SEO / Guidance · Test first
Your English AI visibility score cannot speak for every market.
Source published 2026-10-14 · Brief published 2026-10-15 · Updated 2026-10-15
What changed
In new Search Engine Land guidance, consultant Myriam Jessier recommends considering the language customers use commercially when tracking AI prompts, alongside an English comparison baseline. The article discusses locally meaningful terms and cross-market comparability. It is practitioner guidance, not a platform announcement.
What this actually means
My recommendation is to test the buying question, not simply its translation. Two sentences can look equivalent while implying a different service, qualification or purchasing situation. A useful local question should be checked by someone who knows the market. Keep that distinction in the report instead of blending all language observations into a reassuring overall score.
Who should care
B2B companies selling in several languages, particularly where reporting relies on English questions while buyers evaluate suppliers in French, Arabic or another local language.
The implications for your team
An English-only dashboard could send the content team toward the wrong repair. The issue might be an inaccurate local answer, a missing product fact, a weak local proof point or a genuinely different buying need. Those require different work. Before commissioning more articles, determine which problem the observation actually supports and whether the business can serve the audience concerned.
Editorial recommendation
Your next useful move
Choose one offer and two relevant markets. Build a small, locally reviewed set of buyer questions, then record comparable observations without treating the results as search-volume estimates or a complete picture of AI demand.
What could change in practice
The first result should be a better measurement method and a shortlist of specific content or positioning questions. Differences between answers may persist or vary across checks. They do not, by themselves, show lost customers or prove that a content revision will earn a recommendation.
How to put it into practice
These are recommended next steps. Confirm the feature or workflow is available in your account before changing production settings.
Get the question from the market
Collect recurring evaluation questions from local sales or support conversations. Ask a fluent reviewer to preserve the intended buyer task, including terminology, suitability and prerequisites. Label questions that are genuinely local rather than forcing them into an English-equivalent list.
- Who owns it
- Local commercial lead with content
- Check before moving on
- Each question sounds natural and corresponds to a buying situation the company can actually serve.
Separate comparison questions from local-only questions
Create one small group that supports a fair cross-language comparison and another for needs specific to the market. Record why each belongs in its group. Use keyword data as supporting context where available, not as a count of conversational AI prompts.
- Who owns it
- SEO lead and local reviewer
- Check before moving on
- The report states which observations can be compared and which cannot.
Record the conditions and inspect the answer
Use permitted tools and retain the prompt, language, date, service or model and any known location or account context. Log mentions, recommendations, cited pages and factual errors separately. Have the local reviewer check meaning rather than trusting a translated summary alone.
- Who owns it
- Analytics owner with a fluent reviewer
- Check before moving on
- Another reviewer can understand the observation and distinguish a citation from an actual recommendation.
Fix the demonstrated gap
Assign a verified error or missing answer to the relevant product, content or market owner. Improve the appropriate page rather than generating one page per prompt. Repeat comparable checks and review referrals and enquiries separately, retaining uncertainty about attribution.
- Who owns it
- Content owner with the relevant subject expert
- Check before moving on
- The revision addresses a documented buyer-information gap, not just an unfavorable score.
How to check whether it worked
A useful program can explain what was observed in each market and which decision follows. It should also identify where there is not enough evidence to act. Evaluate the accuracy and usefulness of the local buying journey alongside visibility, not merely the number of times the brand appears.
What to keep in mind
The source’s examples and numerical selection heuristics are not universal thresholds for B2B markets. This brief does not adopt its broad claims about all models’ internal language processing. Prompt samples are observations under particular conditions, not a census of buyer demand.
Read the original
Search Engine Land · 2026-10-14
What language should you track AI prompts in? ↗