Keeping One Brand Consistent Across Languages
A multilingual site can describe the same product three ways in three languages. How the inconsistency is created, how a model resolves it, and how to converge without flattening what each market needs.
Attributing Leads That Came From AI Answers
Mentioned, cited and recommended are three different things, and only one of them is a traffic source. A practical way to label AI-origin leads so the number means something.
When an AI Answer About You Is Wrong
An incorrect claim in an AI answer is a finding, not a verdict. This is a triage method: classify where the error came from, choose a correction path, and verify that the correction actually took.
Where Answer Variance Comes From
The same question can produce different answers with no change on your side. Four variables explain most of it, and separating them is what makes a measurement worth repeating.
From a Citation Gap to a Content Brief
The reasoning chain between 'the answer did not cite our page' and 'here is what to write' is where most briefs go wrong. This is the chain, step by step.
Prompt Injection and Brand Hijacking in AI Answers
Someone else can change how AI describes your brand without touching your website. Here is how to tell deliberate manipulation apart from ordinary model variation, and what to do about it.
Turning GEO Gaps Into a Content Backlog
A gap report is not a work queue. This is the field set, the priority rule and the acceptance criteria that turn 'AI did not cite us' into something a content team can schedule.
Keeping Your Cited Sources Defensible
Once AI answers quote your site, its claims become quotable evidence. What to record when you cite third-party data, compare competitors, or publish a performance number.
A Page Structure Built to Be Quoted
A reusable template for pages that need to survive extraction into an AI answer, with the reasoning behind each part.
How to Build a Question Map From Real Buyer Language
The question set decides what you optimise for and what you measure. A practical method for building one from conversations you already have.
A Crawl Access Checklist You Can Run in Ten Minutes
Before any content work, confirm that AI crawlers can actually reach your pages. A ten-minute checklist that catches the failures which make everything else pointless.
How Often to Measure, and What Each Round Tells You
Weekly, monthly or quarterly: measurement cadence decides what you can conclude. What each interval can and cannot tell you.
Should You Invest in GEO? A Framework for the Decision
The question leadership actually asks is not how GEO works but whether it is worth funding. This gives a testable way to answer it, including when not to.
GEO Project Acceptance: How to Prove the Work Landed
Acceptance is where GEO projects most often become contentious. A checklist for what to measure, how, and what counts as passing.
Measuring a GEO Baseline: A Reproducible Method
Without a baseline, no optimisation conclusion is defensible. How to choose a fixed question set, what to record, and what makes it reproducible.
Six Months of GEO With No Result: A Diagnostic Order
Six months of effort and the brand still does not appear in AI answers. A triage order that finds which layer actually failed.
How Long Until GEO Shows Results
The most common dispute in GEO projects comes from expecting one kind of change on one kind of timeline. Here is what actually moves when.
Build In-House or Buy GEO: A Comparison You Can Act On
In-house GEO needs three capabilities that rarely sit in one place. Here is what each option really costs and how to tell an unreliable supplier from a capable one.
What Does GEO Cost, and How Do You Measure the Return
GEO pays off in citations rather than clicks, which makes the return hard to argue. Here is the real cost structure, a defensible way to measure it, and three mistakes that inflate the numbers.
Cross-Border GEO: One Product, Four Different Descriptions
The defining difficulty in cross-border GEO is entity fragmentation — the same product described differently by every engine. Here is how fragmentation starts and how a single source of fact prevents it.
What Buyers Ask AI Right Before They Choose: A High-Intent Question Set
Once someone is comparing vendors, their questions change shape. Most content effort goes into awareness questions, but the decision happens in the answers AI gives at this stage.
Chinese AI Engines Are Not One Market: A Per-Platform Playbook
DeepSeek, Doubao, Kimi and Yuanbao draw on different corpora and different sources. Treating them as one audience wastes the work. Here is what each one actually rewards.
llms.txt and AI Crawler Control: What to Allow, What to Block
AI crawlers follow different rules from search engines. A pragmatic guide to deciding which to allow, and what a useful permission file actually changes.
Schema Markup That Helps AI Cite You (and the Parts That Do Not)
Structured data helps a model understand what your page is. It does not make it quote you. Here is which schema types carry weight and which are mostly noise.
How to Measure AI Visibility Without Vanity Metrics
AI visibility is not a traffic number. It is a mention rate over a fixed question set. This is a measurement method that produces numbers you can act on.
GEO vs SEO: What Actually Changes When AI Answers the Query
SEO competes for a position on a results page. GEO competes for inclusion in an answer that has already been written. Here is what that difference means in practice.