The Measurable AI UberEats E-Receipt Dataset is a leading source of email receipts and transaction data, offering data collected directly from users via Proprietary Consumer Apps, with millions of opt-in users.

We source our email receipt consumer data panel via two consumer apps which garner the express consent of our end-users (GDPR compliant). We then aggregate and anonymize all the transactional data to produce raw and aggregate datasets for our clients.

Use Cases Our clients leverage our datasets to produce actionable consumer insights such as: - Market share analysis - User behavioral traits (e.g. retention rates) - Average order values - Promotional strategies used by the key players. Several of our clients also use our datasets for forecasting and understanding industry trends better.

Coverage - Asia (Taiwan, Japan, Australia) - Americas (United States, Mexico, Chile) - EMEA (United Kingdom, France, Italy, United Arab Emirates, AE, South Africa)

Granular Data Itemized, high-definition data per transaction level with metrics such as - Order value - Items ordered - No. of orders per user - Delivery fee - Service fee - Promotions used - Geolocation data and more

Aggregate Data - Weekly/ monthly order volume - Revenue delivered in aggregate form, with historical data dating back to 2018. All the transactional e-receipts are sent from the UberEats food delivery app to users’ registered accounts.

Most of our clients are fast-growing Tech Companies, Financial Institutions, Buyside Firms, Market Research Agencies, Consultancies and Academia.

Our dataset is GDPR compliant, contains no PII information and is aggregated & anonymized with user consent. Contact business@measurable.ai for a data dictionary and to find out our volume in each country.

The Measurable AI FoodPanda Food & Grocery Transaction dataset is a leading source of email receipts and transaction data, offering data collected directly from users via Proprietary Consumer Apps, with millions of opt-in users.

We source our email receipt consumer data panel via two consumer apps which garner the express consent of our end-users (GDPR compliant). We then aggregate and anonymize all the transactional data to produce raw and aggregate datasets for our clients.

Use Cases Our clients leverage our datasets to produce actionable consumer insights such as: - Market share analysis - User behavioral traits (e.g. retention rates) - Average order values - Promotional strategies used by the key players. Several of our clients also use our datasets for forecasting and understanding industry trends better.

Coverage - Asia (Hong Kong, Taiwan, Singapore, Thailand, Malaysia, Philippines, Pakistan)

Granular Data Itemized, high-definition data per transaction level with metrics such as - Order value - Items ordered - No. of orders per user - Delivery fee - Service fee - Promotions used - Geolocation data and more

Aggregate Data - Weekly/ monthly order volume - Revenue delivered in aggregate form, with historical data dating back to 2018. All the transactional e-receipts are sent from the FoodPanda food delivery app to users’ registered accounts.

Most of our clients are fast-growing Tech Companies, Financial Institutions, Buyside Firms, Market Research Agencies, Consultancies and Academia.

Our dataset is GDPR compliant, contains no PII information and is aggregated & anonymized with user consent. Contact business@measurable.ai for a data dictionary and to find out our volume in each country.

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India Food Delivery Market Size and Trends

The India food delivery market size is forecast to increase by USD 1.01 billion at a CAGR of 34% between 2024 and 2028. The food delivery market is experiencing significant growth, driven by the increasing cravings for diverse and popular dishes among consumers. Restaurants are recognizing the importance of delivering high-quality food and quick delivery times to meet customer queries. AI search features and AI-generated content are becoming increasingly popular, allowing customers to easily find their favorite dishes and receive personalized recipe suggestions through platforms like Recipe Rover. However, the market is also facing challenges, including the growing threat from direct delivery services and the need for efficient food preparation and customer support to maintain customer satisfaction. These trends and challenges highlight the importance of collaboration and partnerships between food delivery services and restaurants to meet the evolving demands of consumers.

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The food delivery market is witnessing a significant shift as technology continues to revolutionize the way we order and receive our meals. Quick commerce platforms, powered by AI-integrations, are leading this transformation by offering personalized product recommendations, streamlined user experiences, and efficient food delivery services. Generative AI plays a pivotal role in enhancing the functionality of these platforms. This advanced technology analyzes user data, including past orders, cravings, and preferences, to generate tailored recipe suggestions and meal planning ideas. AI-generated content, such as personalized food assistant widgets, engage users and offer real-time assistance in their food choices.

Moreover, the integration of AI-powered tools in food delivery platforms not only improves user experience but also addresses the challenges faced by startups in the industry. High costs and intense competition make it essential for businesses to optimize their operations and offer value-added services to customers. AI integrations help streamline food preparation, manage delivery time efficiently, and provide excellent customer support through AI search features and automated responses to common queries. However, the adoption of AI in the food delivery market is not without its challenges. Data privacy concerns are a significant hurdle, as the collection and analysis of user data are essential for AI-driven recommendations and services. Ensuring transparency and security in data handling is crucial for maintaining user trust and adhering to regulations. Moreover, the success of AI food assistants relies on the accuracy and relevance of the data they process. The density of restaurants and the availability of popular dishes in a given area are essential factors in generating accurate recommendations.

