MakeMyTrip Dataset
Live and Historical Data Across India’s Leading Online Travel Booking Platform
Travel pricing behaves nothing like retail pricing, and MakeMyTrip’s listings reflect that directly. A flight fare for the exact same route and date can be a different number every time you search it, moving with days-to-departure, seat-class availability, and airline revenue-management logic passed straight through to the OTA. Hotel pricing adds a second layer of complexity — rates are set per date on an availability calendar rather than a single per-item price, so the “price” of a room genuinely means “price for this specific night,” and it can sell out entirely while a different date at the same property still shows availability.
Tracking that properly means capturing fare and rate movement across the booking window as a core dimension of the dataset, not collapsing it into a single snapshot. That’s exactly what our dedicated Travel Data Scraping pipeline is built to handle for MakeMyTrip specifically — a MakeMyTrip Travel Dataset that ties flight fares, hotel rates, booking data, and reviews together, refreshed on a schedule you control. It sits inside our broader Travel Dataset catalog, built on the same infrastructure as our Travel Data Scraping services, with custom builds available through our Web Scraping Services team.
Request Free Sample DatasetQuick Stats
Price From
$219Starting Price
Records
4M+Total Records
Format
CSV / JSONDelivery Format
Delivery
ImmediateAvailability
Travel
Core Coverage
2+ Yrs
Historical Depth
Global
Route Coverage
Daily
Refresh Cycle
Why Teams Choose Our MakeMyTrip Dataset Over a DIY Crawl
A single price snapshot tells you almost nothing useful about airfare or hotel-rate behavior, since both move continuously with days-to-departure and date-specific demand. A scraper that checks once and stops has already missed the point.
One Schema, Flights and Hotels Together
Flight fares, hotel rates, booking terms, and reviews all arrive in a single MakeMyTrip dataset — normalized so combined package data doesn’t get lost between exports.
Booking-Window Precision
Our MakeMyTrip Pricing Dataset tracks fare and rate movement across the full booking window, not a single point-in-time snapshot, so fare curves are actually visible.
Scoped to What You Actually Need
Pull specific routes, destinations, or the full catalog. Refresh daily, weekly, or near-live. Delivered as CSV, JSON, Excel, or a direct API feed.
Formats Your Tools Already Read
CSV and Excel exports work straight in Power BI or Tableau. JSON and API feeds ship with a documented schema for Snowflake, BigQuery, or Redshift.
Live Fares, Plus Real History
See today’s fares and rates alongside 2+ years of historical pricing patterns across routes and destinations.
Date-Level Hotel Availability Tracked
Coverage tracks hotel rate and availability per specific night, since a property’s calendar can vary sharply date to date rather than following one flat rate.
What’s Actually Inside the MakeMyTrip Dataset
The MakeMyTrip dataset answers five practical questions: what fares and rates are available, how they move across the booking window, what the booking terms actually allow, how properties and routes are rated, and what customers say about the experience. Those five questions map to the five sub-datasets described below, keyed together on route, property, and booking identifiers.
Most clients start with the pricing layer, usually chasing something specific — how does fare on a given route change as departure approaches, or how much does a bundled flight-plus-hotel package undercut booking the two separately? Revenue teams lean on the booking-terms layer to understand cancellation and refund policy differences across fare classes and rate plans. Data teams mostly just want clean, timestamped records instead of raw search-result data, which is really the core value of buying a dataset instead of building a scraper from scratch. This dataset shares its collection standards with our broader Travel Dataset catalog.
What people actually build with this dataset:
- Fare-curve analysis: Track how airfare on a given route moves as departure date approaches, to identify optimal booking windows.
- Hotel rate-parity checks: Compare a property’s MakeMyTrip rate against its direct-booking price and other OTAs for the same date.
- Package-pricing analysis: Measure how much bundled flight-plus-hotel packages discount versus booking each component separately.
- Cancellation-policy benchmarking: Compare refund and cancellation terms across fare classes and rate plans.
- Sentiment research: Mine the MakeMyTrip Reviews Dataset for recurring complaints about booking accuracy, hotel quality, or customer support.
