a use case of your own analyst

Product insights from feedback, support and Amplitude

Q: Does it decide what to build next?

No. It shows what people ask for most, what happens with it in the product and what changed after releases. Priorities and decisions stay with the product team. Every insight in the brief carries a source, a mention count and a confidence level, so it's easy to verify.

Q: How often does the brief arrive?

Every week, a day before planning, at your time. Between briefs you can ask questions in the thread: for example, how many users asked for export in the last month. We agree the frequency, the brief's format and the topics it groups mentions by at onboarding, and change them on request.

Every week it merges customer feedback, support tickets and in-product behaviour into a structured brief for planning.

Build your AI agent Everything your own analyst does

Product insights is a use case of your own analyst from sviy.ai for product teams: a weekly brief that merges customer feedback, support tickets, Amplitude events and Git releases into one document. Every insight carries a source, a mention count and a confidence level, and the priorities stay with the team.

Amplitude + feedback files
a brief every week
every insight with a source

Your own analyst · Slack

Read 186 tickets. Three main topics: export to Excel (41), notifications not arriving (27), team permissions (19).

Notifications is a new topic: 24 of the 27 tickets came after release 2.14 on 1 October. In Amplitude the share of users opening notifications fell from 38% to 21%. Confidence: high.

What hurts

Before every planning session I spend half a day merging feedback, support and analytics into one document.

Priorities go to whoever asked loudest last week, not to the numbers.

Insights from research get lost before the next sprint.

What your own analyst does

Collects the signals

Reads the feedback and support-ticket exports you drop into the thread or Google Sheets, and the product events from Amplitude.

Finds the overlaps

Groups mentions by topic and checks them against behaviour: how many users hit the problem and what they do next.

Links them to releases

Takes release dates from Git to tell a new problem after a change from an old one that has simply piled up.

Writes the brief

Every week before planning it sends the brief to Slack or Telegram: topics by mention count, impact on metrics, hypotheses with a confidence level.

Sources and channels

Amplitude
Git
Google Sheets
feedback and ticket files
Slack or Telegram

Before → after

Before: Half a day of merging before every planning session

After: The brief in the thread a day before planning

Before: Priority goes to the loudest voice

After: Topics ranked by mentions and impact on metrics

Before: Insights get lost between sprints

After: An insight base with tags and sources, open to the team

What it looks like in the chat

Support_tickets_W40.csv

Read 186 tickets. Three main topics: export to Excel (41), notifications not arriving (27), team permissions (19).

Mentions by topic · 4 weeks

Notifications is a new topic: 24 of the 27 tickets came after release 2.14 on 1 October. In Amplitude the share of users opening notifications fell from 38% to 21%. Confidence: high.

Put that as item one in the planning brief

Added as item 1 with a link to the tickets and the Amplitude chart. The brief will be in the thread tomorrow at 10:00 ✓

Questions

Where does the feedback come from if there's no support integration?

From exports. You drop a CSV or PDF of tickets, reviews or a survey into the thread or into Google Sheets, and your own analyst reads it. There is no direct connection to support systems today; if you need one, we discuss it at the demo. Product events it takes from Amplitude directly.

Does it decide what to build next?

How often does the brief arrive?

Updated: October 8, 2026

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