Use Case

Mine Social Media for Product Insights

Your users share honest feedback on social platforms — not in NPS surveys. SignalSurf aggregates product feedback from across the web to inform your roadmap.

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Your most honest feedback isn't in your survey tool

Users share their real opinions about your product on Reddit, Threads, and X — not in NPS surveys or feedback forms. They're more candid with their community than with your customer success team.

User feedback on social platforms is scattered and hard to aggregate
Product teams rely on biased internal feedback channels
Feature requests on social media go untracked and unacknowledged
No way to quantify which feature requests have the most demand

Aggregate and analyze feedback from everywhere

SignalSurf collects every mention of your product that contains feedback, feature requests, or sentiment. Product teams get a complete picture of user needs.

Capture all feedback

Monitor social platforms for any conversation where users discuss your product's strengths, weaknesses, or desired improvements.

Classify and cluster

AI categorizes feedback into themes: feature requests, bug reports, praise, UX complaints. See which categories appear most frequently.

Inform your roadmap

Use aggregated social feedback to validate roadmap priorities. Show stakeholders that feature requests come from real users.

Key Features

Feedback classification

AI categorizes social mentions into feature requests, bug reports, praise, and complaints.

Theme clustering

Group related feedback into themes to identify the most common requests and pain points.

Sentiment trends

Track how user sentiment about specific features changes over time.

Roadmap evidence

Export aggregated feedback data to support product decisions and prioritization.

Your GTM Playbook that works.

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