10
Buyer prompts tracked from day one
Self-study
We run Anovox on Anovox. Here's what the first 30 days look like.
Before asking anyone to trust the dashboard, we pointed it at ourselves: 10 buyer prompts, 2 engines, one self-managed workspace. This is the exact journey a new Starter account takes.
Disclosure: this is Anovox tracking itself. Metrics below illustrate an example workspace — the journey and the loop are real; treat the numbers as illustrative.
6
Zero-citation gaps found in week one
3
Fixes generated in Agent Studio
+6pt
Illustrative SOV lift after publishing
Week 1 — Measure
Ten prompts, first run, honest baseline
We listed the questions buyers actually ask AI about this category (“best AI visibility tool for SMBs”, “how to track ChatGPT citations”) and ran them across ChatGPT and Gemini. The citation board showed exactly where we were invisible — no surprises, no vanity.
Week 2 — Rank
Aim turned gaps into a worklist
Six prompts had zero citations. Aim ranked them by severity × priority × recency instead of leaving a flat backlog, so the week's work was obvious: three prompts worth fixing now, three worth watching.
Week 3 — Fix
Three assets out of Agent Studio
Each top gap became a generated asset — an FAQ page, a comparison page, and schema markup — grounded in the real answers that had omitted us. Every asset got a pre-publish prediction score before shipping.
Week 4 — Prove
Remeasured, not assumed
The next runs showed which fixes moved citations and which didn't. That's the whole loop: measure → rank → fix → prove. Nothing in this story required trusting a black box — every number links back to a stored answer.
The product's promise in one sentence: a new account goes from 'are we in AI answers?' to a ranked fix list in week one, and to measured proof within a month.