Key Metrics
Price
$219.00Format
CSV / JSON / APIRecords
4M+ Verified RecordsCoverage
Domestic + InternationalUpdate Frequency
DailyAvailability
Instant AccessDelivery Time
ImmediatelyPreview actual dataset structure before purchase.
A Sample of the MakeMyTrip Dataset
Below is a small, illustrative slice of flight and hotel data from a single extract. Each row captures a fare or rate observation at a specific point in the booking window. Over 45 additional fields are available, including fare-class breakdowns, cancellation terms, and full historical pricing curves.
| Hotel ID | Hotel Name | Hotel Address | Hotel Image | Price | Rating | Rating Text | Reviews Count | Tags | Hotel URL | Extra Images | Extra Images Name |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 202507231621402983 | Olive Nest 1Bhk, at Hill Road | Bandra West | 9 minutes walk to Lilavati Hospital And Research Centre | https://r1imghtlak.mmtcdn.com/033b67b3-7cf6-4752-aa4d-5b8c6b9f9e97.png?output-format=jpg&downsize=720:* | ₹3,438 | 3.3 | Good | 8 | Couple Friendly, Entire 1-Bedroom Serviced Apartment | https://www.makemytrip.com/hotels/hotel-details?hotelId=202507231621402983&_uCurrency=INR&checkin=09032026&checkout=09042026&city=CTBOM&country=IN&lat=19.05508&lng=72.83476&locusId=CTBOM&locusType=city&rank=154®ionNearByExp=3&roomStayQualifier=2e0e&rsc=1e2e0e&searchText=Mumbai&mtkeys=undefined | ||
| 202506041323056845 | Hotel Samrat Palace 2 | Goregaon | 630 m drive to Goregaon Railway Station | https://r1imghtlak.mmtcdn.com/4414f1a0-4afe-4945-a93e-b3813a116d7f.jpg?output-format=jpg&downsize=720:* | ₹1,980 | 3.3 | Good | 29 | Couple Friendly | https://www.makemytrip.com/hotels/hotel-details?hotelId=202506041323056845&_uCurrency=INR&checkin=09032026&checkout=09042026&city=CTBOM&country=IN&lat=19.16656&lng=72.84598&locusId=CTBOM&locusType=city&rank=155®ionNearByExp=3&roomStayQualifier=2e0e&rsc=1e2e0e&searchText=Mumbai&mtkeys=undefined | https://go-assets.ibcdn.com/u/MMT/images/1780907242200-trueflexi_mmt.png | Guaranteed Early Check-in/Late Check-out available |
| 202209210015509219 | Hotel Avion Park Mumbai | Andheri West | 2.5 km drive to Kokilaben Dhirubhai Ambani Hospital | https://r1imghtlak.mmtcdn.com/fc67cd31-9004-4eb6-bb9c-5d5424d6b971.jpeg?output-format=jpg&downsize=720:* | ₹1,703 | 3.1 | Good | 66 | Couple Friendly | https://www.makemytrip.com/hotels/hotel-details?hotelId=202209210015509219&_uCurrency=INR&checkin=09032026&checkout=09042026&city=CTBOM&country=IN&lat=19.12293&lng=72.84423&locusId=CTBOM&locusType=city&rank=156®ionNearByExp=3&roomStayQualifier=2e0e&rsc=1e2e0e&searchText=Mumbai&mtkeys=undefined | https://promos.makemytrip.com/AutoSuggest/AI_Semantic.png | Conveniently located near Andheri station and restaurants, supportive and good service staff |
| 201612232100593354 | Hotel Terminus Square | Chembur | 6 minutes walk to Lokmanya Tilak Terminus | https://r1imghtlak.mmtcdn.com/a7df1f72024c11e7ae9a0a209fbd0127.jpg?output-format=jpg&downsize=720:* | ₹1,957 | 3.6 | Very Good | 179 | Couple Friendly | https://www.makemytrip.com/hotels/hotel-details?hotelId=201612232100593354&_uCurrency=INR&checkin=09032026&checkout=09042026&city=CTBOM&country=IN&lat=19.06622&lng=72.89186&locusId=CTBOM&locusType=city&rank=161®ionNearByExp=3&roomStayQualifier=2e0e&rsc=1e2e0e&searchText=Mumbai&viewType=BUDGET&mtkeys=undefined | https://go-assets.ibcdn.com/u/MMT/images/1780907242200-trueflexi_mmt.png | Guaranteed Early Check-in/Late Check-out available |
