A Website Data Extraction Checklist for Competitor Research

A website data extraction checklist is the short list of fields to collect from every page you research — so two weeks later your spreadsheet is complete, comparable and traceable instead of a pile of half-remembered screenshots. The template below works for company research, competitor analysis, lead enrichment and academic work; it is the same checklist our team runs when doing product research.

The checklist

Copy this block into your notes and run it on every page you visit:

[ ] Source URL captured
[ ] Capture date noted
[ ] Company / author / publisher name
[ ] Core facts as structured rows (prices, plans, specs, rankings)
[ ] Text content saved (article, description, terms)
[ ] Full-page screenshot for visual record
[ ] Key claims copied verbatim with location noted
[ ] Everything routed into ONE database with mapped fields

Step by step

1. Capture the source URL and date first

Every fact you extract is only as useful as its provenance. If your tool attaches the source link and capture date automatically — Uniclip does — let it; if not, paste the URL manually before doing anything else. A "price was $49" without a date and a source is noise.

2. Extract structured data as rows

Pricing tables, plan comparisons, product grids, team lists — capture them as structured rows, not pasted text. This is where most checklists go wrong: pasting a table as text loses the columns that make it comparable. Use a table capture tool so rows arrive with headers intact, straight to CSV or a Notion database.

3. Save the prose around the numbers

Numbers need context: the paragraph above the pricing table, the trial terms, the FAQ. Clip the page text — clean Markdown survives being searched later; screenshots don't. The web clipper workflow keeps text, tables and visuals from the same page together.

4. Screenshot what layout communicates

Some intelligence is visual: how a competitor tiers their plans, what they feature first, what their onboarding looks like. One full-page screenshot per visit is usually enough.

5. Centralize in one place, with fields

The checklist's quiet killer step: everything lands in one database with consistent fields (company, URL, date, price, notes, screenshot). Scattered exports don't compound; a mapped database does. If you're capturing many pages, batch capture queues them and saves in one pass.

Checklist variants for common jobs

• Competitor pricing: structured pricing rows + screenshot + trial terms field + quarterly re-capture.
• Lead / company enrichment: company name, public contact info, team page rows, "about" text, news mentions — with source links for every field.
• Job description analysis: capture each posting's title, requirements and salary band as rows; the pattern across twenty postings is the insight.
• News & media research: publication name, date, author and key quotes per article — clipping handles the citation shape automatically.

Tools that run the checklist

FAQ

How many fields should the checklist have? Fewer than you think: source, date, and three to five fields you actually compare. Long checklists don't get filled in; short ones get reused.

How do I extract data from a webpage without coding? A browser extension that reads the page structure — point at the table or list, export the rows. The web scraper guide covers the workflow; code is only needed for scale.

What about pages behind a login? If you can view the page, an in-browser extension can capture what you see. Respect the site's terms of service about what you do with the data — especially for anything confidential.