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Restaurant Ratings & Review Sentiment for
Food Delivery Leaders

FoodDataLab structures Restaurant Ratings & Review Sentiment across global delivery apps, Google Maps, and Tripadvisor. Account managers identify high-quality venue targets and monitor partner performance without manual tracking.

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Trusted by Fortune 500.

Get real-time data from all food platforms.

Without this data

Your team struggles to measure true venue quality at scale

Reliance on fragmented feedback leaves account managers reacting to churn instead of preventing it. Teams waste effort acquiring low-quality venues that ultimately damage user retention.

Strategic
Incomplete venue quality mapping
Platform executives rely on aggregate ratings rather than granular sentiment trends. This delays targeted interventions to improve the overall quality of available restaurants in key cities.
Operational
Manual data aggregation bottlenecks
Account managers spend dozens of hours copying feedback from Tripadvisor and Google Maps into spreadsheets. This repetitive extraction prevents them from actually consulting with restaurant partners.
Business
Reduced customer lifetime value
Acquiring poorly rated venues increases negative customer experiences on your platform. Diners who receive bad food switch to a rival app for their next meal.
Intelligence
Lagging partner performance reports
Data teams deliver static quality reports on a monthly or quarterly basis. Leadership lacks the daily pulse required to cull consistently underperforming partners before they impact platform GMV.
Sample signal

What a review sentiment record looks like

Each normalized profile provides immediate clarity into restaurant performance across platforms. Sales teams can evaluate average ratings, review volume, and sentiment shifts in seconds.

Venue Name Platform Source Store ID Avg Rating Total Reviews 30D Sentiment Last Sync
Dishoom Covent Garden Uber Eats LDN-COV-01 4.8 / 5 3,412 Trending Up today 09:14
Honest Burgers Soho Deliveroo LON-SOHO-84 4.6 / 5 1,894 Stable today 11:22
Franco Manca Brixton Just Eat UK-BRI-22 3.8 / 5 2,105 Declining yesterday
Padella Borough Market Google Maps GM-LON-09 4.7 / 5 4,510 Stable today 14:05
Goiko Grill Sol Glovo MAD-CEN-33 4.2 / 5 854 Monitoring 2 days ago
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What you get

Your team accesses normalized quality data instantly

FoodDataLab delivers structured feedback metrics directly into your existing reporting stack. We transform unstructured scores into clear, actionable signals for partner management.

12+
Tracked sources
Compare restaurant ratings across Glovo, DoorDash, and public review platforms.
47
Monitored areas
Track local sentiment shifts across major urban markets like London and Madrid.
<24h
Update velocity
Receive updated review counts and score changes daily to spot slipping quality.
98%
Match precision
Attain a verified match rate when linking venue names into a unified identity.

What food delivery providers want to understand with data

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FoodDataLab use cases across food delivery departments

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Why in-house food delivery data scraping costs more than you think

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How our data serves pricing and marketing teams worldwide

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Why comparing food delivery platform pricing is so hard?

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Business impact

Turn partner quality into a competitive advantage

Drive higher order frequency by curating a superior restaurant selection. Armed with normalized ratings, your platform can acquire top-tier venues and weed out poor performers.

Capture top local venues
Identify highly rated independent restaurants before competing platforms notice them. Your sales team can secure exclusive partnerships with the best local operators.
Protect customer retention
Flag deteriorating restaurant scores instantly to pause low-quality venues. Preventing bad food experiences directly preserves diner loyalty and protects platform GMV.
Win major chain contracts
Approach large enterprise brands with detailed data on their franchise locations. You can leverage these quality insights to negotiate better commission fee structures.
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How it works

From raw feedback to actionable insights in three steps

FoodDataLab processes fragmented quality metrics into a single source of truth. We handle the heavy lifting of collection and normalization so your teams can focus on account management.

1

Extract

Our infrastructure captures public ratings from Uber Eats, Delivery Hero, Google Maps, and Tripadvisor. We gather this data continuously without relying on any internal login credentials.
2

Normalize

We match slightly varied restaurant names across sources into one definitive profile. This ensures a venue listed differently on Just Eat and DoorDash is tracked accurately as a single entity.
3

Deliver

Clean sentiment data flows directly into your choice of Metabase, Tableau, or Power BI. Account managers access refreshed scores alongside their regular CRM activities via scheduled exports or REST API.
FAQ

Questions we get from food delivery leaders

Straight answers about coverage, integration, and data reliability.

Start tracking venue quality with precision

Request a sample dataset covering ratings in your most competitive market. An intelligence analyst will verify your requirements and provide a tailored export within two business days.

  • A dedicated data expert assigned to your case
  • No obligation, free consultation
  • Full support from scoping to delivery

Need an NDA first? Just mention it in the form - we're happy to sign.

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