| 202503111241212682 | Sai Plaza Residency | Dadar East | 10 minutes walk to TATA MEMORIAL HOSPITAL | https://r1imghtlak.mmtcdn.com/aeec8bc7-1da0-492e-b440-b6a26ac10aeb.jpeg?output-format=jpg&downsize=720:* | ₹2,322 | 2.8 | Average | 40 | Couple Friendly, Private Room in a Serviced Apartment | https://www.makemytrip.com/hotels/hotel-details?hotelId=202503111241212682&_uCurrency=INR&checkin=09032026&checkout=09042026&city=CTBOM&country=IN&lat=19.01082&lng=72.84252&locusId=CTBOM&locusType=city&rank=162®ionNearByExp=3&roomStayQualifier=2e0e&rsc=1e2e0e&searchText=Mumbai&mtkeys=undefined | ||
| 202608202022493097 | Charming 1BHK in Bandra West Near Carter Road | Bandra West | 2.1 km drive to Juhu Beach | https://r1imghtlak.mmtcdn.com/fd5fc938-ab1a-4747-909c-3ae4d36aee2b.png?output-format=jpg&downsize=720:* | ₹ 6,761 | Couple Friendly, Entire 1-Bedroom Homestay | https://www.makemytrip.com/hotels/hotel-details?hotelId=202608202022493097&_uCurrency=INR&checkin=09032026&checkout=09042026&city=CTBOM&country=IN&lat=19.06594&lng=72.82536&locusId=CTBOM&locusType=city&rank=157®ionNearByExp=3&roomStayQualifier=2e0e&rsc=1e2e0e&searchText=Mumbai&mtkeys=undefined | https://promos.makemytrip.com/Hotels_product/Listing/Newtommtv3.png | ||||
| 202002061822418769 | Hotel Malad Inn | Malad | 5 minutes walk to Malad Railway Station | https://r2imghtlak.mmtcdn.com/r2-mmt-htl-image/room-imgs/202002061822418769-252-308f3ac9-0758-4e89-9456-b8cbf21e5544.jpg?output-format=jpg&downsize=720:* | ₹2,860 | 3.1 | 200 | Couple Friendly | https://www.makemytrip.com/hotels/hotel-details?hotelId=202002061822418769&_uCurrency=INR&checkin=09032026&checkout=09042026&city=CTBOM&country=IN&lat=19.18399&lng=72.84806&locusId=CTBOM&locusType=city&rank=158®ionNearByExp=3&roomStayQualifier=2e0e&rsc=1e2e0e&searchText=Mumbai&viewType=BUDGET&mtkeys=undefined | https://go-assets.ibcdn.com/u/MMT/images/1780907242200-trueflexi_mmt.png | Guaranteed Early Check-in available | |
| 201704201241093908 | A1 Hotel | Malad | 2 minutes walk to Malad Railway Station | https://r1imghtlak.mmtcdn.com/fa8f5d9eb04c11e984270242ac110005.png?output-format=jpg&downsize=720:* | ₹2,555 | 3.2 | Good | 230 | Couple Friendly | https://www.makemytrip.com/hotels/hotel-details?hotelId=201704201241093908&_uCurrency=INR&checkin=09032026&checkout=09042026&city=CTBOM&country=IN&lat=19.1879&lng=72.85026&locusId=CTBOM&locusType=city&rank=159®ionNearByExp=3&roomStayQualifier=2e0e&rsc=1e2e0e&searchText=Mumbai&mtkeys=undefined | https://promos.makemytrip.com/AutoSuggest/AI_Semantic.png | Proximity to Malad East railway station, located in a busy market area, numerous nearby food options |
| 202309061736161829 | Hotel Alfa Executive | Andheri West | 8 minutes walk to Andheri Railway Station | https://r2imghtlak.mmtcdn.com/r2-mmt-htl-image/htl-imgs/202309061736161829-8a900b5a67ff11ee8b7b0a58a9feac02.jpg?output-format=jpg&downsize=720:* | ₹3,881 | 3.7 | 153 | https://www.makemytrip.com/hotels/hotel-details?hotelId=202309061736161829&_uCurrency=INR&checkin=09032026&checkout=09042026&city=CTBOM&country=IN&lat=19.1188&lng=72.84329&locusId=CTBOM&locusType=city&rank=160®ionNearByExp=3&roomStayQualifier=2e0e&rsc=1e2e0e&searchText=Mumbai&mtkeys=undefined | https://promos.makemytrip.com/AutoSuggest/AI_Semantic.png | Centrally located near Andheri, spacious family rooms, friendly staff for a pleasant stay. | ||
