Singapore Restaurant Data Scraping Case Study — Restaurant Re-Allocation Across Singapore After Platform Exit
How a SEA food delivery platform used real-time foodpanda data scraping and AI-assisted migration tracking to capture +18% share during the 90-day foodpanda Singapore withdrawal window.
Client overview
Who the client is
The client is a SEA food delivery platform competitor operating in Singapore. When foodpanda announced its Singapore withdrawal, the platform's growth team identified a one-time opportunity to capture significant share — but only if they could move faster than competing platforms on merchant onboarding. They needed Singapore restaurant data intelligence to identify and prioritize re-allocation targets. Names are anonymized for confidentiality; metrics are shown exactly as delivered.
Objectives
What they wanted to achieve
- Track restaurant re-allocation from foodpanda to remaining platforms
- Identify high-value restaurants moving to GrabFood vs. Deliveroo vs. exiting delivery
- Quantify the 90-day migration window
- Prioritize merchant outreach for the client's own platform
- Capture share faster than competing platforms via data-led targeting
- Build ongoing platform-shift monitoring for future events
The challenge
A 90-day window to capture share — and no targeting data
foodpanda's Singapore withdrawal announcement created a narrow window — roughly 90 days — when 8,400+ restaurants would re-allocate to alternative platforms or exit delivery entirely. The first platform to identify and onboard high-value re-allocators would capture disproportionate share. Without merchant-level migration tracking, the client's growth team would be onboarding random restaurants instead of the most valuable ones.
The solution
A real-time platform-shift migration tracker
FoodDataScrape built a continuous foodpanda data scraping pipeline (during wind-down) plus GrabFood Singapore data and Deliveroo coverage to track restaurant re-allocations in real time, with daily migration alerts and high-value-target prioritization. The build went live in three weeks.
Snapshot pre-exit
We captured the full foodpanda Singapore restaurant footprint before the withdrawal completed.
Track daily migrations
Per-platform extractors detected restaurants newly appearing on GrabFood or Deliveroo during the wind-down.
Score & prioritize
Each re-allocator was scored for value (review velocity, category, average order) and routed to the client's outreach team.
The AI layer
How does AI-assisted platform-shift tracking work?
AI-assisted platform-shift tracking combines food delivery data scraping with merchant-matching models that detect when restaurants migrate between platforms — surfacing high-value migration targets in near-real time during platform transitions.
On top of the raw feed, an AI matching layer turned platform data into migration intelligence: it matched foodpanda-departing restaurants to their new-platform appearances, scored each migrator's value, prioritized outreach targets, and surfaced restaurants exiting delivery entirely. The client's growth team received daily prioritized target lists.
- Tracked 8,400 restaurant re-allocations over the 90-day window
- Identified 1,200 high-value re-allocators prioritized for outreach
- Surfaced 640 restaurants exiting delivery entirely
- Flagged 320 restaurants going GrabFood-exclusive (lost-cause for the client)
Data captured
What data we captured
The pipeline captured a full Singapore restaurant data intelligence migration view:
| source | method | fields |
|---|---|---|
| foodpanda (wind-down) | foodpanda data scraping | pre-exit restaurant snapshot |
| GrabFood SG | GrabFood Singapore data scraping | post-exit appearances |
| Deliveroo | Deliveroo data extraction | post-exit appearances |
BEFORE VS AFTER
Before vs after comparison
| Metric | Before | After (FoodDataScrape) |
|---|---|---|
| Migration visibility | Industry rumor | 8,400 movements tracked daily |
| Outreach targeting | Random merchant lists | Value-scored prioritized targets |
| Window response time | Reactive scrambling | Same-day target identification |
| Exit visibility | Unknown post-event | 640 delivery exits flagged |
| Share capture outcome | Baseline | +18% share gained |
| Refresh cadence | Weekly market reports | Daily migration alerts |
ROI impact
From Assumption to Measurable ROI
Singapore market share gained during the 90-day migration window.
Restaurant re-allocations across all post-exit platforms.
Prioritized outreach list driven by value scoring.
Pipeline deployed fast enough to capture the full migration window.
The data-led targeting let the client outpace competing platforms during the 90-day migration window — capturing 18 percentage points of share that would otherwise have gone to undifferentiated outreach.
Client testimonial
In the client's words
"When foodpanda announced the Singapore exit, every competitor knew the share was up for grabs. The data showed us which restaurants we actually wanted — and which to leave to the competition."
— Head of Merchant Growth, SEA food delivery platform (name withheld)
Why FoodDataScrape
Why they chose FoodDataScrape
- Specialists in Singapore food delivery data scraping
- foodpanda, GrabFood Singapore & Deliveroo coverage
- AI-assisted cross-platform merchant migration matching
- Daily migration alerts during platform transitions
- Compliance-aware sourcing and dedicated SEA analyst support
- Live in three weeks with a free proof-of-concept first
Questions
Frequently asked questions
It combines pre-exit data capture from the exiting platform with continuous monitoring of competing platforms — matching the same merchant across platforms to detect when re-allocation has occurred.
Each migrating restaurant is scored on value signals (review velocity, cuisine category, average order proxies, location quality) to produce a prioritized outreach list aligned to the client's commercial goals.
foodpanda (during wind-down), GrabFood Singapore, and Deliveroo — covering the full Singapore food delivery ecosystem during the migration window.
An 18 percentage point share gain during the 90-day migration window, 1,200 high-value targets identified for outreach, and a continuing migration-monitoring pipeline.
Yes — the same migration-tracking pipeline can be deployed for any platform consolidation, withdrawal, or merger event in any covered market.
Yes — we use compliance-aware sourcing across all SEA markets and delivery platforms.
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