SEO and marketing decision
BuildOnDomains
A technical user can build a useful narrower version (live list, scoring, watchlist, digest, Stripe billing) but reproducing BuildOnDomains' large-scale crawl coverage, curated scoring and long-running inventory is multi-week work and costly to match exactly.
Visit website↗$10/mo
$120/yr
Read off the official pricing page.
$100one-off88 h to build
$60/mo6 h/mo upkeep
On cash alone, building overtakes the subscription at 7 seats.
No open-source build does this yet
Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.
What a replacement has to do
- Crawl registrar auction feeds, score/filter domains, display live list with watchlist, send email digests, accept subscriptions.
What it still won’t have
- The product's pre-scanned, large-scale inventory and historical crawl coverage
- Curated business-idea curation and established scoring/tuning done by BuildOnDomains
- Native live syncing across multiple auction platforms and in-app auction status reliability
- Brand, user base and any trust/reputation built by the hosted service
What remains hard
- Infrastructure at scale
We scan 250,000+ expiring domains daily and surface only the select few worth building a business on.
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 7 seats.
Money you would actually spend
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
Build a minimal self-hosted BuildOnDomains clone using: Python (FastAPI) backend, Postgres, Redis (jobs), simple React frontend, and deploy on one VPS (or a small cloud). Core features in scope: (1) scheduled scrapers/pollers to ingest expiring-domain lists from multiple auction sites (scrape or use available feeds), dedupe and store domain records in Postgres; (2) a scoring pipeline that applies heuristics (keyword matching, length, estimated search intent) and assigns one of a few business-model tags; (3) a browsable live list UI with filters, countdown timers, and a star/watchlist per user; (4) background worker to update statuses and send weekly email digests; (5) Stripe subscription checkout for one paid tier and basic account pages. Out of scope: training proprietary ML models, extensive historical archive reconstruction, advanced domain valuation models, native auction bidding. Include error handling for failed scrapes and API rate limits, unit tests for scraper and scoring logic, and an integration test for the end-to-end watchlist + digest flow.
How we checked
How the score was reached
- Partly verdict base52
- Price verified on pricing page+3
- 3/3 assessment runs agreed+4
- Hard moats found in the evidence-3
- Evidence score56
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 · 1
Every page the run actually retrieved.
- official productBuildOnDomains — Expiring Domains with Built-in Business Ideas
Integrity checks
What held up, and what did not.
