AI feedback analysis grounded in the original responses

Signaldeck turns collected responses into themes, positive and risk signals, confidence, and suggested actions, then keeps the original feedback available so your team can move from a full response set to a focused decision faster.

  • Themes and next actions
  • Confidence signal
  • Original feedback

Turn collected feedback into a clearer next step

Signaldeck analyzes text and rating responses collected through your widgets and shareable flows, bringing repeated themes, positive signals, risks, and suggested actions into one focused report. See what deserves attention, then decide what to fix, test, explain, or explore next.

  • Themes surfaced across responses
  • Positive and risk signals
  • Suggested actions
  • Original feedback within reach

See the themes, evidence, and next actions in one report

A Signaldeck report brings together an overview, common themes, positive signals, risks and suggested actions. Original submissions remain available when you want to explore the detail behind a pattern.

Move from a full response set to a focused decision faster

Let Signaldeck handle the first reading pass, surface what repeats, and organize the strongest signals so your team can focus on the action those responses support.

  1. Collect

    Gather responses around one useful question

    Keep the page, form, or product moment connected to the answers.

  2. Generate

    Create a focused summary of the current response set

    Bring themes, positives, risks, confidence, and suggested actions into one report.

  3. Inspect

    Read the grouped output and confidence

    Review the overview, themes, positives, risks, suggested actions, and source-response count.

  4. Verify

    Open original submissions separately when needed

    Check the response detail and context behind a pattern before committing to a change.

  5. Decide

    Choose a small fix, test, explanation, or follow-up

    Use the summary to focus judgment, then revisit the question after the change.

Map each report to a decision your team can revisit

Use one consistent report structure across pricing, onboarding, launches, and team reviews so every feedback question leads toward a clear decision.

  • Pricing

    Separate price resistance from unclear plan fit

    Read
    Themes and risk signals across pricing and signup responses.
    Act
    Test clearer plan framing or implementation expectations.
  • Onboarding

    Find repeated friction before first value

    Read
    Common setup gaps, positive signals, and confidence.
    Act
    Simplify or explain the first step, then ask again.
  • Feature launch

    Understand expectation and adoption gaps

    Read
    Repeated use cases, confusion, praise, and risks.
    Act
    Adjust the workflow, positioning, or next experiment.
  • Team readout

    Prepare a recurring evidence review

    Read
    Current summary and response count for the question.
    Act
    Assign the next decision to an owner and keep the supporting feedback attached.

AI organizes the evidence so your team can decide what it means

Use confidence and original submissions to judge how much weight to give each pattern. Review the source feedback when a decision carries risk, and consider who responded and what context may be missing.

Go deeper on AI feedback analysis

Integration

MCP integration for feedback analysis

Connect feedback, summaries, and response context to tools like ChatGPT and Claude through the Signaldeck MCP server.

Use feedback in an MCP workflow

Turn one focused question into a clearer next move

Collect feedback on the Free plan, see how Signaldeck turns a response set into a focused report, and keep the original answers ready for review.