Scrape Google with AI to Enrich Your B2B Prospects: The Tutorial
By Romain QUECHON · Published on February 23, 2024 · Updated on September 30, 2026
Scraping Google means automatically querying the search engine to retrieve structured results, then cleaning and sorting them with AI. In B2B prospecting, it is mainly used to enrich a list by finding a website, a LinkedIn profile or recent company news.
This tutorial shows you how to build a bot that runs any Google search, retrieves results in real time and has AI sort them based on your business needs.
6 use cases for B2B prospecting
| You have | The bot retrieves |
|---|---|
| A list of company names | Their websites and social media accounts |
| A prospect’s first and last name | Their LinkedIn profile, a starting point for their role, email address and phone number |
| A company to monitor | Its latest news in real time |
| An industry and a location | A list of companies from Google Maps |
| A topic | Google search trends |
| An image | Google Lens results |
AI then cleans and sorts the results by keeping the right website, removing namesakes and categorizing companies based on your criteria.
Video tutorial
The setup, step by step:
3 APIs for querying Google
All three return Google search results as usable data that you can connect to an automation workflow such as Make.
Connect the bot to your prospecting workflow
The bot becomes useful when it fits into a workflow: a list of target accounts goes in, enriched data goes to your database, then scoring determines whom to contact. See AI lead scoring on LinkedIn.
The Allbound AI platform performs this enrichment in real time for every lead, with no bot to maintain. View the implementation program.
Method limitations
This tutorial dates from 2024, so API plans and settings may have changed. Google results are not always accurate, due to namesakes or outdated pages. AI classification reduces errors but does not eliminate them.
Finally, make sure your use complies with the terms of the services involved and personal data regulations.
5 tips to apply this week
- Start with one use case. Finding the websites for a list of accounts is the fastest way to generate a return.
- Add the company name to a prospect search to reduce namesake matches.
- Ask AI for structured output, with one column per data point, so it can feed your database directly.
- Schedule news monitoring for your target accounts to identify the right moment.
- Manually review a sample before running the bot across the entire list.
Enrichment is only one step. It becomes more valuable when combined with signals such as funding rounds, within an Allbound strategy.
Frequently asked questions about scraping Google with AI
Why scrape Google for B2B prospecting?
To enrich a prospect list with current information: a company website and social media accounts, a contact’s LinkedIn profile, news about a target account or a list of companies from Google Maps.
Which APIs can you use to query Google automatically?
This tutorial presents three options that return Google search results as usable data: SerpAPI, Piloterr’s Google Search module and Autom.
What does AI do when scraping Google?
It cleans and sorts raw results based on your needs: keeping the right website, removing namesakes, categorizing companies based on your criteria and producing structured output for your database.
What prospect data can you find through Google?
Using a first name, last name and company, the bot generally finds the LinkedIn profile, which then provides a starting point for the person’s role, email address and phone number.
Romain QUECHON, founder of Allbound AI (formerly The World of AI). More than 60 clients supported, with 10 to 15 meetings generated per month on average for implementation program clients. See Romain's background · Follow me on LinkedIn