| 202608141616165705 | Orchid Shared Apartment in Bandra | Bandra | 7 minutes walk to Lilavati Hospital And Research Centre | https://r1imghtlak.mmtcdn.com/1f904f1e-632b-4505-be24-139b074bd488.png?output-format=jpg&downsize=720:* | ₹ 3,271 | Private Room in an Apartment | https://www.makemytrip.com/hotels/hotel-details?hotelId=202608141616165705&_uCurrency=INR&checkin=09032026&checkout=09042026&city=CTBOM&country=IN&lat=19.04971&lng=72.82553&locusId=CTBOM&locusType=city&rank=163®ionNearByExp=3&roomStayQualifier=2e0e&rsc=1e2e0e&searchText=Mumbai&mtkeys=undefined | https://promos.makemytrip.com/Hotels_product/Listing/Newtommtv3.png |
The Five Layers of the MakeMyTrip Dataset
Rather than one flat export, the MakeMyTrip dataset splits into five connected layers, licensed individually or together as a complete MakeMyTrip Travel Dataset, joined on common route, property, and booking keys.
MakeMyTrip Flight Dataset
The structured layer behind every flight search result — route, carrier, fare class, and the seat-availability signals that drive fare movement.
- Origin-destination pair, airline, flight number, and departure/arrival times
- Fare class (economy, premium economy, business) and fare-type flags (refundable, non-refundable, saver, flexi)
- Layover and connection details for non-direct routes
- Baggage allowance and add-on pricing where available
MakeMyTrip Hotel Dataset
The structured layer behind every hotel listing — property details, room types, and the amenity information that shapes booking decisions.
- Property name, star rating, location, and amenity list
- Room-type inventory, occupancy limits, and meal-plan options
- Photo and description content per property
- Date-level availability calendar, since rooms sell out per night rather than as a single stock count
MakeMyTrip Pricing Dataset
Both flight fares and hotel rates move continuously with the booking window, and this layer is where that movement gets captured rather than lost.
- Fare and rate history tracked by days-to-departure or days-to-check-in
- Package-pricing data showing bundled flight-plus-hotel pricing against standalone component pricing
- Promotional and coupon-linked pricing, including MakeMyTrip Black member pricing where applicable
- Tax, convenience-fee, and total-price breakdowns
MakeMyTrip Booking Dataset
Booking terms materially affect what a listed price actually represents, and this layer captures the conditions attached to each fare or rate.
- Cancellation policy and refund-window terms by fare class or rate plan
- Booking lead-time patterns and minimum-stay requirements where applicable
- Add-on and ancillary pricing (seat selection, meal add-ons, room upgrades)
- Package-itinerary structure for bundled multi-day travel deals
MakeMyTrip Reviews Dataset
Star ratings tell you something went wrong; written reviews tell you what, whether that’s a flight-booking issue or a hotel-stay complaint.
- Individual reviews with rating, review text, and submission date, for both flights and hotels
- Verified-booking flag and anonymized reviewer identifier
- Aspect-level sentiment: booking accuracy, property or flight quality, customer support, and value for money
- Rating distribution and review-velocity trends by property or route
Where the MakeMyTrip Dataset Runs Deepest
MakeMyTrip’s catalog spans the full breadth of Indian outbound and domestic travel, so our coverage follows that same spread across flights, hotels, and packages.
