SEO and marketing decision
KillerEMD
A single competent developer can build and operate a useful Exact-Match Domain finder with provider integrations in about a week; the vendor page gives no evidence of irreproducible data or moats, so self-building is realistic.
Visit website↗Built by Herc Magnus, who ships 3 products in this index
Not priced
No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.
$100one-off34 h to build
$70/mo4 h/mo upkeep
No published price to break even against.
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
- Ingest candidate domain/keyword lists, fetch ranking and search-metrics from providers, score domains by ease-to-rank and profitability, present sortable/filterable results
What it still won’t have
- Proprietary aggregated datasets and historical SERP measurements
- Any branded UX polish or onboarding flows
- Managed integrations or commercial support
- Potential paid integrations to large SEO platforms
What remains hard
- Product polish and ongoing maintenance
First-year cost
No published price
KillerEMD does not publish a price we could read, so there is nothing to compare against. What building costs is below.
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 web app (Python + FastAPI backend, Postgres, React frontend) that helps a user find easy-to-rank exact-match domains. In scope: CSV/paste input of candidate domains/keywords; integrations to one SERP provider (or a simple rate-limited scraper) and one keyword-metrics provider; normalized storage of responses; scoring pipeline that flags exact-match domains, computes a difficulty score, and a profitability score (volume*CPC); searchable/sortable UI and CSV export; error handling for API failures, rate limits, and malformed uploads; unit tests for ingestion, scoring, and API handlers. Out of scope: multi-user billing, team collaboration, large-scale distributed scraping, and training proprietary models.
How we checked
How the score was reached
- Build verdict base78
- Evidence score78
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 productKillerEMD - Find Easy To Rank & Profitable Exact Match Domains
Integrity checks
What held up, and what did not.
