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Highlights

Use Highlights when you want to work with the key insights extracted from your recordings in NEXT. Highlights are the analyzed moments from raw customer evidence such as interviews, customer success calls, support conversations, survey responses, and usability tests.

Highlights can be created automatically by NEXT AI or manually by users. In practice, they turn long transcripts and media files into smaller, reviewable evidence units that are easier to organize, search, share, and reuse.

How Highlights Are Created​

NEXT can generate highlights automatically after you upload a recording. Once transcription is finished, AI analyzes the recording and usually creates the first set of highlights within a couple of minutes. These highlights can capture user pain points, needs, positive feedback, and other relevant insights that help teams make better product decisions.

If AI misses an important moment, users can also create or adjust highlights manually from within a recording. Because highlights are based on selected transcript text, they stay tied to the original source material instead of becoming disconnected notes.

What a Highlight Includes​

Each highlight is created from transcript text in a recording. Since recordings in NEXT are time-based media, every word in the transcript is linked to a moment in the underlying audio or video, even when the original upload started as text.

A highlight typically includes:

  • An audio or video clip
  • The highlighted transcript text
  • A descriptive title
  • Tags for organization

The title matters especially because it is one of the main inputs AI chat uses when working with highlights.

What You Can Do With Highlights​

Highlights make raw customer evidence easier to consume and share across the team. They are one of the main building blocks for downstream workflows in NEXT.

Teams commonly use highlights to:

  • Start AI chat from all highlights, selected highlights, or individual highlights
  • Group related highlights into larger themes or work items called clusters
  • Share important findings quickly with teammates or external stakeholders
  • Send supporting evidence into connected tools such as Miro, Figma, Jira, or Productboard
  • Copy highlights into workshop boards such as Miro or FigJam to support synthesis and brainstorming

This section covers common highlights workflows in NEXT, including tagging highlights, starting chat from selected highlights, bulk editing metadata, adding highlights to clusters, changing the library view, and translating highlight text.