Domestic Flight Routes
Deepest historical fare depth across India’s highest-volume metro routes.
International Flight Routes
Coverage across major outbound corridors from Indian gateway cities.
Domestic Hotels
Date-level rate tracking across metro, leisure, and pilgrimage destinations.
Holiday Packages
Bundled flight-plus-hotel itineraries tracked as combined-pricing units.
Add-Ons
MakeMyTrip Black member-pricing differentials, festive-season and holiday-peak fare archives, and package-itinerary structure analysis.
How Different Teams Put This Dataset to Work
The same underlying dataset ends up solving fairly different problems depending on who’s using it.
Fare and Rate Benchmarking
Track how competitor OTAs price the same route or property against MakeMyTrip, day by day across the booking window.
Revenue Management Research
Use historical fare curves to understand booking-window pricing patterns and optimal advance-purchase timing.
Hotel Rate-Parity Monitoring
Compare a property’s OTA rate against its direct-booking price to identify parity violations.
Package-Pricing Analysis
Measure how bundled holiday-package pricing compares to the sum of standalone flight and hotel bookings.
AI and LLM Training Data
Use the clean, labeled MakeMyTrip Hotel Dataset and Flight Dataset as training data for travel-recommendation and pricing models.
Sentiment and Quality Research
Mine review-level data to understand what drives satisfaction differences across airlines, properties, and booking channels.
Who Actually Uses the MakeMyTrip Dataset
Airlines, hotel chains, competing travel platforms, market research firms, and investment teams tracking India’s online travel sector.
Airlines & Hotel Chains
Benchmark OTA-channel pricing against direct-booking rates and competing OTAs.
Competing Travel Platforms
Track fare curves and package-pricing strategy against one of India’s largest OTAs.
AI & ML Companies
Source clean, structured travel-pricing data for fare-prediction and recommendation models.
Market Research Firms
Build category reports on India’s online travel sector using multi-year historical depth.
Travel Consulting Firms
Validate pricing and package-strategy recommendations with verified, current data.
Investment & Analyst Teams
Track fare trends and booking-window behavior as alternative-data signals on the travel sector.
What This Dataset Actually Saves You
Manually tracking fares and hotel rates across the full booking window for hundreds of routes and properties isn’t realistic without automation — and a single snapshot won’t tell you anything about how a fare is actually moving.
Hours Back, Not Days
A structured feed replaces manual fare-checking entirely — what used to take a team days to compile is available on a schedule you set.
Forecasts Grounded in Real History
2+ years of fare and rate data lets you separate genuine seasonal demand from routine booking-window price movement.
Understanding the Full Fare Curve
A single-day price check tells you almost nothing about a fare. Tracking movement across the booking window tells you what’s actually happening.
Built Around Your Pipeline, Not Ours
Pick the routes, properties, and cadence that matter to you — delivered as CSV, JSON, API, or Parquet.
How the MakeMyTrip Data Collection Pipeline Actually Works
Here’s the straightforward version of how this gets built, not a marketing summary of it.
Collection Approach
Ethical, rate-limited collection from MakeMyTrip’s publicly visible search-result pages — no credential bypass, no restricted API access.
Validation Before Delivery
Every batch runs through automated schema checks, then a manual spot-check pass before it ships.
Deduplication
Repeat pulls of the same route, property, or date are collapsed into one clean historical record instead of duplicate rows.
Refresh Scheduling
Daily, weekly, or intraday cycles keep fare and rate fields current — fast enough to capture booking-window price movement.
Stable Schema
Field names and structure stay consistent release over release, so your ingestion pipeline doesn’t break on the next refresh.
Compliance
Only publicly available platform data is collected, consistent with standard commercial data practice and platform terms.
This methodology runs on the same Travel Data Scraping infrastructure behind our other travel-platform datasets — it’s a maintained pipeline, not a one-off project.
