Introduction

In India’s booming food delivery ecosystem, menu prices on Swiggy and Zomato are no longer static. Prices fluctuate based on:

• Location-specific demand

• Peak delivery hours

• Restaurant promo cycles

• Platform-led dynamic pricing models

For restaurant chains, aggregators, and pricing strategists, tracking these changes in real time is vital. Actowiz Solutions offers an AI-powered scraping engine that monitors dynamic menu pricing across cities—hourly, geo-tagged, and category-wise.

Why Dynamic Menu Monitoring Is Crucial

• Real-Time Adjustments: Menu items may cost more in the evening or during weekends

• Surge Pricing & Delivery Fee Bundling affects perceived food cost

• Location Variance: A single chain may price biryani at ₹250 in Delhi and ₹210 in Ahmedabad

• Offers May Differ by Pin Code-Zomato Pro, festival discounts, or bank offers

How AI-Powered Menu Price Scraping Works

1. City-Based Restaurant List Compilation

AI scrapers crawl Swiggy and Zomato city-wise to extract active restaurant listings based on user location.

2. Hourly Menu Price Fetching

Each restaurant’s menu is scraped every 30–60 minutes, collecting base price, taxes, add-ons, and dynamic charges.

3. Price Change Detection Engine

Our AI models highlight fluctuations for the same menu item by time, city, or offer logic.

Sample Data Extracted

Swiggy – Mumbai:

• Restaurant: Behrouz Biryani

• Menu Item: Mutton Biryani

• Time: 1 PM

• Base Price: ₹345

• Final Price: ₹395

• Offer Tag: 25% Off
  
  

Zomato – Mumbai:

• Restaurant: Behrouz Biryani

• Menu Item: Mutton Biryani

• Time: 1 PM

• Base Price: ₹345

• Final Price: ₹379

• Offer Tag: Zomato Pro – 20%
  
  

Swiggy – Bengaluru:

• Restaurant: Behrouz Biryani

• Menu Item: Mutton Biryani

• Time: 1 PM

• Base Price: ₹345

• Final Price: ₹345

• Offer Tag: No Promo

AI-Driven Features by Actowiz

• Time-Series Price Tracking

• Geo-Price Variance Models

• Tag-Based Promo Mapping (Zomato Pro, Festival Offers, BOGO)

• Price Benchmark Reports by Cuisine/Restaurant Chain

Key Use Cases

Restaurant Chains

Monitor how third-party delivery platforms modify your menu prices city-wise or under dynamic load.

FoodTech Startups

Scrape pricing from 1000s of restaurants daily to power price comparison tools or insights dashboards.

Q-Commerce & Hyperlocal Players

Align bundled FMCG and meal pricing during high-demand hours based on competitor food pricing.

Business Impact

A multicity pizza chain used Actowiz's hourly pricing tracker to negotiate fair pricing enforcement with Zomato in Tier-2 cities—restoring control across 45 outlets.

A meal subscription startup identified pricing gaps of 18–22% between Zomato and Swiggy for the same SKUs, enabling smart redirection for margin-optimized conversions.

Visualization Example

• Line Chart: Hourly menu price vs. delivery slot (by platform)

• Map Overlay: City-wise average markup on menu prices across India

• Bar Chart: Menu item base price vs. delivery-inclusive price across 5 metros

Tech Stack Used

• Scraping: Selenium, Playwright + Python

• AI/ML: Time Series Pattern Recognition

• Storage: AWS RDS + S3

• Delivery: Excel, API Feed, or PowerBI Dashboards

Compliance & Fair Use

• Adheres to public data access norms

• All scraped data is from customer-visible interfaces

• No login-protected or personal data scraped

Final Takeaway

India’s online food delivery landscape is algorithmic, dynamic, and deeply localized. If your pricing isn’t monitored, your margins are silently eroded. With Actowiz Solutions’ AI-powered scraping, you can track, respond, and stay competitive

Want to monitor your competitor’s menu pricing every hour in every city? Start a pilot project with Actowiz Solutions today!

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