homing shifts — the supply-side momentum that precedes order and GMV trends.
Model platform growth ahead of quarterly disclosures. Read per-market share movement from cross-platform churn: a merchant leaving app A for app B is market share you can see now.
Daily, market-level, point-in-time supply data — the dimension your demand-side order/GMV feeds simply don't cover. 6 listed platforms exposed, one subscription.
Type A closures are a macro/liquidity gauge; Type B switches are a competitive tell. Reported separately, live-verified — never a single ambiguous number.
Counts, growth, churn and average rating per platform per market, aligned to the exact geography your models already use.
Aggregate-only, public sources, no PII — a dataset your compliance desk clears, not fights.
Live health checks on restaurant borrowers between financial statements — covenant-relevant signal for banks and alternative lenders.
Per-location performance vs. every comparable in the network; franchisee health and brand-standard compliance at a glance.
Where your products are available on delivery apps — and where competitors' are. Distribution and shelf analysis at chain + market level.
F&B tenant health and delivery density as a location-quality proxy for portfolios, leasing and development decisions.
Structured screening universes over thousands of operators, with current performance context for valuation and process design.
Restaurant-sector entry, exit and churn as regional consumption and small-business-health indicators.
Native collectors per platform read public discovery surfaces across 1,000+ probe points — cities, postcodes, grids — in scheduled daily sweeps.
Schema-on-write into a warehouse; ratings normalized to 0–5 with raw scales preserved; cuisine, chain and brand enrichment applied.
Venues are matched across platforms into a stable, chain-safe merchant ID — the layer that turns five app views into one restaurant.
Churn candidates are re-probed live — absence must be confirmed twice before it counts. T+1 delivery as CSV, Parquet or API.
Capture floors per platform, watchdogged refresh windows, self-healing re-fires and anomaly guards run every day. Absence ≠ churn is a solved problem, not a caveat — that verification loop is the difference between a signal and a noise generator.
Your team is exactly the one we'd expect to build it. That is precisely why we want you to see the full picture before you do. This is not a capability question — it's a cost and timing question.
| Cadence | Daily snapshots, T+1 · history accruing since June 2026 |
| Coverage | 6 platforms · 400+ markets · 30+ countries · ~250k venues/day |
| Identity layer | 14,000+ merchants matched across two or more platforms |
| Metrics | Merchant counts, new listings, verified churn (A/B split), ratings, review volume |
| Delivery | CSV / Parquet / JSON — bulk or per-market · API on request |
| Compliance | Aggregate-only · public sources · no PII · no review text · GDPR-clean |
A real slice of venue snapshots and a daily series — see the grain, the ratings, the identity layer before any commitment.
Bring your universe — a portfolio, a market set, a watchlist. We verify what's in the data, honestly, before you license anything.
Run your use case against the live feed for a defined period. If the signal isn't there, we don't expect a renewal.