Zenzo Analyst
StripeAsk what Product asks every week
Answers in the planning meeting, not two sprints later.
Zenzo for Product
Ship what customers use, and prove it.
Product teams have the usage data but rarely the time to query it. Zenzo lets PMs ask how features perform, who adopts them and what they do for retention, and shows the query behind every answer.
- Read-only connections
- Sensitive data hidden before AI sees it
- 30+ connectors
Connects to the tools Product teams already use
PostgreSQL
MongoDB
ClickHouse
BigQuery
Snowflake
Google Analytics
Jira
Intercom
Zendesk
SlackBefore and after
Answers in the meeting,
not after it.
Product judgement, backed by the data you already collect.
TodayManual work
Product manager · the usual way- Feature adoptionA ticket to the data team, answered next sprint.
- Release impactEyeballing a chart for a bump.
- PrioritizationThe loudest request wins.
- Past decisionsDigging through old docs and threads.
With ZenzoEvidence attached
Product manager · with Zenzo- Feature adoptionAsked and answered in plain English.
- Release impactBefore-and-after cohorts with sizes and dates stated.
- PrioritizationRequests weighted by the revenue of the accounts asking.
- Past decisionsCited answers from specs and decision records.
How it works
From question
to answer you can check.
Follow one Product question through Zenzo, from the moment it’s asked to the evidence behind the answer.
Ask
Which bugs generate the most support load?
Which features do our largest customers never touch?Where do new users drop out of setup?
Answer
Which bugs generate the most support load?
Jira issues linked to tickets, ranked by ticket count.
Answered with Zenzo Analyst · from Jira and Intercom
Evidence attached · sources and query shown
You get a plain-English answer with the evidence attached.
Questions with proof
Product questions,
without the data queue.
Answers in the planning meeting, not two sprints later.
Where do new users drop out of setup?
Completion rates for each setup step, for sign-ups in the last 30 days.
Which bugs generate the most support load?
Jira issues linked to tickets, ranked by ticket count.
How will adoption look in eight weeks?
A forecast from current adoption, with its error rate and a naive baseline drawn alongside.
What did we decide about this feature last year?
The decision and its reasoning from the product spec, cited to the document and version.
One adoption view for every release
Answered with Zenzo BI from Snowflake and Google Analytics, with the evidence attached.
Decision rhythm
From roadmap bet
to release review.
Every release starts as a guess. Zenzo helps you check it at each step.
- Before you build
How many customers hit this problem today?
Zenzo deliversCounts of the behavior behind the request, from your own event data.
- Release day
Is the new feature being used, and by whom?
Zenzo deliversAdoption by plan and segment, refreshed daily for the first few weeks.
- Four weeks later
Did it change retention, or just clicks?
Zenzo deliversCohorts compared before and after release, with sample sizes shown.
- Roadmap planning
What are customers asking for most?
Zenzo deliversRequests from tagged tickets grouped by theme and weighted by account revenue.
Where each product fits
Start with Analyst.
Add the rest as you grow.
Zenzo products are built to work together on one platform, so each step builds on the one before it.
Live
Zenzo Analyst
Query event data, cohorts and forecasts in plain English.
Start hereEarly access
Zenzo BI
Release and adoption dashboards with consistent definitions.
Learn moreEarly access
Zenzo Knowledge
Specs, decision records and research notes answered with citations.
Learn moreComing soon
Zenzo Brain
Planned: connecting product signals with revenue and support context.
Learn moreGuardrails
Switched on
from the first question.
The controls Product teams ask about first, applied to every query and every answer.
Privacy firewall
Only masked schema metadata is sent to the AI model. Sensitive data hidden before AI sees it.
Column-level masking
Give each role full, masked or no access per table, and redact, hash or partially mask sensitive columns.
Row-level security
Per-role and per-user filters are applied to every query automatically, so people only see their own data.
Tamper-proof audit trail
Every action is logged with personal data scrubbed and a cryptographic signature that proves it hasn’t been altered.
Single sign-on
Sign in with Google, Microsoft, Okta or any OIDC provider, with SCIM to add and remove users automatically.
Your model, your keys
Bring your own API key, choose OpenAI, Azure OpenAI or Anthropic, or run local models with Ollama.
User identities maskedSchema only to the modelForecasts that show their error
Explore more
Questions rarely stop
at one team.
These pages pick up where this one ends.
By department
By industry
FAQ
Questions from
Product teams.
Still deciding? We’re happy to walk through your own data and questions.
Does Zenzo work with event data at scale?
It queries your warehouse or analytical database directly, such as ClickHouse, BigQuery or Snowflake, so the heavy lifting stays where the data lives.
Is Zenzo a product analytics tool?
It isn’t a tracking SDK. It answers questions from the event data you already collect, and joins it with CRM, billing and support data.
Can I see the query behind an answer?
Yes. Every answer shows its SQL, and you can save, version and share it.
How are forecasts kept honest?
Forecasts report their error (MAPE and MAE) and draw a naive baseline next to the model, so you can see whether the forecast adds anything.
Get started
Bring your Product
questions.
Connect a source, ask what your team asks every week, and check the evidence behind every answer.
Read-only connections · Sensitive data hidden before AI sees it · 30+ connectorsCheck out the plans that fit your team or organization.
See Pricing