Product Analytics Team

Last updated:

|Edit this page


Team members


Makers everywhere get better at building products because of PostHog

Q4 2023 Goals

  1. Project "NoteForce Exploration 3000" (Michael, Thomas)
  • Pair up with Team Monitoring to complete projects Data Exploration, Notebooks and PostHog 3000.
  • Release new navigation and insight editor.
  • Work more HogQL prompts into the interface.
  • Build metrics into the system, introduce Metric Mondays.
  1. Project "Finish the darned Query Engine" (Tom, Marius)
  • Finish insight HogQL conversion.
  • Support non-event data sources on HogQL insights (BI tools for data warehouse).
  • Build tools to measure HogQL query performance, and catch regressions before they hit users.

Who are we building for?


  • Primary Personas:
    • Product engineer
      • These are the engineers building the product. Normally full-stack engineers skewing frontend or frontend engineers.
      • Product engineers have more limited time. Need to quickly get high-quality insights to inform what they are building and assess what they've shipped.
    • Product manager (ex-engineer type)
      • Supports the product teams (engineers, PMs, designers) to build the best products. They guide the product roadmap by speaking to customers and diving into the data.
      • Product managers are the power-users of analytics (further evidence in the data analysis of paying users). They have desire and the time to go significantly deeper into the data.
  • Limited focus:
    • Growth engineer
  • Not a focus but should be usable by:
    • Everyone in the product team (less technical PMs, designers)
    • Marketing
    • Leadership team

What types of companies?

The highest-performing product teams building the most loved products at high-growth startups. For more context on the company read about the ideal customer persona.

Jobs to be done

Product analytics is a wide tool which fulfills many job-to-be-done (non-exhaustive list):

  • Monitoring KPIs - how are the specific KPIs (product/team/company) doing? Are there any big changes, is everything going roughly in the right direction?
  • Insights into a new feature you've built - I've created a new feature and I want to make sure that it's being used successfully
  • Watching for errors and debugging - something went wrong (error gets trigger, product regression, drop in conversion), getting told it went wrong, debugging it, shipping a solution and making sure that fixes it
  • Conversion optimization - the growth team is monitoring how particular KPIs are doing, trying to come up with experiments, shipping features to try and improve these
  • Answering product strategy questions - which customers should we focus on, what are our most used/valued features. e.g. should we increase the pricing from X to Y? Which customers should we focus on?

You can broadly group the job-to-be-done of Product Analytics in PostHog as:

  • Creating: You have a specific query/dashboard in mind, you open PostHog to view it. E.g. creating a dashboard to Monitor KPIs, or creating the funnel for your onboarding flow
  • Consuming: you or someone else has made something in Posthog that you refer back to. E.g. Checking the dashboard you made to Monitor KPIs
  • Exploring: you're answering a broader open-ended question. E.g. If you're monitoring your KPIs and you see something not right - you then want to dive into understanding why


3 year goals

  • You can explore data across all insights and dimensions
  • You can trivially share any insight anywhere
  • Onboarding is as easy as a video game
  • Tight integration with developer workflows
  • No more complex than it is today
  • Using PostHog sparks joy
  • We support trillion event querying

Feature ownership

You can find out more about the features we own here

What we're building


Was this page useful?

Next article

Developing locally

❗️ This guide is intended only for development of PostHog itself. If you're looking to deploy PostHog for your product analytics needs, go to Self-host PostHog . What does PostHog look like on the inside? Before jumping into setup, let's dissect a PostHog. The app itself is made up of 4 components that run simultaneously: Django server Celery worker (handles execution of background tasks) Node.js plugin server (handles event ingestion and apps/plugins) React frontend built with Node.js These…

Read next article