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Use Tag for AI Focus

Use Tags to decide which tags NEXT AI can use when it automatically narrows the chat focus to the most relevant highlights.

Being selective here helps teh chat to focus on the right slice of data without narrowing the search so much that useful highlights are missed.

Before You Start​

  • You must have permission to edit teamspace settings.
  • Review how consistently your team applies each tag before you enable it for AI focus.

Steps​

  1. Open Teamspace Settings > General > Tags.
  2. Search for the tag you want to review and open it.
  3. In AI focus, keep Use this tag for AI focus enabled if the tag is a good candidate for AI focus.
  4. Add a clear description that explains what the tag represents, so AI can better decide when to use it.
  5. Repeat this review for the tags you want AI to use, and turn Use this tag for AI focus off for tags that should never guide chat focus.

When Should I Use This?​

Use this setup when your team wants chat in NEXT to narrow its search with tags automatically, but only when those tags are reliable enough to improve the result.

Review AI focus whenever your taxonomy changes, a tag becomes inconsistent, or your team notices that chat is focusing too broadly or too narrowly.

How Do I Decide Which Tags To Opt In?​

Choose tags conservatively. In most cases, it is better to opt in a smaller set of strong tags than to enable every tag in your taxonomy.

Look for these qualities:

  • Clear user relevance: The tag reflects a dimension people commonly ask about, such as channel, market, or customer segment.
  • Reliable data quality: The tag is applied consistently whenever it should be. If the tagging is incomplete, AI may miss relevant highlights.
  • Broad coverage: The tag appears across a substantial portion of your highlights, so AI can narrow the search without excluding too much relevant data.

Be cautious with tags that are:

  • Rare or highly specific
  • Inconsistently applied
  • Unclear to end users
  • Unlikely to help answer common questions

An easy way to think about this is e-commerce filters. Online stores do not expose every product attribute as a filter. They choose the ones with strong coverage, reliable data, and clear relevance to shoppers. The same principle applies here.

If you are unsure about a tag, leave it out. AI can still fall back to broader search methods, while a poor tag can push the search toward an overly narrow or misleading result.

Tips​

  • Prefer tags that cover a substantial portion of your dataset.
  • Keep descriptions specific enough to guide AI, but broad enough to match normal user questions.
  • Revisit AI focus settings after major tagging cleanup or taxonomy changes.

Example​

If your team regularly asks about onboarding issues by market, country tags like France or USA can be good AI selection candidates when they are applied consistently across many highlights. A highly specific tag used on only a few highlights is usually better left out.

FAQ​

Q: Do I need to opt in every tag?​

No. It is usually better to opt in only the tags that have strong coverage, reliable data quality, and clear value for common questions.

Q: What happens if a tag is enabled for AI focus but applied inconsistently?​

AI may narrow the search too aggressively and miss relevant highlights that should have had the tag but do not.

Q: What should I write in the AI focus description?​

Write a short explanation of what the tag represents so AI can recognize when the tag is relevant for a chat request.