Skip to main content

General Highlight Settings

Adjust the general AI guidance so highlight extraction reflects your teamspace context and priorities.

NEXT can automatically analyze customer interactions such as user interviews, usability tests, sales calls, customer success calls, support tickets, and other audio, video, or text-based research materials. General highlight extraction settings tell NEXT AI what your product is about, what feedback to prioritize, and which language to use for generated highlights.

The workflow is straightforward: add a recording or text file to your library, let NEXT transcribe it into searchable text when needed, and then let AI identify key moments. These shared settings make that analysis more relevant to your teamspace by giving NEXT AI the right product and research context before it generates new highlights.

Before You Start​

  • You must have permission to edit teamspace settings.
  • These settings apply to future highlight extraction.

Steps​

To configure general highlight extraction settings:

  1. Open Teamspace Settings > Prepare with AI > Highlights.
  2. In General, describe your company or product.
  3. Describe the content areas AI should focus on.
  4. Choose the language in which NEXT AI should create highlight content.

When Should I Use General Highlight Settings?​

Use these settings when highlight quality needs better domain context, a clearer thematic focus, or stronger alignment with your research goals.

  • New teamspaces without established AI context
  • Teams changing product positioning or audience
  • Teams that want highlight output in a specific language
  • Teams uploading different kinds of customer interactions, from interviews and calls to tickets and survey responses
  • Research projects that need AI to focus on one product area, device, workflow, or audience
  • Analysis that should emphasize themes such as accessibility, onboarding friction, bugs, or feature requests
  • Teams that want AI analysis to better reflect their reporting priorities and recurring review themes

Tips​

  • Keep descriptions specific and concrete to improve extraction quality.
  • Write product context as if you were briefing a new researcher on your product, users, and workflows.
  • Focus on recurring themes your team actually reviews.
  • Use the content focus field to steer AI toward the topics that matter most instead of trying to describe everything at once.
  • Because these are shared teamspace settings, keep the guidance useful for everyone reviewing highlights.
  • Align the guidance with the kinds of insights your team wants to surface, such as pain points, requests, sentiment patterns, or recurring themes.
  • Revisit these settings when your product strategy changes.
  • If highlight quality drops or feels overly narrow, simplify or remove overly prescriptive guidance.

Example​

This video demonstrates how to update product context, focus topics, and language for highlight extraction.

FAQ​

Q: Do these settings affect existing highlights?​

No. They primarily influence future AI highlight extraction.

Q: What should I write in the product description?​

Describe your product, target users, and core workflows in plain language. Good examples include the product area under review, who uses it, and the context the AI should keep in mind.

Q: What should I include in the content focus description?​

List the customer feedback themes your team wants to prioritize, such as onboarding friction, accessibility, bugs, feature requests, or feedback from a specific platform or audience.

Q: When should I change the extraction language?​

Change it when your team needs generated highlights in a specific working language.

Q: Can I use these settings to steer AI toward a specific project or audience?​

Yes. You can use the product and content descriptions to guide AI toward a product area, workflow, device type, market, or audience segment when that context matters for the analysis.

Q: Why does NEXT AI need these settings?​

They help NEXT AI understand your teamspace goals and apply more relevant context during highlight extraction, which can improve how well it surfaces useful patterns in customer feedback across recordings, transcripts, tickets, survey responses, and similar sources.

Q: Will NEXT AI always follow these instructions exactly?​

Not always. These settings guide NEXT AI, but they do not override the source material. Results are usually strongest when the instructions match the actual language and themes in your recordings.

Q: What kinds of files can NEXT analyze for highlights?​

NEXT can analyze customer interactions from video, audio, and text sources. Common examples include user interviews, usability tests, sales calls, customer success calls, and support tickets.

Q: How does NEXT create highlights from uploaded files?​

After you add a recording or text file to your library, NEXT transcribes supported media into text and then uses AI to identify important moments such as positive feedback, negative feedback, pain points, bugs, and user needs.