🎯 The Challenge
The client needed real-time visibility into new discounted airline ticket postings — ticket price, airline, origin city, destination city, and trip type — without having to constantly refresh the source website and copy-paste data into a spreadsheet.
The data had to land in a clean, structured format that supported quick review, filtering, and downstream analysis.
Goal: eliminate manual website checking and data entry, replacing it
with a reliable, automated data feed straight into Google Sheets.
🧩 The Solution
A Make.com pipeline that watches the source site, scrapes new listings as they appear, cleans and normalizes the data, and appends each offer as a structured row in Google Sheets — running on a continuous schedule with no manual intervention.
01
Website monitoring with Make.com
A Make.com scenario periodically checks the target page for new or updated
airline ticket offers. Deduplication logic ensures only fresh entries are
processed — no double-posting, no noise.
02
Web scraping & data extraction
Relevant HTML elements are parsed to pull structured fields out of each listing:
- Airline company name
- Ticket price
- Origin city
- Destination city
- Trip type (round-trip, one-way, etc.)
03
Data cleaning & formatting
Parsed values are cleaned and normalized — price formats unified, whitespace
trimmed, location strings standardized — then mapped into a structured schema
ready for the sheet.
04
Google Sheets integration
Using Make.com's Google Sheets modules and API calls, new records are appended
to a dedicated sheet. Each row represents a single ticket offer with timestamp
and all key attributes — ready for filtering, sorting, and reporting.
🛠 Tools & Stack
Orchestration
Make.com (Integromat) — scheduler, scraper, and data pipeline
Data extraction
Web scraping & HTML parsing for structured field extraction
Data destination
Google Sheets via API — live, structured, analytics-ready
📈 Results & Impact
- Real-time, automated capture of discounted airline ticket data — no more manual copying from the source site.
- Improved data accuracy through consistent parsing and normalization rules applied to every record.
- Time savings — the client stopped monitoring the website manually and got their hours back.
- Instant analysis — data lands directly in Google Sheets, ready for filtering, sorting, charting, and reporting.
🖼 Screenshots
Make.com scenario — the full scrape, clean, and load pipeline
Have a website you need to monitor?
Automated scraping, structured data pipelines, and live Google Sheets feeds — built to
run reliably without manual intervention.