How to Scrape Singapore Food Delivery Data for Offer & Fee Benchmarking?

Introduction

Singapore's food delivery market has rapidly evolved into a highly competitive digital battleground. With platforms like GrabFood, FoodPanda, and Deliveroo dominating the scene, restaurants and cloud kitchens are under constant pressure to stay visible, offer competitive pricing, and adapt to dynamic customer preferences. In 2025, Singapore’s online food delivery industry is projected to exceed SGD 3.4 billion, driven by convenience, app-based loyalty programs, and increased demand for quick commerce options.

Delivery fees, promotional campaigns, and exclusive deals have emerged as key factors influencing consumer choices. According to recent insights, 64% of Singaporean customers in 2025 choose a food delivery platform based on delivery cost and discounts offered. That’s why relying on guesswork or manual checks is no longer sustainable.

To maintain a competitive edge, restaurants must harness the power of Singapore food delivery data through structured, scalable solutions like food delivery app scraping. By tapping into real-time data—such as competitor pricing, trending offers, and fluctuating delivery fees—businesses can make informed decisions on promotions, menu pricing, and platform prioritization. Whether it's a Food Panda Menu Data Scrape or delivery fee benchmarking across GrabFood, data scraping unlocks the visibility and intelligence brands need to thrive in this fast-paced ecosystem.

Why Offer & Fee Benchmarking Matters in Singapore’s Food Delivery Market?

In Singapore’s saturated food delivery ecosystem, standing out requires more than just good food—it demands intelligent pricing, strategic promotions, and deep visibility into delivery fees. With platforms like Grab, FoodPanda, and Deliveroo constantly tweaking their algorithms and incentives, restaurant owners must benchmark offers and fees to stay ahead. Ignoring these shifting patterns means missing out on customer attention, losing platform rankings, and ultimately, sacrificing revenue.

The Impact of Delivery Fees on Consumer Choice

Delivery fees can significantly influence a customer's purchasing decision. In Singapore, where many users compare platforms before placing an order, even a minor difference in delivery charges can sway preferences.

Restaurants that fail to monitor or benchmark fees across apps risk being undercut by competitors who offer lower or subsidized delivery costs. With food delivery data intelligence services, businesses can track average delivery charges by region, time, or order size and adjust accordingly.

Importance of Promotions in Platform Visibility

Promotions—whether platform-wide or brand-specific—boost visibility and customer engagement. Grab’s “Free Delivery Wednesdays” or FoodPanda’s “Daily Deals” often determine which outlets get featured more prominently on app homepages.

By using restaurant data scraping services, brands can extract promotional insights like coupon patterns, combo pricing, and app-exclusive deals from competitor listings. These insights help in aligning their own strategies, whether it’s launching a new promo or bundling items for higher cart value.

Competitive Pricing and Ranking Implications

In the algorithmic world of food delivery platforms, price competitiveness plays a major role in app rankings. If your burger combo is $1 more expensive than a similar offering in the same locality, you may lose position—and sales.

Benchmarking allows businesses to match or beat competitor pricing, a tactic made possible through food delivery data intelligence services that analyze not only item prices but also fees, taxes, and packaging charges.

Extending Beyond Food – Grocery & Multi-Vertical Benchmarking

The need for benchmarking is not exclusive to restaurants. With the rise of Q-commerce, grocery sellers also face pricing and delivery challenges. Using grocery delivery data scraping, retailers can track charges across platforms and maintain competitive basket values, ensuring customers stay loyal.

By integrating cross-category benchmarks, businesses can ensure their pricing stays in line not just with direct competitors but with substitutes in the broader delivery market.

Actowiz Makes It Easy with Automated Benchmarking

Manual monitoring is inefficient and inaccurate. Actowiz Solutions enables clients to automate data collection using restaurant data scraping services and food delivery data intelligence services. From delivery fee mapping to promotional insights and grocery delivery data scraping, Actowiz empowers businesses to make fast, informed decisions with real-time benchmarks.

In conclusion, offer and fee benchmarking isn't optional—it's essential for survival and success in Singapore's ultra-competitive food delivery landscape.

