Everyone wants to scrape Google for leads. It's the world's largest database, filled with potential customers for any niche. There’s just one massive problem: Google hates being scraped.

You've probably seen this yourself. You run a broad search like "marketing agencies in USA" and Google tells you there are "About 2,450,000 results." You think you've hit gold. But as you click through the pages, you hit a wall. Around page 25, or 250 results, Google just... stops.

This isn't a bug. It's a deliberate feature to stop people like us from exporting their entire index. This 250-result limit makes scraping Google for broad topics almost useless for building a B2B lead list.

So, how do you get the thousands of leads you know are in there?

The secret is to stop trying to scrape deep and start scraping wide. Instead of one big query, you use hundreds of small, specific ones. Datablist's Start with a Google Query source is the tool that makes this strategy simple and scalable.

I'll show you exactly how it works.

Scraping Wide, Not Deep

If Google won't let you go deep on one query, the answer is to go wide with many queries.

Instead of one search for "Lawyers in France" (250 results), you run 100 different searches:

  • "lawyer paris" (gets 250 results)
  • "lawyer nantes" (gets 250 results)
  • "lawyer lyon" (gets 250 results)
  • "lawyer marseille" (gets 250 results)
  • ...and so on for 100 cities.

Suddenly, your potential pool of 250 results has turned into 25,000 (100 cities x 250 results).

This multi-query strategy is the same principle used for scraping Google Maps effectively, where you search by ZIP code instead of a whole city. By breaking one big problem into hundreds of small ones, you bypass Google's limits and get exponentially more data.

The only problem? Manually running hundreds of searches is a nightmare.

How to Generate Thousands of Google Queries (Fast)

You don't have to type out 500 search queries by hand. You can use an LLM like ChatGPT, Claude, or Gemini to do it for you in seconds.

Here’s a simple prompt template:

"I need to create a list of Google search queries. Please give me a list of the 100 largest cities in Germany.

Now, create a new list by adding the keyword 'Software Agency' in front of each city name. The final list should only contain the queries, one per line. For example: Software Agency Berlin Software Agency Hamburg"

Generate Queries with ChatGPT
Generate Queries with ChatGPT

In 30 seconds, you'll have a list of 100 highly specific queries ready to be pasted into Datablist.

You can get creative with your query generation. Combine industries, job titles, technologies, and locations to create thousands of permutations.

How to Scrape Google Results with Datablist (Step-by-Step)

This is where it all comes together. Datablist's "Start with a Google Query" source was built specifically for this multi-query strategy.

Step 1: Create a New Collection

First, create a new collection in Datablist. This is where your scraped results will be stored.

Step 2: Select the "Start with a Google Query" Source

From your new collection, click "Import" and select "Start with a Google Query" from the list of data sources.

Google Queries Data Source
Google Queries Data Source

Step 3: Paste Your Query List

This is the magic step. Take the list of 100 (or 1,000) queries you generated with your LLM and paste them directly into the "Search Queries" box, with one query per line.

Data Source
Data Source

Step 4: Configure Your Search Settings

Now, you can fine-tune your scrape:

  • Search Country Choose the Google domain to search from (e.g., google.de for Germany, google.fr for France). This is crucial for getting local results.
  • Search Language Set the language for the search interface to ensure you get results in the correct language.
  • Time Period You can filter results from the "Past 24 hours," "Past Week," "Past Month," or "Past Year." This is perfect for finding fresh leads or recent news.
  • Limit Per Query Set a maximum number of results to pull for each query. You can set this to 50, 100, or the full 250.

Step 5: Run the Import

Click "Run Import." Datablist will now work through your entire list of queries, one by one, and scrape the results for each. It will run in the background, so you can grab a coffee while it builds your lead list.

