Log in

Data & Analytics

See where users drop off and why.

ZeroTwo builds conversion funnels from raw event data in your Postgres or MySQL database, identifies which step has the steepest drop-off, and compares feature adoption between users who convert and those who don't.

Integrates with:

What changes

Before
With ZeroTwo
Depth of analysis
Funnel chart shows where users drop, not why
Behavioral comparison showing which features and actions differentiate converters
Segmentation
One segment at a time, each requiring a new chart
Every segment computed in one run: channel, plan, device, cohort
Auditability
A chart with no source code or query behind it
Every query and every line of analysis code visible and editable
Actionability
'Activation is 34%.' OK, but what do we do?
Specific features and actions ranked by how much they differentiate converters

Depth of analysis

Before

Funnel chart shows where users drop, not why

With ZeroTwo

Behavioral comparison showing which features and actions differentiate converters

Segmentation

Before

One segment at a time, each requiring a new chart

With ZeroTwo

Every segment computed in one run: channel, plan, device, cohort

Auditability

Before

A chart with no source code or query behind it

With ZeroTwo

Every query and every line of analysis code visible and editable

Actionability

Before

'Activation is 34%.' OK, but what do we do?

With ZeroTwo

Specific features and actions ranked by how much they differentiate converters

Activation is 34%. The product team wants to know why.

Your analytics tool shows the funnel chart. You can see where users drop off. But the chart doesn't tell you why. Getting from 'Step 2 has a 60% drop-off' to 'users who complete onboarding within 24 hours convert at 3x the rate' requires SQL, notebooks, and a full day of analysis.

Every time the product team ships a change, they want a fresh funnel analysis with new segments. Each request means rebuilding the queries, reformatting the output, and presenting findings that are already a week old by the time they land.

How ZeroTwo analyzes your funnel and user behavior

1

Pulls signup, interaction, and activation events

Neon

Events grouped by user ID for the analysis window. SQL visible in the execution log.

2

Builds a step-by-step conversion funnel

Google

Computes conversion rates at each stage, identifies steepest drop-off, segments by channel, plan type, device.

3

Ranks behaviors that separate converters from non-converters

Google

Computes adoption rates for each feature, ranks differences by effect size.

4

Posts top findings to your channel

Slack

Delivers funnel step drop info, differentiating behaviors, segment variations with full data and code.

Runs Monthly, or on demand after product changes · Analysis posted to #product-data in Slack

Get started in under 10 minutes

1

Connect your tools

One-click OAuth for each integration. No API keys, no engineering.

2

Describe what you need

Analyze our signup-to-activation funnel: landed on pricing, started trial, created first project, invited a teammate. Show where users drop off and compare conversion rates by referral source.

3

It runs on schedule

Updated analysis lands in your team channel every month, with on-demand reruns after product changes.

Frequently asked questions

ZeroTwo runs against your raw event data with your definitions, so you're not limited by what your analytics tool tracks or how it segments. The analysis runs as code you can inspect, edit, and extend.

For each tracked feature or event, ZeroTwo computes the adoption rate among converters and non-converters, then ranks the differences by effect size.

Yes. Every SQL query and every line of Python analysis code is visible. You can edit the funnel steps, adjust the comparison logic, or add segments and rerun.

Yes. Trigger a rerun with a date filter: 'compare funnel conversion for users who signed up before vs. after March 1.'

Related workflows

Stop doing the work your tools should do for you.

Set it up once. ZeroTwo runs it every time.