Menu Pricing Data Scraping Case Study — Tracking Restaurant Menu Inflation Across 6 Markets 2024–2026
How a global FMCG ingredient supplier used menu pricing data scraping and AI-assisted dish matching to track 12.4% average menu inflation across 6 markets and 180K+ items over 24 months.
Client overview
Who the client is
The client is a global FMCG ingredient supplier selling to restaurant chains across multiple regions. With local inflation rates diverging sharply post-2023, the supplier needed reliable menu pricing data intelligence to understand how restaurants in each market were passing through cost pressures — and to recalibrate its own pricing strategy market by market. Names are anonymized for confidentiality; metrics are shown exactly as delivered.
Objectives
What they wanted to achieve
- Track restaurant menu inflation across 6 priority markets
- Quantify per-category and per-cuisine inflation rates
- Identify which restaurant categories absorbed costs vs. passed through
- Build a defensible inflation panel from merchant-level evidence
- Recalibrate the supplier's pricing strategy by market
- Establish ongoing monthly inflation monitoring
The challenge
Macro inflation data does not equal menu inflation
National CPI data tells you what the broad economy is doing. It does not tell you whether restaurants in São Paulo are passing through 8% of food costs or 18%, whether Indian QSR chains are holding prices to defend share, or whether Dubai casual-dining is absorbing or recovering ingredient inflation. Without merchant-level menu price data, the supplier could not make market-specific pricing decisions defensibly.
The solution
A 6-market 24-month menu pricing tracker
FoodDataScrape built a continuous menu pricing data scraping pipeline across the US, UK, UAE, India, SEA, and Brazil — capturing 180,000+ menu items in local currency with month-by-month price evolution. The build went live in seven weeks.
Define dish equivalents
We built a cross-market dish-equivalent taxonomy so menu items were comparable across countries (a 'beef burger combo' in the US matches its UAE equivalent).
Multi-market extractors
Per-country extractors captured menu prices in local currency from dominant delivery platforms in each market.
Time-series backfill
Historical pricing was reconstructed back to 2024 so the inflation curve was visible from day one.
The AI layer
How does AI-assisted inflation tracking work?
AI-assisted inflation tracking combines food delivery data scraping with classification models that match equivalent dishes across countries and currencies — producing a defensible cross-market inflation panel from merchant-level price data.
On top of the raw feed, an AI dish-matching layer turned price data into menu inflation intelligence: it normalized dish equivalents across markets, computed category-level inflation rates per country, and surfaced where restaurants were absorbing versus passing through ingredient cost increases. Each month the supplier received refreshed inflation dashboards.
- Classified 180,000+ menu items into cross-market dish equivalents
- Identified 12.4% average menu inflation across 6 markets over 24 months
- Surfaced Brazil and Turkey QSR as highest pass-through markets
- Flagged India and Indonesia QSR as lowest pass-through (margin absorption)
Data captured
What data we captured
The pipeline captured a full menu pricing data intelligence view across 6 markets:
| source | method | fields |
|---|---|---|
| Multi-market | Menu pricing data scraping | 180K menu items · local + USD |
| Time-series | Historical reconstruction | 24 months of monthly prices |
| AI dish-match | Cross-market equivalents | comparable inflation rates |
BEFORE VS AFTER
Before vs after comparison
| Metric | Before | After (FoodDataScrape) |
|---|---|---|
| Inflation visibility | National CPI only | Restaurant-category-specific inflation |
| Cross-market comparability | Currency-mixed reports | USD-normalized dish equivalents |
| Time-series depth | Annual benchmarks | 24-month monthly panel |
| Pass-through analysis | Anecdotal | Per-category, per-country quantified |
| Pricing strategy | Global template | Market-specific recalibration |
| Refresh cadence | Annual repricing review | Monthly inflation dashboard |
ROI impact
From Assumption to Measurable ROI
Measured across 6 markets and 180K menu items over 24 months.
Comprehensive cross-market dish-equivalent panel.
US, UK, UAE, India, SEA, Brazil — all on a single panel.
From 2024 baseline through 2026 with monthly resolution.
The supplier recalibrated its global pricing into 4 market-specific tiers based on pass-through behavior — protecting margin in high-absorption markets and capturing more value in high-pass-through markets.
Client testimonial
In the client's words
"National CPI tells you almost nothing about menu inflation. We needed restaurant-category-specific, market-specific, dish-level inflation data — and that is exactly what the pipeline produced."
— Global Pricing Director, FMCG ingredient supplier (name withheld)
Why FoodDataScrape
Why they chose FoodDataScrape
- Specialists in menu pricing data scraping across multiple markets
- Coverage of dominant delivery platforms per country
- AI-assisted cross-market dish-equivalent matching
- 24-month historical backfill in every market
- Compliance-aware sourcing and dedicated regional analyst support
- Live in seven weeks with a free proof-of-concept first
Questions
Frequently asked questions
It combines food delivery data scraping with AI classification that matches equivalent dishes across countries, currencies, and platforms — producing comparable inflation panels from merchant-level price data.
A cross-market dish-equivalent taxonomy maps locally-named dishes (e.g., 'cheeseburger combo' in the US and its UAE equivalent) so that inflation rates are computed on truly comparable items.
United States, United Kingdom, UAE, India, Southeast Asia (Singapore + Indonesia), and Brazil — each with monthly price tracking back to 2024.
A defensible 4-tier global pricing recalibration, protected margin in high-absorption markets, and more value captured in high-pass-through markets.
Yes — the same cross-market price-tracking pipeline can monitor grocery, FMCG, beverage, and any category with merchant-level pricing visibility.
Yes — we use compliance-aware sourcing across all markets and delivery platforms.
Need cross-market menu inflation data for your pricing?
Tell us your target markets and dish categories. We'll scope a pricing-tracking pipeline and show sample output in a short demo.
