The Client
Our client is a leading grocery delivery platform operating across tier-1 and tier-2 cities in India. The platform wanted to capitalize on the Janmashtami season by introducing special offers on sweets, dairy products, decorative items, and puja essentials. However, they lacked visibility into Pin Code–Wise Janmashtami Sales Data
Extraction trends and competitor offerings. They approached Food Data Scrape to:
- Track product-wise and location-wise sales trends.
- Identify Geo-Targeted Janmashtami Product Listings Data Scraping opportunities.
- Monitor competitor pricing strategies for festival products.
Key Challenges
- Fragmented Data Sources – Data was spread across multiple platforms—delivery apps, local stores, and e-commerce listings—making consolidated analysis difficult.
- Dynamic Festival Pricing – Competitors frequently updated prices for sweets, milk, curd, and decorations, creating challenges in Grocery Price Tracking Dashboard accuracy.
- Hotspot Identification – Finding high-demand locations for Janmashtami Hotspot Sales Tracking via Web Scraping required precise pin code mapping.
- Product Categorization – Differentiating between generic grocery listings and Scraping Janmashtami Festival Market Insights by Pin Code-specific products.
Key Solutions
- Real-time Data Aggregation – Using our proprietary Web Scraping Quick Commerce Data tools, we pulled location-wise order volumes, pricing changes, and product availability from multiple platforms.
- Pin Code–Level Insights – Implemented targeted Location-wise Janmashtami Festival Orders Data Extraction to map sales hotspots in cities like Mumbai, Pune, Surat, and Ahmedabad.
- Festival Trend Alerts – Integrated a Grocery Pricing Data Intelligence system to send hourly alerts on price drops, ensuring the client could match or beat competitor offers instantly.
- Competitor Monitoring – Provided a competitor-wise and product-wise analysis to identify opportunities for price advantage and product bundling.
Methodologies Used
- Geo-Targeted Data Collection – Leveraged Grocery Delivery Scraping API Services to identify Janmashtami hotspots by tracking product sales density at pin code level.
- Structured Dataset Creation – Built datasets combining product names, categories, order counts, and timestamps for Scrape Janmashtami Midnight Sweet Sale Trends Data.
- Demand Prediction Models – Used historical and live data to predict peak ordering times, especially for midnight modak and sweet sales in Maharashtra and Gujarat.
- Dynamic Pricing Analysis – Applied Grocery Pricing Data Intelligence to track and compare price fluctuations of popular Janmashtami items across regions in real time.
- Market Share Benchmarking – Combined sales and pricing insights to evaluate performance against competitors during the Janmashtami season.
Advantages of Using Food Data Scrape Services
- Accurate Hotspot Identification – Pin code–level mapping allowed the client to focus marketing spend only on high-demand localities, boosting ROI.
- Price Optimization – Our Grocery Price Tracking Dashboard gave them a competitive edge by continuously monitoring pricing fluctuations.
- Faster Inventory Planning – Insights from Extract Janmashtami Hotspot Sales Data in Maharashtra & Gujarat helped ensure popular products didn’t go out of stock.
- New Product Discovery – Identification of festival-specific items like dry fruit modak, LED jhoola lights, and Krishna idols enabled broader assortment planning.
Sample Data Tables
Table 1: Competitor Price Benchmarking
Table 2: Pin Code–Wise Janmashtami Sweet Sales (Mumbai)
Table 3: Midnight Order Trends in Gujarat
Client’s Testimonial
"Working with Food Data Scrape completely transformed the way we approached our Janmashtami sales strategy. Before partnering with them, our promotional campaigns were based largely on assumptions and past experiences. Their team provided us with accurate, location-specific sales data, allowing us to focus our marketing on high-demand areas while fine-tuning our pricing in real time. The level of detail in their reports—down to the pin code level—was unmatched. Not only did this help us avoid overstocking or understocking, but it also improved customer satisfaction during the festive rush. We have never had such a seamless and data-driven execution for a festival season before, and this has set a new benchmark for how we will approach all major events going forward."
— Head of Marketing, Leading Grocery Delivery Platform
Final Outcomes:
The project delivered measurable results within just one festival cycle:
- Sales Boost in Hotspots – The client saw a 27% increase in sales across targeted high-demand locations.
- Reduced Wastage – Better inventory planning led to a 19% reduction in unsold stock, particularly in perishable items like sweets and dairy products.
- Competitive Pricing Wins – Real-time alerts allowed the client to respond to competitor price changes within an hour, capturing additional market share.
- Improved Customer Retention – Targeted offers and product availability during peak demand improved repeat order rates by 22%.
- Strategic Planning for Future Events – The datasets generated are now being used as a reference for Diwali, Ganesh Chaturthi, and other high-demand festive periods.
This case study proved that combining hyper-local market intelligence with agile decision-making can significantly enhance sales performance during culturally significant events.
