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LogZuno

Product analytics that answers who did what, and who came back

Product analytics should answer plain questions: how many people did this, did they finish, did they come back, and who are they. LogZuno answers them from your own events, with funnels that follow each person and retention by cohort.
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A LogZuno dashboard: active users, new users and events, with daily and weekly charts and top events

  • Funnels of up to 10 steps

    Per person, in order or any order, inside a window.

  • 3 breakdowns a chart

    By event, user or group property, with an exact Other.

  • Formulas over 10 series

    Conversion rates and ratios without exporting anything.

  • Hourly to monthly

    In your project's timezone, so today means your today.

Trends, numbers and tables

  • Calculations

    Count events, unique users or groups, weekly and monthly active users, new users, or the sum, average, minimum, maximum, median, 90th and 99th percentile of any property.

  • Breakdowns and filters

    Split any chart by up to 3 properties of the event, user or group, with an exact Other. Filter with AND/OR groups.

  • Formulas and comparison

    Combine up to 10 series with a formula (for example A / B for a conversion rate) and compare with the previous period.

  • Hour to month

    Group by hour (up to 14 days), day, week or month, in your project's timezone, so today means your today.

Illustration: a LogZuno trends chart of weekly sign-ups broken down by plan over 13 weeks, with a written summary.

Every chart your team needs, from the same events

Eleven ways to look at your events. Pick one to see what it answers and how it's built.

Line chart

Is it growing, and which segment drives it?

Teams use it for

  • Weekly sign-ups by plan
  • Errors an hour after a release
  • Compare with the previous period

Built with

Signed upUnique usersBreakdown: planWeekly

Funnels that follow each person

A funnel step only counts people who did the previous steps first, inside the conversion window you set.

  • In order or any order

    Up to 10 steps, strictly in sequence or in any order, counted per user or per group (account).

  • Conversion windows

    Count a conversion only if it happened within an hour, a day, a week or any window you choose.

  • See who dropped off

    Open any step to see the users who reached it and the ones who didn't.

Illustration: a four-step LogZuno funnel from viewing pricing to subscribing, counted per person in order within 7 days, with the conversion at each step.

Who came back, and who they are

Illustration: a LogZuno weekly cohort retention table. Each row is the people who signed up in one week, and each cell the share who used a feature in each following week.

  • Cohort retention

    Group people by when they first did something and see what share came back to do something else in each following day, week or month.

  • Power-user curve

    See how many people used the product on 1, 2, 3 or more days of the period: the frequency chart.

  • Segments

    Built-in segments (new sign-ups, active, engaged, recent, power and drifting users) plus your own, from properties, computed properties and what people did or didn't do.

  • Groups

    Account-level analytics for B2B products: active accounts, members per account and account profiles.

Ask in plain English

  • Questions become charts

    Ask "weekly sign-ups by plan over the last 3 months" and Ask LogZuno builds the chart spec, which runs through the same engine as every other chart. It never writes SQL.

  • What it sees

    Only event names and property keys are sent to the model (OpenAI), never your events or users' data.

Illustration: Ask LogZuno. A question in plain English, weekly sign-ups by plan over the last 3 months, answered with a chart and the chart settings it chose.

Questions

What is the difference between a funnel and a conversion rate?

A conversion rate divides one count by another. A funnel follows each person through the steps in order, so someone who bought without signing up first doesn't count as a converted sign-up.

How long is data kept?

90 days on every plan. Charts can cover any range within those 90 days.

What is product analytics?

Product analytics measures what people do inside your product, from events tied to users and accounts. It answers how many people do something, whether they finish the steps that matter, whether they come back and who they are.

What does product analytics tell you?

Which features people use, where they drop out of a flow, how many come back each week, which accounts are growing or drifting, and how a release changed behaviour. In short: whether people get value, and what to change next.

What is the difference between product analytics and data analytics?

Data analytics is the broad practice of analysing any data, usually with SQL and a warehouse. Product analytics is a focused part of it: behaviour inside a product, with ready-made trends, funnels, retention and user profiles, so teams answer product questions without writing queries.

What are some product analytics examples?

An activation funnel from sign-up to first project, weekly retention by sign-up cohort, the share of active users who use a new feature, the power-user curve, and the list of accounts whose activity dropped this month.

Can I count accounts, not just users?

Yes. Send a group_id with events to tie users to their company, then count unique groups, see active accounts and members per account, and build funnels counted per account.

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Send your first event today.

7 days free on any plan, up to 500 events. Then from $17 a month. Cancel during the trial and you pay nothing.

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