Additionally, AI-generated recipes must consider macro-nutrients and ingredient availability to ensure meal planning is feasible and healthy. Midjourney, a leading quick commerce platform, is addressing these challenges by focusing on the development of an AI-driven food assistant that caters to users' unique needs and preferences. By continuously learning from user interactions and feedback, this AI food assistant offers personalized recipe suggestions, meal planning ideas, and ingredient recommendations. It also integrates with popular food delivery services to ensure a seamless ordering and delivery experience. In conclusion, the integration of generative AI and quick commerce platforms is transforming the food delivery market by offering personalized recommendations, streamlined user experiences, and efficient services. While challenges such as data privacy concerns and the need for accurate data remain, the potential benefits of this technology make it an exciting development in the food industry.

Market Segmentation

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018 - 2022 for the following segments.

Service Type

  Online
  Offline


Type

  Digital payment
  Cash on delivery


Geography

  India

By Service Type Insights

The online segment is estimated to witness significant growth during the forecast period. The food delivery market in India has witnessed significant growth due to the increasing preference for ordering in over dining out. Consumers can now easily order their favorite cuisines through a restaurant's website or mobile app or via multi-restaurant aggregators.

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The online segment was valued at USD 114.00 million in 2018 and showed a gradual increase during the forecast period. This convenience has particularly resonated with Gen-Z, who make up a large p

The Measurable AI Rappi alternative Dataset is a leading source of email receipts and transaction data, offering data collected directly from users via Proprietary Consumer Apps, with millions of opt-in users.

We source our email receipt consumer data panel via two consumer apps which garner the express consent of our end-users (GDPR compliant). We then aggregate and anonymize all the transactional data to produce raw and aggregate datasets for our clients.

Use Cases Our clients leverage our alternative data to produce actionable consumer insights for use cases such as: - User overlap between players - Market share analysis - User behavioral traits (e.g. retention rates, spending patterns) - Average order values - Promotional strategies used by the key players - Items ordered (SKU level data) Several of our clients also use our datasets for forecasting and understanding industry trends better.

Coverage - LATAM (Brazil, Mexico, Argentina, Colombia, Chile)

Granular Data Itemized, high-definition data per transaction level with metrics such as - Order value - Items ordered - No. of orders per user - Delivery fee - Service fee - Promotions used - Geolocation data and more - MAIDs

Aggregate Data - Weekly/ monthly order volume - Revenue delivered in aggregate form, with historical data dating back to 2018. All the transactional e-receipts are sent from the Rappi food delivery app to users’ registered accounts.

Most of our clients are fast-growing Tech Companies, Financial Institutions, Buyside Firms, Market Research Agencies, Consultancies and Academia.

Our dataset is GDPR compliant, contains no PII information and is aggregated & anonymized with user consent. Contact michelle@measurable.ai for a data dictionary and to find out our volume in each country.

The Measurable AI GrabFood and GrabExpress Restaurant & Food Delivery Transaction datasets are leading sources of email receipts and transaction data, offering data collected directly from users via Proprietary Consumer Apps, with millions of opt-in users.

We source our email receipt consumer data panel via two consumer apps which garner the express consent of our end-users (GDPR compliant). We then aggregate and anonymize all the transactional data to produce raw and aggregate datasets for our clients.

Use Cases Our clients leverage our datasets to produce actionable consumer insights such as: - Market share analysis - User behavioral traits (e.g. retention rates) - Average order values - Promotional strategies used by the key players. Several of our clients also use our datasets for forecasting and understanding industry trends better.

Coverage - SE Asia (Singapore, Indonesia, Thailand, Malaysia, Philippines, Vietnam, Cambodia)

Granular Data Itemized, high-definition data per transaction level with metrics such as - Order value - Items ordered - No. of orders per user - Delivery fee - Service fee - Promotions used - Geolocation data and more

Aggregate Data - Weekly/ monthly order volume - Revenue delivered in aggregate form, with historical data dating back to 2018. All the transactional e-receipts are sent from the GrabFood and Grab Express food delivery apps to users’ registered accounts.

Most of our clients are fast-growing Tech Companies, Financial Institutions, Buyside Firms, Market Research Agencies, Consultancies and Academia.

Our dataset is GDPR compliant, contains no PII information and is aggregated & anonymized with user consent. Contact business@measurable.ai for a data dictionary and to find out our volume in each country.

In 2024, Deliveroo reported marketing and overhead costs amounting to over 210 million British pounds in the UK and Ireland. The previous year, Deliveroo's marketing and overhead costs amounted to approximately 205 million British pounds.

Understand customer behaviour, competitive benchmarking, market share etc. using Measurable AI's email receipt dataset. We own a proprietary consumer panel whereby we can access the email accounts of over 2 million users. We are GDPR compliant as we expressly receive consumer consent via our two consumer apps we built in-house: 1) Mailtime (YC2016; an email productivity app), and 2) RewardMe (cash back app that automatically rewards users with cash dollars for their real purchase data; no need to upload receipts).

