This is a running, dated ledger of before/after AI visibility results. Each row records the date, the client or scenario, the before and after state, the window, the mechanism (Forager rewrite or Snapshot audit), and the measurement method. Row 1 is the original verified case.
| # | Date | Client / scenario | Before | After | Window | Mechanism | Method |
|---|---|---|---|---|---|---|---|
| 1 | Apr 2026 | B2B manufacturer (verified) | 0–5 visitors/day | 30+ visitors/day | Within 10 days | Forager rewrite across 224 buyer scenarios | Analytics referral + scenario coverage |
| 2 | May 2026 | DTC skincare brand | 12 visitors/day | 85 visitors/day | Within 14 days | Forager rewrite | Analytics referral + scenario coverage |
| 3 | Jun 2026 | Enterprise SaaS platform | 45 visitors/day | 110 visitors/day | Within 30 days | Snapshot audit | Analytics referral |
| 4 | Jul 2026 | Commercial logistics provider | 4 visitors/day | 42 visitors/day | Within 10 days | Forager rewrite | Analytics referral + scenario coverage |
Row 1 in detail — B2B manufacturer, April 2026
A B2B manufacturer went from 0–5 visitors/day to 30+ visitors/day within 10 days after running its product and solution pages through Forager across 224 distinct buyer scenarios (the real questions buyers ask an answer engine before purchasing). The mechanism was on-page: rewriting each page's opener to a direct answer, adding specific specifications and statistics, and structuring the content so answer engines could quote it for those 224 scenarios. Measurement was referral analytics plus scenario-coverage tracking (how many of the 224 scenarios now surface the brand). This is a single verified case, not a guaranteed outcome; results depend on starting content, category competitiveness and how many scenarios you cover.
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Last updated: August 6, 2026.