Step 6: Review Your Results

Once finished, your collection will be filled with clean, structured data. For every result, you get:

  • Result Title: The page title.
  • Result Snippet: The short description from Google.
  • Result URL: The direct link to the page.
  • Result Position: The ranking (1, 2, 3, etc.) on the Google results page.
  • Search Query: The exact query that found this result, so you always know which search was successful.

The "Hidden" Feature: Automatic Deduplication

Here's something you might not think about until it's a problem: Google search results are messy. A URL that appears as result #5 for "lawyer paris" might also show up as result #12 for "corporate lawyer paris."

If you just scrape both queries, you'll have duplicates in your list.

Datablist automatically handles this. As it scrapes, it identifies results that have already been added (even from different queries) and automatically deduplicates them. This ensures the final list you get is clean and unique, saving you a data cleaning headache later.

Let's Talk Cost: 4,000 Results for $1

This strategy is not only effective, but it's also incredibly cheap.

  • Scraping 10 Google results costs 2.5 credits.
  • A $20 top-up in Datablist gives you 20,000 credits.

Let's do the math:

  • $1 (which is 1,000 credits) gets you 4,000 Google search results.
  • Your $20 credit pack gets you 80,000 results.

For the price of a couple of coffees, you can generate a massive, targeted lead list that would have taken days or weeks to build manually.

What to Do With Your Scraped Data

Scraping the results is just the first step. Now you have a list of high-intent URLs. The real value comes from what you do next.

  1. Enrich Your List: You have the Result URL. Use this as the input for other Datablist enrichments. You can find their LinkedIn Company Page URL, and then find verified email addresses.
  2. Qualify Leads: Use the Result Snippet and Title to quickly qualify leads. You can even feed this text into an AI model (like ChatGPT or Claude) to automatically categorize them.
  3. Find Technology Users: Create queries like "powered by Shopify" or "running on WooCommerce" to build highly targeted lists of e-commerce stores. (Check our guides for finding Shopify stores or WooCommerce stores).
  4. Competitor & Market Research: Track mentions of your competitors or industry keywords over time. Set the "Time Period" to "Past 24 hours" and run it daily to get a live feed of news and mentions.

Conclusion

Stop fighting Google's 250-result limit. You can't win by scraping one query deeply. The key is to scrape wide by using hundreds of specific, targeted queries.

Datablist's "Start with a Google Query" source is the perfect tool for this strategy. It lets you automate the entire process, handles deduplication, and delivers a clean, structured list of thousands of leads for an incredibly low cost.

FAQ

What is the Google 250 result limit? Google limits the number of search results it displays to any user (or scraper) to around 250, regardless of how many millions of results it claims to have found.

Is it legal to scrape Google? Scraping publicly available information from Google is generally legal for purposes like market research and lead generation. However, you must always respect Google's terms of service and use the data ethically. Datablist handles scraping responsibly.

How many queries can I run at once? You can paste thousands of queries into the Datablist source. The tool will work through them sequentially, building your list as it goes.

How is this different from a normal Google search? A normal search is manual and stops at 250 results. The Datablist Google Query source automates hundreds of searches at once, bypasses the 250-result limit by using multiple queries, deduplicates the findings, and delivers the data in a clean, structured spreadsheet.

What data does the Google Query scraper return? It returns the Result Title, Result Snippet (description), Result URL (the direct link), Result Position (ranking), and the original Search Query that found the result.

Use Cases

  • Sales Teams: Build targeted lead lists by scraping for industries and locations (e.g., "plumbers in new york," "dentists in chicago").
  • Marketing Agencies: Find potential clients by searching for "marketing agency needed" or by finding companies using specific technologies (e.g., "powered by HubSpot").
  • Recruiters: Scrape for "we are hiring [Job Title]" combined with specific city names to find companies that are actively growing.
  • E-commerce Agencies: Create lists of stores using specific platforms by searching for "powered by Shopify" or "powered by WooCommerce".
  • Market Researchers: Track brand mentions, competitor news, or industry trends by running queries with the "Time Period" filter set to the last day or week.