Analytics and monitoring decision

SpyFu

A limited competitor-research tool for a small set of domains is realistic for a single developer, but SpyFu's scale, freshness, and broad historical index are durable and impractical to replicate.

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You pay

$39/mo

$468/yr

Per seat. Read off the official pricing page.

You’d pay instead

$50one-off30 h to build

$50/mo8 h/mo upkeep

On cash alone, building overtakes the subscription at 2 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 SpyFu alternatives, with the arithmetic →

What a replacement has to do

  • Search a competitor domain -> retrieve their paid & organic keywords and ad history -> store results -> present searchable results and allow CSV export

What it still won’t have

  • Massive historical index (trillions of results) and cross-domain coverage
  • High-frequency live updates and global coverage
  • Enterprise features: white-labeling, unlimited exports, multi-user team controls
  • Included official SpyFu API credits, prebuilt reports, and proprietary data quality

What remains hard

  • Proprietary data7.2 Trillion search results indexed
  • Infrastructure at scaleLive Data Updated every 15s
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 2 seats.

Paid seatsseats

Money you would actually spend

Keep paying
—

Subscription price × seats × 12

Build it
—

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 lightweight competitor keyword-research service using Node.js (Express), React, and Postgres. Scope: 1) implement an HTTP integration to a paid SERP/keyword API (configurable API key) to fetch paid & organic keywords and ad-history for one domain; 2) normalize and store results in Postgres, including timestamp and source; 3) React UI to search by domain, show results table, keyword detail, and CSV export; 4) a scheduler to run weekly rank checks for tracked domains; 5) single-user auth and account page. Out of scope: large-scale crawling/indexing, historical multi-year archives, multi-seat billing, white-labeling, advanced AI features. Include error handling, retries for failed API calls, basic test coverage (unit tests for data import and API routes), and a Dockerfile for local deployment.
How we checked3 sources · 3/3 runs agreed · evidence score 61

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 3 cited sources+3
  • Price verified on pricing page+3
  • 3/3 assessment runs agreed+4
  • Hard moats found in the evidence-6
  • Evidence score61

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 · 3

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ Price read off the page✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 2 moats quoted from the page