How to Extract a List from Any Website to Excel (3 Methods, 2026)

You want to take a list of items off a website and get it into Excel. Could be product prices, business directory listings, job postings, search results — anything. Manual copy-paste is out.

There are three real ways to do this in 2026:

1. Excel's built-in Power Query (works for clean HTML tables)
2. Google Sheets IMPORTHTML formula (free, no setup)
3. A web scraper Chrome extension (works for everything else)

This post compares all three with examples, then tells you which to reach for first.

Quick comparison

Method	Best for	Cost	Setup	Works on modern JS sites?
Excel Power Query	Sites with proper <table> tags	Excel license	Built into Excel	Limited
Google Sheets IMPORTHTML	Quick one-off table imports	Free	None	Limited
Chrome extension (e.g. NCWS)	Any website, including JS-rendered, grids, lists	Free	30-second install	Yes

Method 1 — Excel Power Query (the "official" Microsoft way)

If the website's data lives in a real HTML <table> element — think Wikipedia tables, Yahoo Finance summary tables, simple data dumps — Power Query handles it natively.

Steps

1. Open Excel and create a new workbook.
2. Go to Data → Get Data → From Other Sources → From Web.
3. Paste the URL of the page.
4. Excel parses the page and lists every <table> it finds in a navigator.
5. Pick the table(s) you want, click Load.
6. The data lands in a sheet, refreshable any time via Data → Refresh All.

Where Power Query fails

It only sees what's in the initial HTML response. So:

• Modern JS sites (Amazon search, LinkedIn results, Google Maps): the data is rendered after the page loads by JavaScript. Power Query never sees it.
• Login-protected pages: you can authenticate, but it's fiddly and breaks often.
• Infinite scroll & pagination: Power Query loads one URL. It doesn't follow "Next" links or scroll.
• <div>-based lists, not <table>: most modern sites use <div> grids. Power Query ignores them.

So Power Query is great for ~10% of "extract a list from a website to Excel" jobs. The other 90% need a different tool.

Method 2 — Google Sheets IMPORTHTML

If you live in Google Sheets, there's a built-in formula that pulls tables and lists from a URL:

=IMPORTHTML("https://example.com/page", "table", 1)
=IMPORTHTML("https://example.com/page", "list", 1)

The third argument is the index — 1 for the first table on the page, 2 for the second, and so on.

Where it works

Same constraint as Power Query: it only sees the raw HTML response. Wikipedia, simple government data pages, basic blogs.

Where it fails

• Any JavaScript-rendered content
• Anything behind login
• Anything that paginates or scrolls
• Limited to 50 IMPORT formulas per spreadsheet — at scale it's a non-starter

If IMPORTHTML returns #N/A or an empty result, the page is JS-rendered and you need a different approach.

Method 3 — A web scraper Chrome extension (works on everything)

A web scraper Chrome extension runs inside your already-rendered browser. It sees the page exactly as you do — including everything JavaScript drew on the screen. That's why it can scrape sites that Power Query and IMPORTHTML can't touch.

The free No Code Web Scraper Chrome extension is an example. Here's how the workflow goes for a generic "list to Excel" job:

1. Install the extension from the Chrome Web Store. No signup.
2. Navigate to the page with the list (Amazon search, Yelp directory, LinkedIn results, whatever).
3. Open the side panel.
4. Click Auto Detect — the extension finds the list of items.
5. Click each field you want as a column.
6. Click Export → Excel.

You get a .xlsx file with every row visible on the page. Combine with multi-page scraping and you have every row across hundreds of pages.

Concrete examples

• Amazon products to Excel: see the Amazon Product Scraper tool page.
• Google Maps businesses to Excel: see the Google Maps Scraper tool page.
• Yelp reviews to Excel: see the Yelp Scraper tool page.
• Indeed jobs to Excel: see the Indeed Job Scraper tool page.

Why this method wins for most jobs

• Works on every public site, including JS-heavy ones
• No code, no API keys, no proxy setup
• Pagination + infinite scroll handled automatically
• Free
• Data stays local in your browser — no cloud upload

Which method should you use?

Use this decision tree:

1. Is the data inside a real <table> tag with no JavaScript? Power Query or IMPORTHTML is fine. Stick with what you know.
2. Anything else? Use a free web scraper Chrome extension. It's the only method that handles modern sites without code.

For 95% of real-world "extract list to Excel" tasks, the answer is the Chrome extension.

FAQs

Can I extract a list from a website to Excel without coding?

Yes. Either use Excel's built-in Power Query (for sites with HTML tables) or a free web scraper Chrome extension (works on every site). Neither requires writing code.

How do I extract a table from a website to Excel for free?

Three free options:

1. Excel Power Query (Data → From Web) for tables in static HTML
2. Google Sheets IMPORTHTML for the same case
3. A free Chrome extension for JS-rendered content

Why does Power Query return empty data?

The page is JavaScript-rendered. Power Query only sees the initial HTML — not what JavaScript drew on the screen afterwards. Use a Chrome extension instead.

Can I extract a list from Amazon, LinkedIn, or Google Maps to Excel?

Not reliably with Power Query — those sites are fully JS-rendered. A No Code Web Scraper Chrome extension handles all three. Site-specific guides: Amazon, LinkedIn, Google Maps.

Is web scraping legal?

Extracting publicly visible data is generally legal. What matters is how you use the data — respect each site's terms of service, GDPR/CCPA for personal data, and don't bulk-redistribute someone else's content.

TL;DR

• Power Query / IMPORTHTML: great for static HTML tables, useless for everything else.
• A free web scraper Chrome extension handles modern sites — no code, no setup.
• For most "extract a list from a website to Excel" jobs, the extension is faster, easier, and works.

Install the free Chrome extension and try it on the page you've been struggling with.