How to scrape flights data from Kayak using the Minexa.ai extension
- Minexa.ai
- 2 days ago
- 2 min read
Flight route data from Kayak is genuinely useful for travel research, price monitoring, and competitive analysis. This guide walks through exactly how to extract it using the Minexa.ai Chrome extension, no code required.
Watch the full tutorial first
Before going through the steps below, watch the video walkthrough. It covers the entire extraction from start to export in a single session.
Checkpoint 1: open Minexa.ai and navigate to Kayak
Install the Minexa.ai Chrome extension, then open the extension home page. From there, navigate to kayak.com/flights in your browser. The page loads the full list of featured destination cards with route links.
Once the Kayak flights page has fully loaded, you are ready to open the extension popup.
Checkpoint 2: confirm the page and review pagination
Click the extension icon. Minexa.ai detects the page and shows a confirmation prompt. Click I'm on the right page to proceed.
Minexa.ai then shows the pagination options it detected on the page. Review the selection and click Continue.
Checkpoint 3: choose list-only or list with detail pages
After confirming pagination, Minexa.ai asks whether you want to scrape the list only, or follow each destination link and extract detail page data as well. For a route dataset, the list view already contains the key fields. Select your preference and continue.
Checkpoint 4: select simple or advanced mode, then highlight the container
Choose simple scraping mode for a standard extraction. Minexa.ai then automatically highlights the repeating data container on the page. Confirm the selection and click Create scraper.
Checkpoint 5: review extracted data points
Minexa.ai surfaces all detected fields. Use the next and previous navigation to browse every column it found. Here is a sample of what the extracted data looks like across three destination rows:
[
{
"destination": "New York Flights",
"flight_details": "Flight Fort Lauderdale - New York (FLL - NYC)",
"flight_route_href": "/flight-routes/Palm-Beach-Intl-PBI/New-York-NYC",
"button_aria_label": "View more deals for New York Flights",
"links_div_ids": "links-content-10"
},
{
"destination": "Miami Flights",
"flight_details": "Flight Dallas - Miami (DFW - MIA)",
"flight_route_href": "/flight-routes/Cleveland-Hopkins-Intl-CLE/Miami-MIA",
"button_aria_label": "View more deals for Miami Flights",
"links_div_ids": "links-content-11"
},
{
"destination": "Rome Flights",
"flight_details": "Flight San Francisco - Rome (SFO - ROM)",
"flight_route_href": "/flight-routes/Los-Angeles-LAX/Rome-ROM",
"button_aria_label": "View more deals for Rome Flights",
"links_div_ids": "links-content-12"
}
]Each row captures the destination label, a plain-text route summary with IATA codes, multiple alternative origin route paths, and the DOM section identifier for that card.
Checkpoint 6: run the job and export
The scraper is now saved. Find it at the top of your scraping jobs list and click Run. Once the job completes, export to Excel or JSON directly from the results table.
You can also set up a recurring schedule so the job runs automatically and captures any changes to the featured routes over time.
Ready to build your first flight dataset? Install the Minexa.ai extension and run this exact workflow in one session.
For more on scraping travel and hospitality data, see how to scrape events data from Eventbrite using Minexa.ai.
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