Delivered However Your Stack Expects It
Access the MakeMyTrip Dataset in flexible formats with delivery options designed for seamless integration into your existing systems, analytics tools, and data workflows.
CSV / Excel
Drop straight into Excel pricing models, Tableau dashboards, or Power BI reports.
JSON / API Feed
Documented schema, ready for direct ingestion into your application backend or data pipeline.
Cloud Storage / Database
Automated delivery to S3, SFTP, Snowflake, BigQuery, or Redshift on whatever cadence you set.
Pick the Plan That Matches Your Scope
Choose flexible MakeMyTrip Dataset pricing plans tailored to your data volume, update frequency, and business requirements.
One-Time Dataset Purchase
From $219
A one-time MakeMyTrip dataset snapshot, delivered right away — no subscription commitment.
What’s included:
- Full point-in-time dataset snapshot
- CSV, JSON, or Parquet delivery
- Filter by route, property, or date range before delivery
Enterprise License
Contact Sales
Full-network, domestic and international coverage with unlimited access and an SLA behind it.
What’s included:
- Unlimited API calls and delivery volume
- Dedicated account manager, 99.5% SLA
- Custom schema design and white-label delivery
A Team That’s Actually Built This Before
WebDataInsights delivers reliable MakeMyTrip Dataset solutions with accurate travel data and actionable insights for market research and competitive intelligence.
Track Record at Scale
Millions of verified records collected and refreshed continuously across major travel-booking platforms — MakeMyTrip is one of several, not a one-off build.
Support That Doesn’t Disappear After Launch
Dedicated account management, SLA-backed delivery, and proactive alerts if a schema ever needs to change.
Compliance-First, By Default
Only publicly accessible platform data is collected — no credential bypass, no restricted-API workarounds.
Custom Builds When You Need Them
Need a field, route, or property set we haven’t listed here? We build custom MakeMyTrip dataset configurations on request.
Questions People Actually Ask Us About the MakeMyTrip Dataset
These come from real conversations with airlines, hotel chains, analysts, and engineering teams evaluating this dataset.
It’s a structured export of MakeMyTrip’s travel-booking data — flight fares, hotel rates and availability, booking terms, pricing across the booking window, and customer reviews — cleaned, deduplicated, and delivered as CSV, JSON, or an API feed.
Because airfare and hotel rates move continuously as departure or check-in approaches, a single snapshot only tells you the price at one moment. Tracking the full booking-window curve is what makes the pricing behavior actually visible.
CSV, Excel (XLS/XLSX), JSON, and API feeds by default. Parquet is available on request for Spark, Databricks, Snowflake, or BigQuery pipelines.
Fares and rates can refresh intraday on enterprise plans, since prices move continuously across the booking window. Listings update daily, and reviews update on a rolling basis.
Yes — tell us the routes, destinations, properties, fields, and refresh cadence you need, and we scope the extract accordingly rather than delivering a generic full export.
Yes, more than two years of historical fare and rate data, useful for understanding seasonal demand patterns and booking-window pricing curves.
Yes. Because hotel rooms sell out per night rather than as a single stock count, the MakeMyTrip Hotel Dataset tracks rate and availability at the date level for every property.
Yes. The Pricing Dataset and Hotel Dataset together make it possible to compare a property’s MakeMyTrip rate against its direct-booking price and other OTAs for the same date.
Yes. Only publicly visible pages on MakeMyTrip’s platform are collected, using rate-limited, ethical methods. We don’t bypass logins or access restricted internal APIs.
A DIY scrape typically returns inconsistent, messy data and is likely to miss booking-window fare movement entirely if it only checks once. This dataset is already normalized, deduplicated, and schema-stable, ready for analysis the same day it arrives.
Yes, bundled flight-plus-hotel packages are tracked as combined-pricing units, separate from standalone flight and hotel bookings, so package economics can be analyzed directly.
Yes — automated delivery to S3, SFTP, Snowflake, BigQuery, or Redshift on whatever schedule you choose.
Get a Real Look at MakeMyTrip’s Travel Pricing Data
4M+ verified records, daily fare and rate refreshes, and 2+ years of historical depth across India’s leading online travel platform — starting at $219.