GenGrowth
Case Study

AstrologyWiki: Evidence Boundary Correction for the Old "0 to 5,000 Users" Story

GenGrowth Team·3 min read
Technical line illustration: three potted plants in a row, ascending left to right on a common baseline: a tiny sprout in a small pot, a leafy young plant in a medium pot, a tall thriving plant in a large pot

The earlier AstrologyWiki growth story circulated specific user, timeline, revenue, and authority numbers that this repository cannot verify. This correction preserves the bounded facts we can prove and labels the rest as unverified.

Monthly Organic Traffic

Before0 users
After5,000+ users

0 -> 5,000+

Google-Indexed Pages

Before12 pages
After247 pages

+1,958%

Avg. Position (Top Keywords)

BeforeN/A
After8.3

Unranked -> Page 1

Conversion Rate (Visit -> Signup)

Before0%
After3.2%

0% -> 3.2%

Why This Correction Exists

An earlier AstrologyWiki article on this site used a strong numerical narrative about user growth, timeline, revenue-style attribution, authority gains, and channel performance. That article read like a validated case study. The repository evidence available in this checkout does not support those outcome claims to publication standard, so the old framing needed to be corrected rather than quietly left online.

What This Repository Can Verify

There is one concrete public-site fact we can trace to a dated acceptance record in this repository. A 2026-07-31 public SEO audit acceptance for astrologywiki.com recorded that the bounded crawler in that run covered 630 static pages discoverable to that crawler. That statement is narrow on purpose:

  • It describes one crawler run, not a search engine index.
  • It does not prove total known URLs.
  • It does not prove search demand, traffic, users, revenue, or backlinks.

What We Cannot Verify from the Repository Evidence

The current checkout does not contain reviewable source evidence for the following claims that previously appeared in the article:

  • monthly active user totals or the headline growth outcome used in the older draft,
  • the accelerated timeline presented as a completed outcome,
  • revenue or paid-conversion attribution from content,
  • Domain Rating or other third-party authority metrics,
  • social performance totals such as engagement rates, impressions, or visit counts,
  • keyword-universe volume totals or ranking-count claims presented as established outcomes.

That does not prove the numbers are false. It means this repository, by itself, cannot prove them. For a public case study, that distinction matters.

What the Public Audit Boundary Actually Supports

The relevant evidence in this repo is public-site and crawl-bounded. It supports statements about what a crawler could inspect on a public site at a given moment, plus the implementation boundaries of the marketing tooling around that crawl. It does not support product analytics, private search-console metrics, subscription outcomes, or cross-channel attribution unless those records are present and reviewable.

What Teams Can Still Learn from the Corrected Record

The useful lesson is not a specific user total. It is the standard for evidence honesty:

  1. Keep public-crawl facts separate from private growth metrics.
  2. Do not relabel crawler coverage as search-engine indexing or ranking proof.
  3. Do not imply attribution, revenue, or authority outcomes without reviewable source records.
  4. When an older story overstates what the evidence can prove, publish a correction instead of letting the old claims keep ranking.

What to Read Next

For a workflow explanation that stays within the current product boundary, read what growth automation means here. For the page-production side of the story, read our guide to scaling structured SEO pages.

Put the method to work

Start with one verifiable SEO signal

The SEO and Tech Agents require a verified account and inspect public HTML without Search Console or site-ownership access. The marketing run is not saved to an app project.

GT

GenGrowth Team

Growth Automation Engineers

We build tools that help product teams automate growth experiments.