AI Feedback by Amplitude: Turning noisy customer input into clear product priorities
Feedback engine hums,
Insights from voices converge,
Magic in data.
Amplitude has rolled out AI Feedback, a customer feedback engine that uses a proprietary LLM to turn raw input into prioritised, actionable insights. It ingests reviews, surveys, sales calls, and support tickets-then surfaces what matters inside the Amplitude platform.
For product teams, this is the part of the job that usually drags: collecting feedback across tools, tagging it, and trying to make sense of the patterns. Now it sits in one place, connected with Analytics, Session Replay, and Guides & Surveys, so you can go from "what are users saying?" to "what should we build or fix next?"
What it does
- Consolidates customer sentiment from reviews, surveys, call transcripts, and support tickets.
- Clusters feedback by themes, pinpoints pain points, and ranks opportunities.
- Ties insights to product data via Amplitude Analytics, Session Replay, and Guides & Surveys for fast validation.
Yana Welinder, Head of AI at Amplitude, puts it plainly: "The hardest part of building great products isn't writing code. It's hearing what customers are saying across thousands of sales calls, reviews, and support tickets. AI Feedback provides clarity into what customers really want - all in one place."
Amol Jain, Head of Product Engineering at Replit, shared a similar shift: "The aha moment was truly when I first connected all the sources to AI Feedback, and it did its magic and analysed all of our user feedback. In the past it was so much work to pull data, look through each source, and manually combine them-the fact that AI Feedback just did it with a few clicks? That was fairly magical."
Why product teams should care
- Faster triage: Consolidate and rank issues without manual tagging marathons.
- Cleaner signals: Separate loud opinions from recurring patterns backed by volume and sentiment.
- Closed-loop learning: Move from insight to experiment using Guides & Surveys, then validate with Analytics and Session Replay.
Plans and availability
AI Feedback is available across all Amplitude plans. Higher volumes of feedback analysis can be purchased on Growth and Enterprise, giving larger teams headroom to scale.
Context and credibility
Amplitude acquired AI company Kraftful in July to strengthen its capabilities in this area. The platform serves 4,500+ customers, including Atlassian, Burger King, NBCUniversal, Square, and Under Armour, and has been ranked #1 across multiple categories in G2's Fall 2025 Report.
Quick implementation playbook
- Connect sources: Pipe in reviews, NPS/CSAT, support tickets, and sales call transcripts.
- Define themes: Start with your top product pillars and known pain areas; let the model surface additional clusters.
- Set routing rules: Auto-assign high-impact insights to PMs and functional owners.
- Validate with product data: Use Analytics to quantify reach and impact; watch key sessions with Session Replay.
- Close the loop: Launch in-product surveys or guides to test solutions and confirm you solved the right problem.
What to measure
- Top recurring pain points by volume and sentiment trend.
- Time from signal to decision (and to shipped change).
- Impact on activation, retention, and support volume after changes ship.
- Confidence score of insights vs. manually tagged baselines.
Practical notes
- Start with one or two high-signal sources (support + NPS), then layer in more.
- Create a weekly "insight review" ritual with PMs, design, and support leads.
- Document decisions: What you'll act on, what you'll monitor, and what you'll ignore (and why).
If you're evaluating tools, keep an eye on how well feedback connects to behavioral data. Insights are only useful if they change what you ship and how you prioritise.
Level up your team's AI skills
Want structured training for product roles working with AI-driven feedback and analytics? Explore curated options at Complete AI Training - Courses by Job.
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