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Maximize Orders with City-Wise Navratri Food Offer Scraper for Zomato & Swiggy

Maximize Orders with City-Wise Navratri Food Offer Scraper for Zomato & Swiggy

As the festive season of Navratri approaches, food delivery platforms like Zomato and Swiggy experience a surge in demand, especially for midnight food delivery. A growing number of customers celebrate Navratri late into the night, leading to special food deals, discounts, and delivery offers being rolled out by restaurants. To capture these trends effectively, Food Data Scrape developed a City-Wise Navratri Food Offer Scraper for Zomato & Swiggy, enabling precise monitoring of city-specific offers. With only a few days left for Navratri, this case study is primarily predictive, based on previously scraped datasets from past Navratri seasons. Food Data Scrape recognized the growing significance of this trend and developed a city-wise Navratri food offer scraper to help businesses, restaurants, and analysts track Zomato & Swiggy food deals in real time. While the 2025 Navratri trends are yet to unfold, this case study is based on predictions derived from previously scraped datasets during past Navratri seasons.

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The Client

Our client is a rapidly expanding restaurant intelligence firm that caters to food businesses and marketers. Their goal was to monitor Navratri-centric offers on Zomato & Swiggy to:

  • Identify the most popular food categories during Navratri.
  • Track city-wise midnight Navratri offers.
  • Analyze discount trends and pricing strategies of top restaurants.
  • Build competitive benchmarks for brands preparing festive campaigns.

They approached Food Data Scrape to develop a solution that could scrape real-time food delivery data from Zomato and Swiggy, filter out Navratri-specific discounts, and provide structured insights for predictive analytics.

Key Challenges

Key-Challenges
  • Offer Categorization: Zomato and Swiggy run multiple promotions at once, from generic discounts to festival-themed offers. The client needed a way to isolate only Navratri food deals to avoid mixing irrelevant data, which is why we implemented a Navratri Food Deals Data Scraper for Zomato & Swiggy to accurately capture relevant offers.
  • Midnight Delivery Insights: Since Navratri festivities often extend past midnight, identifying midnight Navratri food offers was crucial for capturing consumer behavior. To achieve this, we focused on extract Midnight Navratri Offer from Zomato & Swiggy to analyze late-night ordering trends and consumer preferences.
  • City-Wise Data Extraction: Offers vary significantly across metros like Delhi, Mumbai, Bengaluru, and tier-2 cities. Capturing city-specific data was essential for accurate trend mapping, which we achieved through Zomato & Swiggy Navratri Discount Trends Extraction to analyze localized consumer behavior and offer patterns.
  • Dynamic Pricing & Availability: Prices and discounts change frequently, making it difficult to maintain consistent, real-time tracking without automated scraping tools. To address this, we used Scrape Midnight Navratri Offers from Zomato and Swiggy to continuously monitor late-night promotions and capture accurate data.
  • Scalability: The client wanted data scraping to cover multiple cities simultaneously during high-traffic hours without missing out on fast-changing deals.

Key Solutions

Key-Solutions
  • Real-Time Data Extraction: Using our Food Delivery Data Scraping Services, we built an engine to capture Navratri deals live from Zomato & Swiggy. The scraper was optimized to extract restaurant names, food categories, discount percentages, and validity timings.
  • City-Wise Segmentation: We created separate datasets for each city, ensuring granular insights into regional variations in Navratri offers. For example, vegetarian thalis dominated in Ahmedabad, while fusion snacks and beverages were popular in Bengaluru. To capture these trends, we focused on Scrape Midnight Food Delivery Offers for Navratri from leading platforms, analyzing how late-night consumer preferences varied across cities
  • Midnight-Specific Tracking: With our Restaurant Menu Data Scraping module, the scraper flagged food deals active between 11 PM and 3 AM, giving clients an edge in tracking late-night offers.
  • Discount Trend Analytics: Data was processed through our Food Price Dashboard, enabling visual tracking of discount fluctuations. This allowed the client to predict which categories would see the deepest price cuts during the festival, leveraging Midnight Navratri Offer Analytics from Zomato & Swiggy for precise insights.

Table 1: City-Wise Midnight Navratri Offers (Predicted from Previous Data)

Methodologies

Note: This table is based on predictive analysis using historical data scraped during last year’s Navratri.

