The Scrape-Bias Page Standard
Eight rules for building a page so machines quote it correctly: question-shaped headings, answer-first openings, visible FAQs, valid structured data, entity consistency. The standard behind every page on this site.
The resources
Published to be adopted.
Three resources. Two are written standards; the third is the machine layer itself, live on this domain. Every page on tbscg.com is built to these rules, which means you can check our homework. Take what is useful.
AEO for Enterprise Estates
How answer engines read an estate, what actually moves visibility, what does not, how to measure presence in AI answers, and where regulated estates need extra care.
llms.txt, live
A plain-text index at the domain root that tells AI crawlers what this firm is and where the canonical pages sit. This card links to the real file, not a description of one. Readable in thirty seconds.
Why we publish
Standards work better in the open.
We would rather the pages machines quote, ours and everyone else's, be built to answer correctly. Publication also keeps us honest: every claim on this site can be checked against the rules on these pages.
Buyers ask an assistant before they search, and often instead of searching. The answer is assembled from whichever pages extract cleanly. Visibility is now decided before anyone reaches your site.
Answer engines favour pages that answer first, structure cleanly and mean one thing. Ambiguity is a tax: every place a page makes the machine guess is a place the answer can come out wrong.
The channels are young and they change monthly. The principles underneath, clear answers, clean structure, consistent identity, are stable. We publish the principles, not the tricks.
These are not aspirations. Each rule in the standard is in force on this estate: question-shaped headings, visible FAQs, JSON-LD on every page, llms.txt at the root. The proof is in the source.
Published, in full
A standard only does its work once it leaves the building.
Where it connects
Part of one estate.
Machine visibility is one property of a healthy estate, not a separate project. Here is where this work most often joins the rest.
Measure first
DXP Value Survey The front door
AI in the estate
AI and Gen AI Solutions
The experience layer
Customer Experience Bloom
A fixed-price four-week diagnostic. AI readiness, including machine visibility, is one of the six dimensions it scores.
Agentic migration plus the AI capability built into the live experience your customers touch.
Conversational interfaces and AI search, built into the live estate and shipped in your brand.
Questions
Frequently asked questions.
What is answer engine optimisation (AEO)?
AEO is the practice of building pages so that AI answer engines, such as ChatGPT, Perplexity and Google's AI Overviews, can extract, attribute and quote them correctly. Where SEO optimises for a ranked list of links, AEO optimises for being the answer itself.
How is AEO different from SEO?
SEO earns a position on a results page that a person scans. AEO earns a place inside a machine-written answer. The disciplines overlap, clean structure and structured data help both, but AEO rewards answer-first writing and entity consistency far more heavily than rank ever did.
What is llms.txt?
A plain-text file at the domain root that gives AI crawlers a curated index of the site: what the organisation is, in one line, and where the canonical pages sit. It is a convention rather than a formal standard, and it costs almost nothing to publish. Ours is live at /llms.txt.
Does structured data still matter?
Yes, more than before. Valid JSON-LD such as Service, Product, TechArticle and FAQPage gives answer engines unambiguous facts to extract instead of prose to interpret. Schema that was once a rich-snippet tactic is now a primary machine-reading surface.
Where should an enterprise start with AEO?
With measurement, then the basics. Find out whether the estate appears in AI answers for the queries that matter, then fix the foundations: one question-shaped h1 per page, answer-first openings, visible FAQs, valid JSON-LD and an llms.txt index. The DXP Value Survey scores this as part of its AI-readiness dimension.
Start here
Find out what the machines see.
The DXP Value Survey includes an AI-readiness dimension: whether your estate is structured for machine readers and visible in the answers your buyers already read. Four weeks, fixed price, benchmarked against UK FS&I estates.