We then build email parsers to parse through all the transactional data and then aggregate and anonymise the datasets to produce granular insights for our data savvy clientele.

We provide SKU-level transaction data with actual amount spent, discounts, purchase frequency, time, geolocation data.

MealMe offers in-depth restaurant menu data, including prices, from the top 100,000 restaurants across the USA and Canada. Our proprietary technology collects accurate, real-time menu and pricing information, enabling businesses to make data-driven decisions in competitive intelligence, pricing optimization, and market research. With comprehensive coverage that spans major restaurant platforms and chains, MealMe ensures your business has access to the most reliable data to excel in a rapidly evolving industry.

Platforms and Restaurants Covered: MealMe's database includes data from leading restaurant platforms such as UberEats, Postmates, ToastTakeout, SkipTheDishes, Square, Appfront, Olo, TouchBistro, and Clover, as well as direct menu data from major restaurant chains including Raising Cane’s, Panda Express, Popeyes, Burger King, and Subway. This extensive coverage ensures a detailed view of the market, helping businesses monitor trends, pricing, and availability across a broad spectrum of restaurant types and sizes.

Key Features: Comprehensive Menu Data: Access detailed menu information, including item descriptions, categories, sizes, and customizations. Real-Time Pricing: Monitor up-to-date menu prices for accurate competitive analysis. Restaurant-Specific Insights: Analyze individual restaurant chains such as Raising Cane’s and Panda Express, or platforms like UberEats, for market trends and pricing strategies. Cross-Platform Analysis: Compare menu items and pricing across platforms like ToastTakeout, Olo, and SkipTheDishes for a holistic industry view. Regional Data: Understand geographic variations in menu offerings and pricing across the USA and Canada.

Use Cases: Competitive Intelligence: Track menu offerings, pricing strategies, and seasonal trends across platforms like UberEats and Postmates or chains like Popeyes and Subway. Market Research: Identify gaps in the market by analyzing menus and pricing from top restaurants. Pricing Optimization: Use real-time pricing data to inform dynamic pricing strategies and promotions. Trend Monitoring: Stay ahead by tracking popular menu items, regional preferences, and emerging food trends. Platform Analysis: Assess how restaurants perform across delivery platforms such as SkipTheDishes, Olo, and Square. Industries Benefiting from Our Data Restaurant Chains: Optimize menu offerings and pricing strategies with detailed competitor data. Food Delivery Platforms: Benchmark menu pricing and availability across competitive platforms. Market Research Firms: Conduct detailed analyses to identify opportunities and market trends. AI & Analytics Companies: Power recommendation engines and predictive models with robust menu data. Consumer Apps: Enhance app experiences with accurate menu and pricing data. Data Delivery and Integration

MealMe offers flexible integration options to ensure seamless access to our comprehensive menu data. Whether you need bulk exports for in-depth research or real-time updates via API, our solutions are designed to scale with your business needs.

Why Choose MealMe? Extensive Coverage: Menu data from 100,000+ restaurants, including major chains like Burger King and Raising Cane’s. Real-Time Accuracy: Up-to-date pricing and menu details for actionable insights. Customizable Solutions: Tailored datasets to meet your specific business objectives. Proven Expertise: Trusted by top companies for delivering reliable, actionable data. MealMe empowers businesses with the data needed to thrive in a competitive restaurant and food delivery market. For more information or to request a demo, contact us today!

The Measurable AI Netflix Email Receipt Dataset is a leading source of email receipts and transaction data, offering data collected directly from users via Proprietary Consumer Apps, with millions of opt-in users.

We source our email receipt consumer data panel via two consumer apps which garner the express consent of our end-users (GDPR compliant). We then aggregate and anonymize all the transactional data to produce raw and aggregate datasets for our clients.

Use Cases Our clients leverage our datasets to produce actionable consumer insights such as: - Market share analysis - User behavioral traits (e.g. retention rates) - Average order values - Promotional strategies used by the key players. Several of our clients also use our datasets for forecasting and understanding industry trends better.

Coverage - Asia (Japan) - EMEA (Spain, United Arab Emirates)

Granular Data Itemized, high-definition data per transaction level with metrics such as - Order value - Items ordered - No. of orders per user - Delivery fee - Service fee - Promotions used - Geolocation data and more

Aggregate Data - Weekly/ monthly order volume - Revenue delivered in aggregate form, with historical data dating back to 2018. All the transactional e-receipts are sent from the Careem Now food delivery app to users’ registered accounts.

Most of our clients are fast-growing Tech Companies, Financial Institutions, Buyside Firms, Market Research Agencies, Consultancies and Academia.

Our dataset is GDPR compliant, contains no PII information and is aggregated & anonymized with user consent. Contact business@measurable.ai for a data dictionary and to find out our volume in each country.