Key Data Points to Extract from Food Delivery Apps

In the highly competitive food delivery ecosystem, gaining real-time visibility into what’s happening on platforms like Grab, FoodPanda, and Deliveroo is essential for strategic decision-making. To build effective pricing models, plan promotions, or benchmark competitors, businesses must extract and analyze key data points from these apps. Below are the most valuable data points to scrape, each offering powerful insights into how brands can refine their digital strategies and optimize their visibility.

Item Price Variations

One of the most critical elements to monitor is item price variation across platforms and locations. Food delivery platforms often allow restaurants to adjust pricing based on location-specific demand or delivery radius. For example, the same burger combo might cost SGD 8.90 in central Singapore but SGD 9.50 in suburban areas due to delivery zone pricing.

Tracking these variations helps identify pricing inconsistencies, evaluate competitors' strategies, and adjust pricing dynamically. Scraping item prices at regular intervals reveals trends like seasonal pricing or changes during peak hours. It also helps in identifying which platforms offer more competitive pricing for specific dishes, enabling smarter cross-platform pricing decisions.

Delivery Charges by Location/Time

Delivery fees are a major component of the total order cost and significantly influence buyer decisions. These charges fluctuate based on time of day, delivery zone, traffic patterns, and weather conditions. For instance, delivery during lunch peak hours in CBD areas may include surge fees, while late-night orders in residential areas may offer free or discounted delivery.

Scraping and analyzing delivery charges by location and time enables restaurants to evaluate whether their pricing structure remains competitive. It also provides insights into how platforms use delivery fee strategies to shape customer behavior. This intelligence allows businesses to offer timed promotions, optimize their delivery range, or shift marketing efforts to periods with lower charges.

Promo Code Types and Frequency

Promotional offers are a critical driver of user acquisition and retention. Platforms frequently offer promo codes like “15% OFF FIRST ORDER,” “BUY 1 GET 1 FREE,” or “$5 OFF ON WEEKENDS.” Scraping promo code details—including type, value, expiration, and eligibility—allows businesses to stay in sync with market trends.

By tracking promo code frequency and type across platforms, restaurants can develop their own competitive offers or match existing promotions to maintain visibility. Understanding which types of deals work best on each platform also supports better ROI on marketing spend.

Platform-Specific Deals (e.g., “Free Delivery Fridays”)

Each food delivery platform often runs its own exclusive campaigns. For example, FoodPanda may promote “50% off selected merchants every Friday,” while Grab might run “Free Delivery Wednesdays.” These platform-specific deals have a direct impact on which restaurants get featured on top searches or banners.

Extracting this data enables restaurants to align their participation with relevant campaigns, increasing chances of being highlighted during high-traffic days. It also helps businesses time their internal offers to complement broader platform-driven promotions, maximizing exposure and conversion rates.

Menu Visibility and Ranking

Finally, scraping data related to menu visibility and ranking is crucial. Food delivery platforms use complex algorithms to rank restaurant listings based on pricing, delivery speed, customer ratings, and promotional activity. Monitoring where a restaurant appears in search results—especially for category-specific searches like “sushi near me” or “best burgers”—can reveal performance gaps.

Businesses can use this data to identify when rankings drop and correlate it with pricing changes, missing promotions, or poor reviews. Regular visibility tracking helps optimize digital menus, adjust promo schedules, and stay competitive across all platforms.

Extracting these key data points from food delivery apps gives brands a decisive edge in a crowded market. Through actionable insights on pricing, delivery, promotions, and visibility, businesses can improve their offerings and drive sustainable growth.

How to Scrape Singapore Food Delivery Data Effectively?

As Singapore’s food delivery market becomes more competitive, real-time access to pricing, promotions, and delivery fee data has become essential for restaurants, cloud kitchens, and Q-commerce brands. With multiple platforms offering varied pricing structures and promotional tactics, manually tracking this information is inefficient and inaccurate. To stay ahead, businesses need to automate the process of scraping Singapore food delivery data effectively—and Actowiz Solutions offers just the right tools to help.

Here’s an overview of the most effective approach to scraping data from top food delivery apps in Singapore, such as Grab, FoodPanda, and Deliveroo.

Selecting Target Platforms: Grab, FoodPanda & Deliveroo

The first step in scraping food delivery data is identifying the most relevant platforms based on your market presence and target audience. In Singapore, Grab, FoodPanda, and Deliveroo are the dominant players, covering a wide user base across various income groups, cuisines, and service models. For Q-commerce and cloud kitchen brands, these platforms offer deep data reservoirs—from menus and pricing to delivery timings and ratings.

