Case studies

Last week we wrote about small, obscure TAMs that can still be very profitable. This week, client conversations pushed it even further: micro TAMs, markets where the total number of target accounts is under 100.

Last week we wrote about small, obscure TAMs that can still be very profitable. This week, client conversations pushed it even further: micro TAMs, markets where the total number of target accounts is under 100.

George Rekouts

CEO and Founder

Last week we wrote about small, obscure TAMs that can still be very profitable.
This week, client conversations pushed it even further: micro TAMs, markets where the total number of target accounts is under 100.

In these markets, every single company matters:

• Hiring a top exec for a heavy civil infrastructure construction company. Your target market is around 60 companies in four states. Miss a few, and you’re missing your entire viable pool.

• Looking for top YouTube sports influencers with millions of followers. There just aren’t that many. Most are booked months ahead. Not finding one that is open means missing Q4 and waiting until next year.

• Selling ERP to power line component distributors. There are 97 companies in the US using a competitor system. Close a couple, and that’s millions in revenue. Miss a few, and you shrink the whole TAM.

• Sponsoring healthcare conferences. There are only 74 in six months. Miss the right ones, and you wait a year to get in. Missed revenue on huge R&D costs.

• Responding to a private help message asking for all pancreatic oncology surgical centers. There’s no directory. Just 58 of them in the US. Each one matters.

And here’s the real problem. What are your options today outside of DiscoLike? I would say none.

• Scrape something with Clay to build a list, but what?
• Go through pages of Google search results?
• Download a 6K hospital list from cms(.)gov with no domain names?
• Get a list from Apollo that is LinkedIn based and miss half the companies?
• Work the unworkable ZoomInfo search?

None of those get you close enough. And when the TAM is this small, every missing record hurts.

The magic pattern behind the solution is the same one that:

• Stripe uses to find fraud
• Claude uses to write better code
• DiscoLike uses to find perfect-fit companies

Dense vector search → contextual filtering → LLM prompt + learn from results (RL) and repeat until the results are the very perfect list you are looking for, complete coverage in “impossible” verticals.

If each discovered company matters in your search, you know where to find us.

Build your best GTM list.
Start using DiscoLike today.

Build your best GTM list.
Start using DiscoLike today.

Build your best GTM list.
Start using DiscoLike today.

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2555 Flores St. Suite #425
San Mateo, CA 94403

Copyright © DiscoLike. All rights reserved.

2555 Flores St. Suite #425
San Mateo, CA 94403

Copyright © DiscoLike.
All rights reserved.