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Restaurant Trend Analysis with Food Delivery Data

ArcTechnolabs analyzes restaurant trends in UAE and Singapore using pre-scraped food delivery data from Talabat, Deliveroo, Zomato, and GrabFood.

Table Of Contents

Introduction

Food delivery isn’t just about convenience anymore—it’s a data goldmine. In fast-paced markets like the UAE and Singapore, food delivery platforms serve as real-time mirrors of restaurant performance, cuisine trends, pricing models, and consumer preferences.

ArcTechnolabs brings powerful visibility into this ecosystem with ready-made datasets scraped from top platforms such as Talabat, Deliveroo, Zomato, Careem NOW (UAE), GrabFood, and Foodpanda (Singapore).

If you’re building a restaurant analytics platform, benchmarking food delivery pricing, or launching a virtual kitchen, our datasets deliver instant, structured, and geo-tagged intelligence.

Why UAE and Singapore?

UAE: Burgeoning QSR chains, cloud kitchen boom, and highly competitive platforms like Talabat and Zomato.
Singapore: Tech-savvy urban population, high delivery frequency, and GrabFood/Foodpanda dominance.

Both countries represent a gold standard for online ordering behavior and digital F&B operations.

What ArcTechnolabs Provides

ArcTechnolabs delivers structured, high-quality datasets extracted from leading food delivery platforms. These datasets include the following key attributes:

–Restaurant Name: The exact listing name as it appears on food delivery platforms. –Cuisine Type: Cuisine categories such as Chinese, Indian, Fast Food, Arabic, etc. –Item Names: Menu items with details including portion size. –Item Prices: Both original and discounted prices. –Delivery Fee: Platform-specific delivery charges. –Ratings: Average customer rating along with total review count. –Delivery Time Estimate: Estimated delivery time as shown on the platform (e.g., 30–40 minutes). –Offer/Discount: Promotional offers such as percentage discounts, coupons, and bundle deals. –Scraped From: Platforms including Zomato, GrabFood, Deliveroo, Talabat, Foodpanda, and others.

Sample Dataset – UAE (Talabat + Zomato)

Restaurant: Al Baik Express

Cuisine: Arabic

Item: Chicken Broast

Price: AED 25.00

Rating: 4.5

Estimated Delivery Time: 30–40 minutes

Restaurant: Burgerizzr

Cuisine: Fast Food

Item: Double Burger

Price: AED 32.00

Rating: 4.3

Estimated Delivery Time: 20–30 minutes

Sample Dataset – Singapore (GrabFood + Foodpanda)

Restaurant: Boon Tong Kee

Cuisine: Chinese

Item: Steamed Chicken

Price: SGD 12.80

Rating: 4.6

Estimated Delivery Time: 25–35 minutes

Restaurant: Crave Nasi Lemak

Cuisine: Malay

Item: Chicken Wing Set

Price: SGD 9.90

Rating: 4.4

Estimated Delivery Time: 20–25 minutes

Use Cases for Food Delivery Data

1. Restaurant Trend Forecasting

Track top-performing cuisines, trending dishes, and delivery frequency by city.

2. Competitor Pricing Analysis

Compare QSR pricing across cities/platforms to optimize your own.

3. Virtual Kitchen Strategy

Use delivery times, cuisine gaps, and demand signals to plan kitchen placement.

4. Franchise Expansion Feasibility

Measure brand performance before launching in new areas.

5. Offer Performance Tracking

Analyze how discount combos affect order ratings and visibility.

How ArcTechnolabs Builds These Datasets

Platform Selection: We target top food delivery apps across UAE and Singapore.
Geo-Based Filtering: Listings are segmented by city, area, and delivery radius.
Smart Scraping Engines: Handle pagination, time delays, JavaScript rendering.
Normalization: Menu names, price formatting, cuisine tagging, and duplication removal.
Delivery ETA Tracking: Extract exact delivery time estimates across dayparts.

Data Refresh Options

ArcTechnolabs offers flexible data refresh options to match your operational or analytical needs:

Hourly Updates

Channel: API or JSON feed

Format: Real-time data access

Daily Updates

Channel: Email delivery or direct download

Format: CSV or Excel

Weekly Trend Reports

Channel: Shared via email or Google Drive

Format: Summary reports with key insights

Target Cities ArcTechnolabs focuses on high-demand urban areas for precise, city-level analysis.

UAE:

Dubai

Abu Dhabi

Sharjah

Ajman

Al Ain

Singapore:

Central

Tampines

Jurong

Bukit Batok

Ang Mo Kio

Customization Options You can tailor your dataset to meet specific business goals or research parameters. Customization options include:

Cuisine Filter: Focus on select cuisines such as Indian, Arabic, or Chinese.

Platform Filter: Limit data to a specific platform like Talabat or GrabFood.

Time of Day: Filter listings by lunch, dinner, or early morning availability.

Restaurant Type: Choose data only from cloud kitchens or dine-in restaurants.

Discount Status: Include only restaurants currently offering deals or promotions.

Benefits of ArcTechnolabs’ Pre-Scraped Datasets

Fast deployment
City-wise trend segmentation
Competitor menu benchmarks
Multi-platform support
Clean & normalized structure

Get Started in 3 Steps

Request your sample dataset
Choose your region, platform & cuisine focus
Start receiving insights via API or scheduled exports

Visit ArcTechnolabs.com to request a demo or consultation.

Conclusion

The future of food delivery is data-driven. Whether you’re analyzing dish popularity, price competitiveness, or delivery performance— equips you with plug-and-play food delivery datasets that transform static restaurant listings into live market intelligence.

Get smart. Get fast. Get food trend insights—powered by ArcTechnolabs.

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