Answers in plain language
Ask in Confidence or in Slack. Every answer comes with a chart, the query behind it, and the tables it used, so you can check the number instead of trusting it blindly.
Product Analytics
Product analytics that knows what you shipped.
Ask a question about your product in plain language. The Confidence Agent finds the right data in your warehouse, writes the query, and answers with a chart, its sources, and the rollouts and experiments that explain the change.
Product Analytics answers the question and tells you what changed
The Confidence Agent is used by thousands of people at Spotify every month.
Context from what you shipped
When a metric moves, the agent checks your rollouts and experiments before it speculates, so the chart and the change that explains it arrive together.
Dashboards answer the questions you planned for
Dashboards are good for questions you ask every week. They break down when you need a cut nobody built. If monthly active users drop in one market and your dashboard can't split that market by device or plan, you're stuck waiting for an analyst or writing the query yourself.
Even when you get the number, it’s missing context. A standalone analytics tool can query your warehouse, but it doesn’t know you rolled out a new onboarding flow last Tuesday. You still have to connect the chart to what you shipped, across separate tools.
How does Product Analytics answer questions?
You ask a question in plain language. The Confidence Agent, the AI agent built into Confidence, finds the relevant tables, writes the query, and returns the answer as a chart you can explore. You test a hypothesis in one conversation, without building a new dashboard.
01
Ask in plain language
For example: “How did monthly active users change in France last month?” Ask in Confidence or in Slack.
02
The agent finds the data
The Confidence Agent picks the relevant fact tables, writes the query, and checks your rollouts and experiments.
03
Check the answer
Every answer shows its query and sources. If the data to answer confidently doesn’t exist, the agent says so.
04
Keep exploring
Ask a follow-up to break the result down by age group, device, or plan, or save it as a Pulse.
How does Product Analytics explain why a metric moved?
A metric move means something different during a launch, halfway through a rollout, or right after an experiment. Product Analytics reads your warehouse alongside what Confidence already knows about your flags, rollouts, experiments, and product strategy.
When activation drops 8% in Germany, Confidence charts the drop and points out that a rollout reached 50% of German users the same day. It pulls the experiment readout for that change into the same answer, so you have a hypothesis for the fix without relying on someone to remember what shipped last week.
Get your key metrics in Slack every day or week with Pulse
A Pulse turns a useful result into a recurring check on a metric, such as monthly active users, activation, or rollout health. Each time it refreshes, Confidence posts it to your team in Slack.
A Pulse stays explorable after it lands. Reply in the thread to ask for a deeper breakdown, or to compare the metric with a rollout or experiment, and the agent answers right there.
You choose the data the agent can use
Connecting every table in your warehouse makes it harder for an agent to pick the right source. Spotify learned this building its internal agent: across more than 70,000 datasets, ad hoc tables and one-off analyses taught the agent the wrong patterns.
In Confidence, your data experts choose the fact tables Product Analytics can use: product events, business metrics, and trusted aggregations. You can also give the agent instructions, such as “follow our definition of an active user.” Product Analytics works with BigQuery, Databricks, Redshift, and Snowflake, and reads your data in place.
Does Product Analytics replace analysts?
No. Product Analytics helps you explore and decide where to look next. A chart can show a change, but it can't prove the cause, fix the source data, or settle what an ambiguous metric means. Important findings still need review from someone who knows the data, and often an experiment to confirm the cause. Confidence runs that experiment on the same platform.
A PM asks why activation dropped in Germany. Confidence charts an 8% drop, notes a rollout reached 50% of German users that day, and shows the drop is almost entirely on desktop. The team pauses the desktop rollout and saves the question as a weekly Pulse.
Questions and answers
What do I need to get started?
A Confidence account connected to your data warehouse. Choose the fact tables the agent can use, add any instructions about your data, and start asking questions.
Where does the data come from?
From your own data warehouse: BigQuery, Databricks, Redshift, or Snowflake. Product Analytics reads the fact tables your team selects in place, without copying data out of the warehouse.
How do I know an answer is right?
Every answer includes the query the agent wrote and the tables it used, so anyone can check the calculation.
What happens if the data doesn't exist?
The agent tells you it can't answer confidently, so you know what data to start collecting.
Can I use Product Analytics in Slack?
Yes. Ask questions in Slack, and get Pulses delivered to a channel, where your team can ask follow-up questions in the thread.
How is a Pulse different from a scheduled report?
A scheduled report tells you something moved and stops there. A Pulse lets your team reply in Slack to break the metric down or compare it with a rollout or experiment.
Read more about Product Analytics
Introducing Product Analytics
Product Analytics in Confidence lets you ask questions of your data in plain language and get answers you can explore with more depth and flexibility than a dashboard.
Guillaume Perchais
Introducing Confidence Agent
Confidence Agent is an AI collaborator built into Confidence that works with your flags, experiments, metrics, and project documents.
Sebastian Ankargren
Get Started