Introduction
The growing complexity of regional tastes and product variety across India has made data-driven decision-making critical for restaurant chains. For a legacy brand like Haldiram’s, which operates across multiple formats—restaurants, snack counters, and sweet shops—granular insights into pricing, performance, and customer preferences are essential. ArcTechnolabs partnered with the brand to deliver a comprehensive Restaurant Dataset for Haldiram’s India. This dataset enabled actionable intelligence on outlet performance, category-specific demand, and regional pricing variances using advanced web scraping services and automation tools designed for the food and hospitality sector.
The Client
Our client is a leading consumer research and retail analytics firm focused on India’s fast-growing food and beverage sector. They provide location-level intelligence, pricing studies, and trend forecasting for brands, aggregators, and investors. The firm approached ArcTechnolabs to extract structured insights from Haldiram’s—one of India’s most well-known food chains. They sought to build a unified Restaurant Dataset for Haldiram’s India to evaluate regional menu differences, track pricing trends, and benchmark product availability across outlets. The data would support various downstream use cases, including competitive pricing reports, menu optimization models, and market-entry advisories. To support these goals, Actowiz deployed tools for web scraping Haldiram’s restaurant data, including mobile app feeds, delivery platform listings, and branded websites. The dataset would become a foundational asset for cross-brand comparisons and regional consumer demand studies, enabling the client to provide sharper insights and forecasts for their enterprise customers.
Key Challenges
Haldiram’s operates across diverse regions of India, where product availability, pricing, and category focus vary widely. One major challenge was the lack of structured access to data from their own stores spread across platforms—websites, third-party delivery apps, and physical menus. The brand struggled to compare item-level data across locations. Without this, menu optimization, regional pricing strategy, and demand forecasting remained inconsistent. Another challenge was tracking dynamic product pricing and category rotation based on seasonal changes, festivals, and local demand. Manual monitoring was time-consuming and unreliable, leading to missed opportunities in product bundling and customer targeting. Moreover, data from delivery platforms was unstructured and difficult to clean. Without an automated solution to extract Haldiram’s product data , it was impossible to measure store-specific performance. The brand also sought insights from the Indian Sweets & Snacks Dataset from Haldiram’s, which needed accurate classification and pricing normalization to power internal dashboards.
Key Solution
ArcTechnolabs implemented a fully automated data pipeline to deliver a structured, actionable Restaurant Dataset for Haldiram’s India. Using its advanced web scraping services and proprietary tools, Actowiz mapped all live Haldiram’s restaurant outlets across India from both brand-owned platforms and major food delivery apps. To handle dynamic menus and region-specific items, Actowiz deployed mobile app scraping services targeting top cities where offerings varied. The team used AI models to recognize item types and categorize sweets, snacks, beverages, and meals. This data was streamlined into the Haldiram’s Menu and Product Datasets, covering over 3,500 unique food items. We also enabled scraping Haldiram’s food prices and categories, capturing real-time pricing data across locations. This helped Haldiram’s conduct pricing audits and optimize rates for highly competitive SKUs. Through the Haldiram’s Menu Scraping API, data was fetched and refreshed weekly for accuracy and compliance. The system allowed the client to extract Haldiram’s food items and rates location-wise, powering internal dashboards. Advanced visualizations highlighted which items performed better regionally and which needed menu restructuring. Using our techniques for scrape Haldiram’s restaurant menu and pricing data, they improved bundling offers and aligned pricing to local expectations. This solution also included restaurant chain-level mapping, building historical trends using restaurant data scraping techniques . The clean, categorized >Haldiram’s restaurant datasets became a cornerstone for product development and competitive benchmarking. .
Client Testimonial
"ArcTechnolabs helped us completely transform our product strategy through precise, real-time restaurant data. Their ability to build a reliable Restaurant Dataset for Haldiram’s India empowered our regional and pricing teams with the clarity they needed to act faster. We were finally able to align our SKUs, bundles, and pricing across channels. The integration was seamless, and the results were immediate. The team at Actowiz made it easy for our business users to access and act on complex restaurant datasets."
— Head of Strategy
Conclusion
ArcTechnolabs’ expertise in Restaurant Dataset for Haldiram’s India empowered Haldiram’s with unparalleled visibility into product trends, pricing patterns, and outlet-level insights. By combining Web Scraping Haldiram’s Restaurant Data with structured analytics, the solution offered the brand a future-proof platform for menu engineering and store performance optimization. This engagement highlighted the growing need for automated restaurant datasets in India’s evolving F&B space. Looking to unlock insights from your food business data? Contact ArcTechnolabs for enterprise-grade restaurant and menu scraping services today!
