CRM and sales decision

LeadsByLocation

A capable developer can assemble a useful subset (search + scoring + contact reveal + CSV) within a multi-week effort using existing OSS components, but matching the hosted product's polish, scale, and ongoing curated dataset is non-trivial.

Visit website
You pay

$9/mo

$108/yr

Read off the official pricing page.

You’d pay instead

$100one-off56 h to build

$90/mo6 h/mo upkeep

On cash alone, building overtakes the subscription at 11 seats.

Open-source builds that already do this

Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need - the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship. All LeadsByLocation alternatives, with the arithmetic →

What a replacement has to do

  • Search a location (Google Places), score websites (PageSpeed), reveal contact details (crawl/extract), export leads and track outreach.

What it still won’t have

  • Access to a maintained, curated index and UI polish
  • White-label PDF report generation and branding
  • The convenience of integrated outreach tracking and prebuilt filters for many niches
  • Ongoing data freshness, scale, and support

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 11 seats.

Paid seatsseats

Money you would actually spend

Keep paying
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Subscription price × seats × 12

Build it
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AI build —APIs + hosting —

Time you would spend

—

—

What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a minimal LeadsByLocation replacement using Node.js (Nest or Express) + Postgres + React. Core features in scope: (1) location+category search using Google Places API, (2) fetch Google PageSpeed API scores and a simple site health check, (3) crawl lead homepage to extract emails/phones (with rate-limiting and polite headers), (4) store leads and search groups in Postgres, (5) UI for search, reveal-contact action that decrements credits, CSV export, and a simple pipeline (New / Contacted / Closed). Out of scope: large-scale data harvesting, multi-city preindexing, white-label PDF generation, and advanced email verification. Include Stripe billing for monthly plans and credit allotments, input validation, error handling, retry logic for API calls, unit tests for backend services, and end-to-end tests for the search-and-reveal flow. Provide deployment scripts for a single Heroku/DigitalOcean droplet and a small docs README for operators.
How we checked5 sources · 2/3 runs agreed · evidence score 63

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 5 cited sources+3
  • Price verified on pricing page+3
  • Evidence score63

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.

How scoring works →

Cited sources · 5

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ Price read off the page! 2 of 3 runs agreed; the verdict is the majority✓ Citations limited to fetched pages! 1 moat recorded