Flight Price Volatility Tracker for an Indian Travel Aggregator Using Yatra & MMT Data
Overview
In India’s highly dynamic travel market, flight fares can fluctuate multiple times per day. To stay competitive and drive user trust, a major Indian travel aggregator needed to track real-time flight price volatility across Yatra and MMT. They partnered with Travel Scrape to build a Flight Price Volatility Tracker using structured scraping and AI-based trend models.
Within three months, the solution led to a 28% increase in booking conversions, reduced fare complaint tickets, and enabled a new revenue stream via B2B data resale.
Project Goals
- Scrape and analyze flight fare changes on Indian routes from Yatra and MMT.
- Build a price volatility dashboard by date, route, and carrier.
- Power "Book Now" or "Wait" recommendations within the aggregator’s mobile app.
- Reduce last-minute refund requests caused by rapid fare fluctuations.
- Provide API access to corporate travel partners and agencies.
Why Yatra & MakeMyTrip?
These are India’s most used flight booking platforms after IRCTC and airline websites. They offer:
- Real-time pricing with frequent updates.
- Calendar-based views with lowest price per day.
- Filters by airline, stop, fare class, baggage, etc.
- Special deals (Flash Sales, Monsoon Offers, etc.)
Scraping Yatra and MMT gives visibility into the broader OTA ecosystem—essential for competitive positioning.
Travel Scrape's Data Strategy
1. Route & Frequency Planning
- Focused on 150 top domestic routes, including:
- Delhi ↔ Mumbai
- Bengaluru ↔ Hyderabad
- Chennai ↔ Kolkata
- Pune ↔ Goa
- Ahmedabad ↔ Delhi
2. Flight Data Fields Extracted
| Field | Example Value |
|---|---|
| Source & Destination | Delhi – Mumbai |
| Airline | IndiGo |
| Departure Date | 2025-06-22 |
| Price (Economy) | ₹3,150 |
| Flight Time | 6:15 AM – 8:05 AM |
| Stops | Non-stop |
| Class | Economy |
| Booking Platform | Yatra / MMT |
| Fare Change (24 hrs) | +₹450 |
| Availability Alert | “Only 5 seats left” |
3. Scraping Infrastructure
- Headless Chrome (Puppeteer) for JavaScript-rendered elements.
- Proxy rotation + cookie simulation to avoid blocks.
- Scheduled scraping: Hourly intervals, 3x daily per route.
- Data stored in MongoDB + S3 backup for fast access.
4. Volatility Score Algorithm
Using a custom scoring model based on:
- Price range in last 7 days
- % daily fluctuation
- Number of fare updates in 24 hours
- Availability + airline volatility history
Sample JSON Data
App Integration & UX Enhancements
- “Fare Alert” Tags: Triggered for routes with >15% volatility
- “Best Time to Book” Tool: Based on 7-day historical trend
- Dynamic Callouts: “Likely to increase by ₹300 – Book Now!”
Dashboard Visuals:
- Volatility graph by route
- Airline-specific fluctuation charts
- Time-of-day-based fare change heatmaps
Results After 90 Days
| Metric | Before Travel Scrape | After Integration |
|---|---|---|
| Booking Conversion Rate | 4.2% | 6.7% |
| Customer Support Tickets (Fares) | 1,100/month | 540/month |
| User Time Spent on Route Pages | 52 seconds | 1 min 28 sec |
| Alert-Driven Conversions | – | 8,400+ |
| Daily API Usage (B2B Clients) | – | 1.2M+ calls |
Insights from Scraped Data
Top 5 Most Volatile Routes (Q2 2025)
| Route | Avg. Daily Change | Max Fluctuation | Best Booking Time |
|---|---|---|---|
| Delhi – Mumbai | ₹325 | ₹850 | 7–10 days in advance |
| Bengaluru – Delhi | ₹290 | ₹760 | Early morning |
| Mumbai – Goa | ₹180 | ₹420 | Weekdays |
| Kolkata – Pune | ₹270 | ₹580 | Afternoons |
| Hyderabad – Chennai | ₹200 | ₹610 | 10+ days out |
Client Testimonial
"We were struggling with real-time airfare transparency. Travel Scrape’s volatility tracker helped reduce our support load, improve trust, and offer genuine booking advice to our users."
Technical Stack Summary
- Scraping Tools: Puppeteer, Python, Selenium (fallback)
- Storage: MongoDB, AWS S3
- Processing: Pandas, NumPy, Scikit-Learn (for volatility modeling)
- API Delivery: FastAPI
- Dashboard: Grafana / Streamlit
Challenges Solved
| Problem | Travel Scrape Solution |
|---|---|
| CAPTCHA Blocks on Yatra/MMT | Real browser headers + delay management |
| Calendar View Extraction | JavaScript DOM scraping with headless tools |
| Rate Limits / IP Blacklisting | Proxy pools & geo-rotation |
| Multi-day Trend Comparison | Data warehousing + time-based triggers |
| Conversion Attribution | UTM-based tracking & alert interaction logs |
Conclusion
Travel Scrape’s flight price volatility solution empowered one of India’s top OTAs to stay ahead in the fast-moving air travel market. With Yatra and MMT data at their fingertips, the client:
- Increased conversion rates
- Improved fare transparency
- Reduced refunds and support issues
- Launched API-based fare trend services
As airline pricing becomes more dynamic and AI-driven, scraping insights from OTAs is the foundation for smarter travel platforms in India and beyond.