MytheAi

🎙️ Task

AI for Interview Analysis (2026)

Interview analysis used to mean a researcher transcribing calls, color-coding quotes in a spreadsheet, and praying nobody asked for the underlying data. AI interview analysis tools transcribe automatically, tag themes across hundreds of interviews, and surface verbatim quotes by sentiment or topic in seconds. Dovetail and Lookback lead UX research with deep transcript and tagging tools; Sprig combines product analytics with interview data; Respondent and dscout add participant recruiting on top of the analysis layer.

Updated May 20265 toolsintermediate

How we picked

Selection focused on: transcript accuracy, AI-powered theme tagging, verbatim quote search, and integration with research recruiting and product analytics.

Top 5 picks

  1. 1
    Dovetail
    DovetailFreemium

    AI-powered research repository that synthesises customer insights from interviews, surveys, and support data

    ★ 4.61,831 reviewsFree tier0
    Try Dovetail →Review →
  2. 2
    Sprig
    SprigFreemium

    In-product research platform for capturing user feedback and behaviour in real time during the actual experience

    ★ 4.4992 reviewsFree tier0
    Try Sprig →Review →
  3. 3
    Lookback
    LookbackPaid

    Moderated and unmoderated user interview platform for capturing rich qualitative research sessions

    ★ 4.3754 reviewsFrom $25/mo
    Try Lookback →Review →
  4. 4
    Respondent
    RespondentPaid

    Professional participant recruitment platform for finding qualified B2B and specialist research participants

    ★ 4.3575 reviews0
    Try Respondent →Review →
  5. 5
    Dscout
    DscoutPaid

    Mobile diary study and remote research platform for capturing experiences in the real world

    ★ 4.3396 reviews0
    Try Dscout →Review →

Frequently asked

Dovetail vs Lookback?
Dovetail leads in transcript analysis and theme tagging across many interviews; Lookback is stronger for live-session moderation and recording. Post-interview analysis emphasis: Dovetail. Live-session moderation emphasis: Lookback.
How accurate is AI theme tagging?
AI suggests themes with 75-85% precision; researcher review is required to verify before publishing findings. Use AI to draft tags 5x faster, not to replace researcher judgment.
How many interviews per study?
For most product-research questions: 8-12 interviews per user segment hits theme saturation. Beyond 20 interviews per segment, AI helps spot deeper patterns that manual review would miss.

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MytheAi Team, editorial team at MytheAi

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MytheAi Team

Editorial Team

The MytheAi editorial team tracks and reviews AI and SaaS tools. We built MytheAi out of frustration with pay-to-rank listicles and SEO-driven directories that prioritize ad revenue over honest guidance. Hands-on testing across 590+ tools to date.

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