//.research
The R&D tax adviser AI visibility checklist
Sixteen checks, ordered by what our own sweep actually showed moves the number — a real compliance figure first, technical schema last.
Steen Stones · Reviewed 5 Aug 2026
This list is ordered by evidence, not alphabetically. Every item traces back to a specific finding from our own sweep of UK R&D tax advisers — a firm that works through this list top to bottom is working on what actually converted a mention into a recommendation in real AI answers, not a generic best-practice guess.
Compliance credibility — do this first
- A real, substantiated HMRC enquiry rate published where an engine can read it as plain text.
- Your Additional Information Form process described plainly — mandatory since August 2023, and its absence from a firm's content now reads as a gap.
- A clear statement of your position under the merged R&D scheme (accounting periods from 1 April 2024) — not the old SME/RDEC split.
- A named sign-off or review process (technical, legal, or both) that reduces claim risk — stated as a process, not a general quality claim.
Track-record and specialism content
- A real average claim value, if you can substantiate it — the single most-cited figure type in our recommendation quotes.
- Named sector specialisms (biotech, construction, software, manufacturing) with the specific reason the specialism reduces risk — not just the label.
- Years operating in R&D tax specifically, stated as a number, not “established”.
- Fee structure stated plainly — contingency percentage, fixed fee, or both — since this market doesn't price the way most professional services do, and ambiguity here reads as a gap.
Content currency
- No page still framed around the pre-merger SME/RDEC split as the current structure.
- Dated review stamps on scheme-specific content — HMRC's own guidance has moved twice in under a year, and content needs to show it's kept pace.
- Any AI-drafted technical or compliance content signed off by a named person against current HMRC guidance before it publishes.
Measurement
- You can currently answer: how often is the firm named across the questions its buyers actually ask?
- You can currently answer: what share of those mentions become a specific recommendation?
- Both of the above are tracked per engine — our own sweep found every one of 87 firms converting zero on one major engine while converting real, different shares on the other two.
Technical foundation
- robots.txt explicitly allows the AI crawlers rather than staying silent on them.
- Organization schema present on the homepage with real sameAs links to Companies House and equivalent.
- Named adviser profiles with visible credentials, not an anonymous "our experts" page.
“There's a difference between showing up and being recommended. AI cannot recommend what it doesn't know.”
//.questions
Common questions
- Where does this checklist come from?
- Every section traces to a specific finding from Avouch's own 18 July 2026 sweep of UK R&D tax advisers — see the pillar, cost, compliance and sweep-data pages in this territory for the underlying evidence behind each item.
- Is compliance really more important than SEO basics here?
- Not instead of — alongside. Ordinary technical SEO still matters for whether an engine cites a page at all. But every recommendation our sweep found was won on a compliance or track-record signal, which is why those items lead this list rather than the technical foundation section.
- How is this different from a generic R&D tax marketing checklist?
- A generic checklist would tell you to build backlinks and target keywords. This one is built from what actually appeared in the sentences AI engines used to recommend a specific firm in our own data — which is a different, narrower, more specific set of actions.
AI can't recommend what it doesn't know.
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