how to build $1M B2B lead lists with google search...

google indexes public linkedin profiles, company sites, and job boards.

that makes the search bar a lead database with no seat cost and no export cap.

here is how to work it properly...

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the operators that do the work:

five operators cover almost everything.

• for personal profilessite: restricts results to one domain, meaning site:linkedin.com/in
• quotes force an exact phrase, so "head of growth" stays together
• OR catches variants, meaning "vp sales" OR "head of sales"
• a minus sign strips noise, meaning -jobs -hiring
• intitle: and inurl: target words in the page title or url

combine them and you have a query language that reaches profiles sales navigator hides behind its 2,500 result ceiling.

google applies no equivalent cap to what it returns.

a few practical notes on using them.

put your most specific term first, since google weights early terms HEAVILY.

test each string on a small result set before scaling it,

because one wrong operator returns thousands of irrelevant pages.

and use the date filter under search tools to restrict results to the last month,

which surfaces recent posts and new profiles rather than pages indexed years ago.

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the strings that produce leads:

start from the signal rather than the title.

• "title" "industry" "city" for exact roles in a placesite:linkedin.com/in
• "keyword only your buyer would have" for niche signalssite:linkedin.com/in
• "we're hiring" plus the role your service replaces, for budget and pain together
• "recently funded" or a raise phrase plus your niche, for fresh money
• "team" or "leadership" for named decision makerssite:company-domain.com
• plus a problem phrase, to find people publicly discussing itsite:linkedin.com/posts

the hiring string is the sharpest of them.

a company posting for the exact role you replace has approved budget and an active problem in one signal.

the posts string is the one basically nobody runs lmao.

someone writing publicly about a problem you solve has already articulated the pain themselves,

so the opener writes itself from their OWN WORDS.

point the same strings at job boards and company pages, not just profiles,

so you find the account first and the person second.

save every string that works, since you reuse them across campaigns and only swap the niche.

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scaling past manual searching:

running these by hand caps you at a few hundred leads.

to get real volume:

• run each string across every city, region, and industry variant in your market
• use a scraper to pull result pages into a sheet rather than copying by hand
• set google alerts on your trigger phrases so new matches arrive automatically
• run the whole set on a schedule, since hiring posts and funding announcements appear weekly

one string across 20 cities and 5 industry variants is 100 searches from one piece of work.

that is where the volume comes from.

two constraints to plan around.

google rate limits aggressive automated querying,

so pace the scraping and rotate rather than hammering it in one session.

and the results are pages rather than structured records,

so budget time for the cleanup step that turns urls into a usable sheet.

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turning results into a list worth sending to:

a search returns pages, and a lead list needs STRUCTURE.

the pipeline:

• pull results into one sheet with the url, the company, and the string that found it
• enrich each row with a model that reads the profile and company
• qualify against your icp, keeping a written reason on every drop
• verify every email before it touches a domain
• dedupe against everyone already contacted

the string column earns the money.

it records why each lead surfaced,

meaning the hiring post or the funding phrase, and that becomes the first line of the message.

read the drop reasons in bulk.

when a few thousand records get cut for the same cause,

your icp definition was wrong before your copy was.

then track which strings produce booked meetings rather than which produce the most leads.

a string returning 200 leads and two meetings beats one returning 5,000 leads and none,

and only the meeting number tells you which is which.

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- din

also, DM me "COLD" if you want us to run our linkedin + email outbound system for your B2B business...

(must be making over $10k/month)

we've done this for over 140 companies across 30 industries

(or just book a call @ calendly.com/eaglerev/eaglerev-strategy-call)