Actowiz Solutions customizes scraping strategies depending on your priority—whether it's menu price extraction, delivery fee comparison, or offer benchmarking analysis across these leading apps.

Using Custom Crawlers or APIs

Once platforms are selected, the next step is to implement data extraction using either custom-built web crawlers or available APIs. Web crawlers are tailored to extract structured data from app interfaces and websites, capturing information like:

• Menu item prices and categories
• Delivery charges based on time and location
• Active promotions, coupons, and platform-exclusive deals
• Estimated delivery times and surge pricing instances

When APIs are available, they offer more stability and consistent access to app-level data without reliance on web interface structures.

Actowiz Solutions builds powerful custom crawlers that can adapt quickly to UI/UX changes, ensuring uninterrupted quick commerce data scraping services. Our crawlers also extract data from both mobile apps and web versions for a complete market picture.

Scheduling and Frequency of Data Pulls

Scraping food delivery data is not a one-time process—it requires frequent updates to capture changes in real-time pricing and promotions. Depending on your operational needs, data can be pulled:

• Hourly: To track flash sales, surge pricing, or campaign windows
• Daily: For standard offer and pricing updates
• Weekly: For trend analysis and planning

Actowiz automates these schedules so you receive structured datasets at your preferred frequency. These timely updates enable accurate offer benchmarking analysis and support faster pricing decisions across platforms.

Ensuring Compliance with Local Data Norms

With increasing global attention on data privacy and scraping ethics, ensuring legal compliance is critical. In Singapore, scraping must be done without violating platform terms of service or collecting personal user data. All data extraction by Actowiz Solutions adheres to PDPA (Personal Data Protection Act) standards.

We ensure that our menu price extraction and delivery fee comparison processes are aligned with regulatory best practices—focusing solely on publicly available commercial information.

How Actowiz Solutions Helps Automate and Scale the Process?

Actowiz Solutions simplifies and scales the data scraping process with:

• Pre-configured scripts for Grab, FoodPanda, and Deliveroo
• Scalable infrastructure to manage high-frequency data pulls
• Real-time dashboards for comparative analytics
• API access for seamless integration with BI tools
• Structured outputs in JSON, CSV, or custom formats

Whether your goal is offer benchmarking analysis, delivery fee comparison, or monitoring competitors' pricing in real time, Actowiz’s quick commerce data scraping services give you full control over strategic decision-making. With 24/7 support, automated workflows, and compliance-focused practices, Actowiz helps Singapore-based F&B businesses turn scraped data into lasting competitive advantage.

Use Cases - How Brands Are Using This Data

With the food delivery landscape in Singapore becoming increasingly saturated, access to Singapore food delivery data has become a game-changer for modern food businesses. From quick service restaurant (QSR) chains to agile cloud kitchens and even independent eateries, brands are using food delivery app scraping to fuel smarter decisions and gain a competitive edge. Whether it's optimizing pricing, launching localized promotions, or decoding app ranking algorithms, data extracted from platforms like Grab, Deliveroo, and Food Panda Menu Data Scrape is now a core driver of success.

Let’s explore how various food businesses are utilizing this data across strategic areas.

Use Case 1: Adjusting Delivery Pricing Strategies for Higher Conversions

A leading QSR chain in Singapore found that higher delivery fees during evening peak hours were causing significant cart abandonment. By analyzing Singapore food delivery data, including real-time delivery charges across Grab and FoodPanda, the chain noticed that competitor restaurants in similar zones were either subsidizing fees or offering discounts.

Using this insight, the brand restructured its delivery pricing by offering flat-rate fees during high-traffic periods and bundling delivery discounts with combo meals. This change led to a 23% increase in completed orders over four weeks.

Use Case 2: Launching Geo-Targeted Promotions for Local Impact

A fast-growing cloud kitchen brand utilized Food Panda Menu Data Scrape to identify areas with a high frequency of discount-led purchases. By comparing menu prices, promotions, and coupon types across various postal codes, they identified underserved regions with fewer competitive offers.

