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The Growth Library

Run the same AEO panel in a second language

Review question equivalence and local buyer needs before comparing answer observations across languages.

A second-language AEO review can answer two different questions: how equivalent questions perform in another language, or what a different audience asks. Keep those designs separate. A local market panel may be more useful commercially, but it is not automatically a like-for-like translation of the first panel.

Begin with the buyer decision behind each prompt. Have a qualified language reviewer check whether the translated question preserves that decision, its conditions, and its tone. Literal wording can remain fluent while shifting the task.

This is an original research-planning method. It does not assume that every answer engine behaves consistently across languages or that translated prompts produce equivalent samples.

Map questions by decision

For a fictional purchasing-software panel, three source questions might concern approval ownership, export requirements, and alternatives to email. The translation review should preserve those specific jobs.

Question purposeEquivalence checkPossible local adaptation
Identify an approval workflowDoes the wording still ask about the same operational process?Use the audience's actual terminology
Verify export requirementsAre format and scope conditions retained?Add a locally relevant requirement in a separate prompt
Compare email with a toolDoes it preserve the option of keeping the current process?Use a different common alternative when research supports it

Store the source prompt, translated prompt, reviewer, and equivalence note. If a local adaptation changes the question materially, give it a new prompt ID rather than treating it as the same measurement unit.

Preserve the collection conditions

Record the interface language, prompt language, relevant location settings, account state, available model label, and answer evidence. Do not assume that changing the prompt language changes every other condition in the same way.

Keep branded questions separate in each language. Some product names remain unchanged; others have verified local forms. Use actual identity records rather than inventing translated brand names to make the panel feel localized.

If an answer mixes languages or fails to address the prompt, record that behavior explicitly. A response can contain a brand string while failing the intended buyer task. Mention counts alone would miss that distinction.

Calibrate the coding in both languages

Give reviewers the same definitions for mentions, recommendations, conditions, and citation support. Use reviewers who can interpret the answer's language and context. A machine translation can assist inspection, but it should not silently replace the underlying evidence.

Review a small shared set for ambiguity. A phrase that sounds like a recommendation in a translated summary may be more tentative or conditional in the original. Preserve the actual wording and the reason for the code.

Use the calibration exercise to document disagreements. Keep linguistic uncertainty separate from missing evidence or an unclear product identity.

Compare only the appropriate subsets

Suppose a hypothetical review includes nine equivalent nonbranded questions in each language and three additional local questions. Compare the nine-question core separately from each expanded panel. Combining everything into one percentage hides the changed question mix.

Show counts and coverage by language, engine, and question group. Do not label a stronger result in one hand-selected panel as proof that the brand has greater market share in that language's entire audience.

Use the panel versioning method to preserve the history. The review should reveal which buyer questions need better explanations or evidence in each language while keeping the comparison honest about what stayed equivalent and what changed.

Matt Pru

Co-founder and CEO of Stackmatix. Writing about growth, customer acquisition, and the decisions behind useful marketing. Connect on LinkedIn.

Developed with AI assistance under Matt's editorial direction. Read our editorial approach.