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// Case Studies · Real Numbers · Real Brands

Food Data Scraping — Real Outcomes, Real Numbers

Real client outcomes with real numbers — UAE QSR chain +18% margin, US grocery -60% stock-outs, UK delivery 6hr→90s reaction, India CPG 18K+ pin codes covered, Gulf Halal 100% compliance, PE diligence saving $60M valuation. All anonymized but unmodified.

// 6 Real Outcomes

Real numbers from real food brands.

Every case study below uses real client metrics. Names anonymized for confidentiality. ROI, scale and timeline shown exactly as delivered.

London Restaurant Data Scraping Case Study — Why London Independents Charge 18.9% More

Client: The client is a UK casual-dining chain
Challenge: London independents felt expensive — but by how much?
Solution: A 3,400-restaurant London independent vs chain tracker
3,400
London restaurants tracked
18.9%
Independent premium
Zone 1-3
London coverage
12mo
Time-series depth

India Multi-Platform Restaurant Data Scraping Case Study — Zomato vs Swiggy 3.8% Price Gap

Client: The client is a national Indian food brand
Challenge: Same dish, two platforms, two prices — no strategy
Solution: A 12-metro Indian cross-platform price tracker
22,400
Matched pairs
3.8%
Avg same-dish gap
12
India metros covered
24mo
Time-series depth

India Tier-2 Restaurant Data Scraping Case Study — Beyond Mumbai-Delhi to Lucknow + Jaipur

Client: The client is a national Indian QSR chain
Challenge: Tier-2 cities are not 'small metros'
Solution: A 14-city tier-2 evaluation panel
14
Tier-2 evaluated
Lucknow + Jaipur
2 prioritized
28
Outlets sequenced
₹95cr
Expansion guided

Dubai Cloud Kitchen Data Scraping Case Study — Why Some Virtual Brands Profit and Others Burn

Client: The client is a Dubai-focused private equity firm
Challenge: Cloud kitchen pitches look identical — outcomes do not
Solution: A 36-month Dubai virtual brand decoder
380
Virtual brands tracked
36mo
Time-series depth
8
ROI patterns decoded
$24M
Investment guided

Bengaluru Cloud Kitchen Data Scraping Case Study — India's Cloud Kitchen Capital Mapped

Client: The client is an India-focused cloud kitchen investor
Challenge: Bengaluru's cloud kitchen ecosystem is opaque from the outside
Solution: A 480-virtual-brand Bengaluru ecosystem decoder
480
Virtual brands mapped
5
Operator archetypes
24mo
Time-series depth
₹85cr
Investment guided

Australia Restaurant Franchise Data Scraping Case Study — QSR Whitespace Across Outer Sydney + Melbourne

Client: The client is an Australian QSR franchise operator
Challenge: Sydney + Melbourne are 240 suburbs, not 2 cities
Solution: A 240-suburb Australian whitespace tracker
240
Suburbs evaluated
38
Whitespace launches
2
Sydney + Melbourne
18mo
Time-series depth
// Could Be Your Outcome Next

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