They launched geo-targeted deals—like “Free Delivery in Punggol on Weekends” and “$2 Off in Bishan After 9 PM”—that aligned with user behavior in those locations. The result? A 35% uptick in order volume from the newly targeted zones and increased platform visibility due to better conversion metrics.

Use Case 3: Improving Rankings on Food Delivery Apps

App ranking is heavily influenced by factors like price competitiveness, estimated delivery time, and active promotions. One independent restaurant struggling with low visibility used food delivery app scraping to monitor top-ranking competitors.

The scraped data revealed that rivals offering limited-time promotions and keeping prices within a specific range were consistently appearing in top results. In response, the restaurant adjusted its pricing model, added platform-specific meal deals, and introduced a daily limited-time offer.

Within two weeks, their ranking improved from the fifth page to the second on Deliveroo under the "Healthy Bowls" category, leading to a 40% increase in visibility and a 20% jump in orders.

Use Case 4: Identifying Competitor Weak Spots and Gaps

Another savvy use of Singapore food delivery data comes in the form of competitor benchmarking. A multi-outlet fusion cuisine brand used data scraping to identify weak spots in competitors’ offerings—such as missing menu items during lunch hours, inconsistent delivery times, or higher prices in certain locations.

By filling in those gaps—extending operating hours, reducing prices in targeted zones, and offering meal combos at optimized price points—they were able to penetrate competitor strongholds and grow their market share by 18% in one quarter.

From strategic pricing to hyper-targeted marketing, food businesses across Singapore are transforming how they operate by leveraging scraped data. With solutions like Food Panda Menu Data Scrape and full-scale food delivery app scraping, Actowiz Solutions empowers brands to unlock data-backed opportunities that fuel visibility, conversion, and long-term growth.

How Actowiz Solutions Can Help?

In Singapore’s hyper-competitive food delivery space, real-time access to reliable data can be the difference between standing out or getting buried in search results. Actowiz Solutions provides a full suite of advanced tools and services for Scraping Singapore Food Delivery Data, helping F&B brands make faster, smarter, and more profitable decisions.

Our expertise in restaurant data scraping services allows brands to extract critical insights from top delivery platforms like Grab, FoodPanda, and Deliveroo. Whether you’re looking to benchmark offers, track fees, or monitor competitor pricing, Actowiz delivers high-quality structured data that powers intelligent decisions.

One of our key offerings is real-time data feeds. These allow restaurants and cloud kitchens to monitor live menu updates, promotions, and delivery fee changes, ensuring you're never out of sync with the market. We also provide cross-platform comparison dashboards that let users evaluate performance metrics like item pricing, promo frequency, and ranking visibility across all major delivery apps in Singapore. This enables side-by-side comparisons that uncover both competitive advantages and gaps.

Actowiz further simplifies decision-making with custom report generation, allowing you to access actionable data visualizations and analytics tailored to your business goals. Whether it's a daily summary of price changes or a weekly report on promo effectiveness, our tools are designed to align with how your team operates.

We are also trusted providers of food delivery data intelligence services, helping restaurant brands analyze consumer behavior, spot pricing trends, and fine-tune menu offerings. From delivery fee tracking to offer benchmarking, we ensure that your business is equipped with the most accurate and timely data available in the industry.

Actowiz’s robust support extends to promotional insights, where we track platform-specific deals and coupon behavior to help you launch impactful, data-backed campaigns. We also have deep capabilities in grocery delivery data scraping, enabling supermarkets and convenience stores to track product pricing, availability, and delivery surcharges in real time.

With end-to-end implementation, from crawler setup to integration with your existing BI tools, Actowiz Solutions offers seamless and scalable data delivery. Our experienced team provides full onboarding, maintenance, and compliance support—so you can focus on what matters most: optimizing your pricing, promotions, and presence across Singapore’s top food delivery platforms.

With Actowiz by your side, you get more than just data—you get a competitive edge.

Conclusion

Reiterate the importance of using scraped data for smarter decision-making in a crowded delivery app ecosystem. Encourage businesses to stay competitive with Actowiz’s reliable, scalable, and customizable Singapore food delivery data scraping services. Ready to beat your competition with offer & fee intelligence? Contact Actowiz Solutions today to start scraping smarter! You can also reach us for all your mobile app scraping, data collection, web scraping , and instant data scraper service requirements!