LogitRank Earns First AI Citations Across Five Platforms in Month 1 — March 2026 Rollup

One month. Four audits. The full picture.

This report aggregates the four weekly prompt audits run in March 2026 — covering 5 March (baseline) through 1 April 2026 (Week 4 close). It documents the month-on-month KPI progression, the milestone citations, the setbacks, and the actions taken that produced each shift.

Every metric in this report is drawn from verbatim AI platform responses published in the weekly snapshots. No metrics are estimated or inferred.

Month-at-a-Glance: Baseline to Week 4

Month 1 Milestones

The following citations are the most significant individual AI responses recorded in March 2026. Each is a verbatim quote from an unedited platform session.

Key Findings

1. Entity-level recognition preceded category-level citation

The pattern followed the expected sequence. Platforms first learned what LogitRank was and who Matthew Bilo was (Q3, Q4 — entity queries), then began returning LogitRank on market-level queries (Q1, Q9 — category queries). By Week 4, Q3 entity recognition sat at 4/5 platforms, directly supporting Q1 and Q9 improvements.

2. Live-retrieval platforms moved first; training-cycle platforms followed

Perplexity, Google AI Overviews, and Microsoft Copilot all cited LogitRank within two weeks of Phase 1 infrastructure being established — because these platforms use real-time web retrieval rather than static training data. ChatGPT and Gemini, which update on training cycles, showed ML algorithm confusion until Week 4, when ChatGPT made its first citation on Q9 via retrieval-augmented access to current web sources.

3. Disambiguation remained the outstanding challenge

Two forms of disambiguation were active in March. First, the “LogitRank” name conflicts with an established ML algorithm — ChatGPT and Gemini still return the ML definition on Q4 at month close. Second, the “AEO” acronym is ambiguous: Microsoft Copilot returned education and migration consultants on Q1 in Week 3 before recovering in Week 4. Both disambiguation issues are expected to resolve as the web footprint grows.

4. Week 3 regression was a platform artefact, not a signal loss

Q1 dropped from 3/5 to 2/5 in Week 3 as Copilot shifted context. Entity-specific queries (Q3, Q4) confirmed Copilot still correctly recognised LogitRank that week — the regression was isolated to the ambiguous Q1 query. Week 4 showed full recovery plus improvement, confirming that single-week drops on live-retrieval platforms should be read alongside entity-level queries, not in isolation.

Actions Taken in March 2026

Month 2 Priorities

The data from March points to three open targets for April:

• →Q4 disambiguation: ChatGPT and Gemini still return the ML algorithm on direct LogitRank queries. Continued web footprint growth and co-citation accumulation are the mechanism — no shortcut exists. Next training cycles are the expected resolution path.
• →Australia-wide category queries (Q5–Q6): Zero platforms returned LogitRank on Australia-wide queries in any week of March. This is the expected pattern — local entity recognition precedes national category citation. These queries are a Month 2–3 target.
• →Q1 Copilot disambiguation: The AEO acronym ambiguity in Copilot's Q1 context needs to be addressed through explicit disambiguation signals — additional content and directory placements that pair 'AEO' with 'Answer Engine Optimisation' in machine-readable contexts.

Questions About This Data

How long does it take to appear in AI search results after starting AEO?

The Month 1 data shows first meaningful citations appearing within two weeks of Phase 1 Knowledge Graph infrastructure being established. Three of five platforms cited LogitRank on Q1 by Week 2. ChatGPT — the slowest platform because it relies on training cycles rather than live retrieval — made its first category citation in Week 4. The methodology anticipates 3–6 months for consistent broad citation across all platforms and query types.

Why did citation rates fluctuate week to week instead of increasing steadily?

AI citation rates are not a smooth upward curve. Platforms using live retrieval (Perplexity, AI Overviews, Copilot) fluctuate based on what is currently indexed. The Week 3 Copilot regression on Q1 was caused by disambiguation — 'AEO' was read as Australian Education Office, not Answer Engine Optimisation. That is a query-context problem, not a loss of entity recognition. Copilot correctly described LogitRank on entity-specific queries that same week. The four-week trend is the meaningful signal, not any single week.

What is the Kalicube Process™ and why did it appear in AI responses unprompted?

The Kalicube Process™ is an entity optimisation framework developed by Jason Barnard that structures the signals AI platforms and Knowledge Graphs use to understand, trust, and recommend an entity. Matthew Bilo applies the Kalicube Process™ at LogitRank. It appeared unprompted in Google AI Overviews, Gemini, and Perplexity responses because LogitRank's third-party profiles — about.me, Crunchbase, and the /methodology page — reference it explicitly. Its unprompted appearance confirms entity architecture is propagating correctly.

Why did ChatGPT take until Week 4 when other platforms cited LogitRank in Week 2?

Perplexity, Google AI Overviews, and Microsoft Copilot pull from live web sources at query time, reflecting the current state of indexed sources. ChatGPT is primarily a training-cycle model — not a live retrieval engine by default. For Q9 in Week 4, ChatGPT's response included a logitrank.com citation link, which indicates retrieval-augmented generation was triggered for that query — confirming sufficient web footprint now exists for real-time retrieval to surface LogitRank.

Weekly Snapshots

Each weekly snapshot contains verbatim AI responses and screenshots from that week's audit session.