Product design question

How would you make sure Amazon gives relevant results if a user types in the product details in local language?

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What this question tests

Product design for multilingual search relevance: understanding NLP challenges and measurable ways to close a language gap.

How to approach it

  1. Clarify scope: which markets and languages, since India alone has many regional languages with different scripts and transliteration patterns.
  2. Identify the user: shoppers who search in their native language or a mix of English and local language (code-mixing), common in markets like India.
  3. Name the pain point: search relevance models trained mostly on English queries fail to match local language terms to the right product attributes.
  4. Propose a solution: a multilingual query understanding layer that maps local language and transliterated terms to canonical product attributes, plus expanding product catalog metadata with local language synonyms.
  5. Prioritize the highest volume regional languages first based on search query data, rather than trying to cover all languages equally at once.
  6. Define success as local language search zero-result rate and click-through rate on local language queries compared with English queries.

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