Real-Time Food-Delivery Data Extraction Across Southeast Asia — A 500-Outlet, 88-City Case Study

Introduction

Southeast Asia’s food-delivery market is expanding rapidly, powered by hyperlocal demand and platforms like GrabFood, Foodpanda, ShopeeFood, and GoFood. For restaurants, cloud kitchens, and F&B enterprises, understanding pricing, ETAs, availability, and competitor behavior across multiple apps and cities has become a mission-critical challenge.

A global F&B enterprise approached Actowiz Solutions to centralize, automate, and scale food-delivery data extraction across:

• 500+ outlets
• 88+ cities
• 5 major food apps
• PIN-code-level granularity

This case study details the problem, architecture, insights, and business impact.

Food Delivery Apps Across Southeast Asia

Client Challenges

The client struggled with fragmented and inconsistent data across SEA markets.

1. No unified visibility across 5 major food apps

Each platform showed different:

• Prices
• Delivery fees
• ETAs
• Discounts
• Menu structures

2. No hyperlocal intelligence

Urban centers like Bangkok, Manila, Jakarta, and Kuala Lumpur require PIN-code-specific extraction due to:

• Zone-based pricing
• Distance-based delivery
• Micro-regional SKUs
• Varying ETAs

3. 88 cities = 88 different market behaviors

Manual tracking was impossible.

4. Frequent app UI & API changes

Platforms constantly updated:

• APIs
• Layouts
• Anti-bot protections

5. No competitor benchmarking

The client couldn’t track:

• Bestseller ranking
• Promo alignment
• Category-level pricing shifts

Fragmented Marketplace Listings / Menu Differences

Project Scope Delivered by Actowiz Solutions

Actowiz designed a high-scale, multi-country extraction system covering:

• 500+ outlets
• 88 cities
• 5 major apps (GrabFood, Foodpanda, ShopeeFood, GoFood, Deliveroo/per region)
• PIN-code-level targeting
• Real-time + scheduled crawls
• Competitor benchmarking

The extraction covered:

• Menu Items: Variants, descriptions, add-ons, combos, allergens.
• Pricing Intelligence: Base, surge, promo price, platform deals.
• Delivery Intelligence: Distance-based fees, ETA by slot, zone surge.
• Stock & Availability: Bestsellers, out-of-stock tracking.
• Ranking & Visibility: Category placement, sponsored positions.

Menu, ETA, Pricing Screens from SEA Apps

The Actowiz Architecture Behind the Scenes

To handle a multi-country, multi-city, multi-app ecosystem, Actowiz deployed:

1. Distributed Crawlers for High-Volume Outlets

Supports:

• Parallel extraction
• Resilient retries
• Multi-threaded crawling

2. Geo-Targeted SEA Proxy Network

Location-accurate results across:

• Indonesia
• Thailand
• Malaysia
• Vietnam
• Philippines
• Singapore

3. App-Specific Logic & Parsing

Each platform has unique complexity:

• GrabFood → Distance-based dynamic fees
• Foodpanda → Time-slot ETA model
• ShopeeFood → Layered discount engine
• GoFood → Availability-by-region logic

4. Anti-Bot Adaptive Framework

Handles:

• CAPTCHA
• Device fingerprinting
• Token refresh cycles

5. Real-Time Dashboard (Client View)

Shows:

• Price changes
• ETA surges
• Competitor movements
• Availability status
• City-wise insights

Data Pipeline / Extraction Architecture Visualization

Key Insights Generated

After implementing the extraction system, the client gained several high-impact insights across SEA.

1. Price Variation Up to 38% Across Cities

The same SKU priced differently in:

• Manila vs Cebu
• Jakarta vs Medan
• Bangkok vs Chiang Mai

Hyperlocal taxation + marketplace logic caused differences.

2. Delivery Fees Changed Every 15–30 Minutes

Data showed:

• Weather-based surges
• Distance-based fee jumps
• Rider unavailability spikes

3. Promo Wars in Tier-2 Cities

ShopeeFood & GoFood ran deeper discounts outside capital cities.

4. Bestseller Lists Varied by Geography

Example:Vietnam preferred iced beverages; Indonesia preferred spicy mains; Singapore purchased premium SKUs.

5. Ranking Dropped Sharply When ETA Increased

A 6–10 minute ETA rise caused:

• Lower category ranking
• Decline in order conversions
• Loss of visibility vs competitors

Bestseller Rankings, ETA Impact, Price Trend Charts

Business Impact Delivered

Actowiz delivered clear operational and revenue benefits:

1. 22% improvement in promotional ROI

Promos aligned with competitor discount timing increased conversion.

2. 18–26% reduction in ETA-related ranking drops

Hyperlocal visibility helped optimize staffing and delivery zones.

3. 14% increase in marketplace visibility

Through menu hygiene, price optimization, and data-backed decisions.

4. Real-time alerts enabled faster decisions

Instant notifications for:

• Stock-outs
• Price drops
• Competitor promotions
• Ranking loss

5. Unified intelligence across 88 cities

Removed manual dependency on outlet managers.

Executive Dashboard / Regional Performance Map

Conclusion: Data Extraction at SEA Scale Requires Precision + Infrastructure

Managing 500 outlets across 88 cities and multiple food apps is extremely complex. Actowiz Solutions delivered:

• Real-time extraction
• App-level intelligence
• City-level precision
• PIN-level accuracy
• High-volume automation
• Multi-country benchmarking

Today, the client uses Actowiz intelligence to run pricing, promotions, expansion, supply chain, and competitive strategy across Southeast Asia.

In markets where food-delivery is evolving daily, data isn’t support — it’s survival.