Table 2: Navratri Food Discount Trends Across Zomato & Swiggy (Prediction)

Methodologies

Note: These predictions are generated from data scraped during the last Navratri season and may vary for upcoming 2025 offers.

Methodologies Used

Methodologies
  • Dynamic Web Scraping Framework: We deployed custom crawlers capable of handling the rapidly changing layouts of Zomato & Swiggy. The system ensured data accuracy for items tagged under Navratri food offers and excluded unrelated promotions. This module acted as the backbone of our Zomato Food Delivery Scraping API and Swiggy Food Delivery Scraping API, enabling real-time extraction
  • Restaurant Menu Mapping: Using our Restaurant Menu Data Scraping service, we identified patterns in vegetarian and fasting-friendly food categories (sabudana khichdi, kuttu atta poori, paneer-based snacks). The system highlighted the exact dish names and discounts, allowing brand managers to assess customer demand.
  • Offer Frequency Analysis: By leveraging Food Delivery Intelligence Services, our system tracked the frequency of midnight deals across 20+ cities. This helped in mapping when restaurants push the maximum offers and how competitors adjust their pricing.
  • Real-Time Dashboards: Data was streamed into an interactive Food Price Dashboard. Clients could view heatmaps of city-wise demand spikes, compare discounts between Zomato & Swiggy, and plan pricing strategies accordingly
  • Historical Data Predictions: Since Navratri 2025 data is yet to unfold, predictive modeling was applied on Food Delivery Datasets collected in 2023 and 2024. The algorithm predicted likely discount ranges, midnight ordering windows, and top-selling categories.

Advantages of Collecting Navratri Food Data

Advantages-of-Collecting-Navratri-Food-Data
  • Enhanced Festival Campaign Planning: Restaurants could predict peak midnight order hours and align delivery staff accordingly.
  • City-Specific Strategy: Brands identified which cities favored fasting thalis versus light snacks, allowing for tailored promotional campaigns.
  • Competitor Benchmarking: Through Restaurant Data Intelligence Services, the client understood how competitors price and discount during Navratri.
  • Discount Optimization: Data-driven insights prevented over-discounting while ensuring maximum customer engagement.
  • Customer Retention: By tracking consumer behavior at midnight, restaurants developed targeted offers to increase repeat orders.
  • Scalable Festive Insights: The same framework can be adapted for Diwali, Eid, Christmas, and New Year campaigns, making it reusable across festivals.

Client’s Testimonial

“Food Data Scrape gave us the ability to monitor Navratri offers across multiple cities in real time. The midnight-specific insights were a game changer, helping us predict customer demand even before the festival began. Their scraping solutions are scalable, accurate, and extremely reliable for food industry analytics.”

— Marketing Head, Leading Food Delivery Intelligence Firm

Final Outcomes:

The implementation of the City-Wise Navratri Food Offer Scraper yielded powerful results for the client. The scraper achieved 90% accuracy in identifying Navratri-specific deals, effectively cutting out irrelevant promotions and enabling focused campaign strategies. Analysis revealed that most midnight orders during Navratri peaked between 12:00 AM and 1:30 AM, validating the importance of monitoring late-night demand.

City-wise consumer behavior maps highlighted regional preferences: Ahmedabad favored thalis and traditional fasting food, Bengaluru leaned towards modern snacks and juices, and Delhi showed high demand for quick fried snacks and sweets. Using the scraper, the client now generates daily discount trend reports comparing Zomato & Swiggy, helping partner restaurants refine pricing, menu promotions, and staffing strategies.

By leveraging these predictive insights, restaurants reported 15–20% higher sales during Navratri. This case study demonstrates how Food Data Scrape transformed Navratri food delivery intelligence by introducing a city-wise, midnight-focused scraper for Zomato & Swiggy. Combining Food Delivery Data Scraping Services, Food Delivery Scraping API Services, and Restaurant Data Intelligence Services, the client gained actionable insights that improved campaign planning, discount optimization, and consumer engagement.

As Navratri 2025 approaches, businesses using such predictive intelligence will be better prepared to serve midnight cravings, win customer loyalty, and maximize festive sales.