Brand Mention vs URL Citation: Two Very Different AI Visibility Metrics
Brand mentions and URL citations have different causes and different fixes. How to compute each, read the gap between them, and decide which to prioritise.
Share of Voice in AI Answers: How to Measure It Properly
How to compute share of voice in AI answers defensibly: fixed prompt sets, derived competitor sets, explicit formulas and controls for variance.
The Analytics Maturity Model: Where Your Organization Is and What the Next Step Looks Like
Most mid-market organizations have invested in dashboards and BI platforms and still cannot explain why key outcomes deviate from expectations — because descriptive reporting and diagnostic analytics are not the same capability. This post maps the five-level analytics maturity model, diagnoses why so many organizations stall at Level Two, and outlines the specific investments that move you to the next level.
Answer Engine Optimization: A Practical Strategy Framework
A six-step answer engine optimization framework built on five dependent layers: access, extraction, attribution, corroboration and measurement.
Should You Block or Allow AI Crawlers? GPTBot, ClaudeBot and the Trade-Offs
A practical decision framework for AI crawler policy: what GPTBot, ClaudeBot and Google-Extended actually do, and the real cost of blocking them.
Data Literacy in Organizations: How to Build It Without a Formal Training Programme
Most mid-market organizations have the data tools but lack the decision-making behaviour to match. Building data literacy through formal training programmes consistently underdelivers — the real leverage lies in redesigning the meetings, decision templates, and dashboards your teams already use. This post outlines a practical, structural approach that embeds data fluency into daily work without adding a single course to your calendar.
Schema Markup for AI Search: The Types That Change Citation Outcomes
Schema does not guarantee citation, but it removes ambiguity about who you are and what you claim. Here are the types that matter and how to implement them.
llms.txt Explained: What It Is, What It Isn’t, and How to Write One
llms.txt is a proposed convention, not a standard, and no major engine confirms reading it. Here is an accurate account of what it does and how to write one.
From Spreadsheets to BI: The Migration Framework That Avoids the Usual Failures
Moving from spreadsheet-based reporting to a BI platform like Power BI is one of the highest-leverage infrastructure investments a mid-market organization can make — and one of the most commonly mishandled. This post walks through the migration framework that avoids the usual failures: auditing the spreadsheet estate, selecting the right first cohort, preserving business logic in the data model, and running a parallel period that builds real trust before cutover.
How to Get Cited in Google AI Overviews
AI Overviews resolve queries above the ranked results. Here is how sources get selected, what to change on the page, and how to monitor citation.
