Local Business TAM from Directories

The play in six steps

1. 01

   Step 1: Size the market before paying for it

   Local businesses are thin or missing in B2B databases, but most directories will tell you exactly how many listings exist before you scrape a single page.

   • Read the result total off one Browserbase fetch per geography and category. It is free and exact.
   • Run a Google Maps pilot on Apify at 30 places per search term to see coverage and noise.
     • If every term hits 30, there is more supply. If terms come back short, the full run will stop early.
   • Multiply the per-term cap by the number of terms. The cap is per term, not a total.
   • Agree a hard dollar budget before the full run.
2. 02

   Step 2: Scrape Google Maps

   Google Maps has the widest coverage of local businesses, with phone, website and address on most rows.

   • Use the Apify Google Maps actor with two or three phrasings of each search term.
   • Search a whole state or region, then exclude cities afterwards rather than in the query.
   • Pass a max spend so Apify stops charging at the budget.
   • Filter on category: broad terms pull in neighbouring trades.
   • Remember Maps lists locations, not companies. A business with five offices appears five times.
3. 03

   Step 3: Add the industry directories

   Trade and professional directories add businesses Maps misses, plus the category detail Maps does not hold.

   • Fetch result pages with Browserbase. Server-rendered listings need no browser session or LLM.
   • Find the parameter that really moves the page. Fetch page 1 and page 2 and confirm they differ before crawling.
   • Category labels are exact strings. Test each one on a single fetch first.
   • Make the crawl resumable on geography, category and offset, with retries.
   • Expect contact data only on paid listings. Free listings usually carry name and address only.
4. 04

   Step 4: De-duplicate across sources and geographies

   The same business turns up in several sources, several categories and several neighbouring cities.

   • Match on website domain first, then normalised name plus street address.
   • Blank directory and link-in-bio domains before matching on domain, or unrelated businesses collapse into one.
   • Keep the richest copy of each record and a set of every category and geography it appeared under.
   • Count rows with a CSV parser, not line counts: descriptions carry newlines.
5. 05

   Step 5: Enrich website, owner and email

   Directories rarely publish emails, so the contact layer is built downstream in Clay.

   • Resolve a website for rows that came in with a name and address only.
   • Claude reads the about or team page to name the owner or principal.
   • Run the email waterfall in Clay: Prospeo, then Findymail on the misses.
   • Verify every address with BounceBan before it is used.
6. 06

   Step 6: Tier and load

   A local TAM is large and uneven, so tiers decide where effort goes.

   • Score on what the sources hold: number of locations, review count and rating, website quality, category fit.
   • Tier 1 gets a call and an email. Lower tiers go to email only.
   • Load companies and contacts into HubSpot, then send through Instantly.
   • Keep the raw scrape so filters can be re-run for free later.