COHORT PROGRAM — $950/SEAT · 3 WEEKS

Product Analytics for B2B SaaS

You have PostHog, Mixpanel, or Amplitude. Your dashboards tell you different things and the numbers don’t match. In 3 weeks, you’ll audit your own stack, build decision-ready dashboards, and run your first data-backed experiment.

Jake McMahon, ProductQuant

Join the waitlist → See the curriculum ↓

For PMs, founders, and product leaders at B2B SaaS with $500K–$10M ARR.

WHAT’S INCLUDED

Live Sessions 6 sessions, 75 min each, 2×/week

Async Work ~2 hrs/week applying to your real product

Analytics Audit Run the ProductQuant framework on your own stack

3 Dashboards Built Activation, retention, and churn signal — in your own tool

Live Experiment First data-backed experiment designed and launched

$950/seat · cohort-based · limited seats

The situation this cohort is designed for

Your dashboards tell you different things.

Someone asks how many users activated last month. Three people give three different answers. PostHog says one number, Mixpanel says another, and the spreadsheet says something else. Nobody knows which one to trust.

You’re not sure what to fix first.

Analytics is clearly broken. But is the problem the event taxonomy? The dashboard structure? The tracking governance? The tools themselves? Without knowing which layer is broken, you can’t prioritize the fix.

You have data but can’t make decisions from it.

You run experiments that produce inconclusive results. Your activation rate looks fine on paper but retention is bad. Your churn rate is stable but you don’t know why. The analytics isn’t telling you anything useful.

WHO THIS IS FOR

Built for product people making decisions without trustworthy data.

Right fit

PMs, founders, or product leaders at B2B SaaS companies with $500K–$10M ARR
You have PostHog, Mixpanel, Amplitude, or a similar tool already set up
Your dashboards exist but the team doesn’t trust the numbers
You want to run experiments but don’t have the analytics foundation to do it
You can commit ~5 hrs/week across 3 weeks (sessions + async)

Not the right fit

Pre-product or pre-revenue — you need customers and events before this makes sense
You haven’t set up any analytics tool yet (start with the Analytics Audit first)
You’re looking for an analyst to do the work for you — this is a learning cohort, you build it yourself
You’re at $30M+ ARR with a data team — the scale is wrong, you need bespoke work

WHAT YOU’LL LEAVE WITH

Five concrete deliverables, built on your own product.

Completed analytics audit of your own product

Using the ProductQuant audit framework, you’ll run a structured assessment of your own stack. Every event reviewed, every gap sized. You’ll know exactly what’s broken and what to fix first.

Event taxonomy cleaned and documented

A complete event inventory with status, issues, and recommendations — reviewed and documented so your whole team knows what exists and how to use it.

3 decision-ready dashboards (activation, retention, churn signal)

Not sample dashboards — your activation funnel, your retention cohort chart, your churn signal view, built inside your own analytics tool. Your team can use them from day one.

First data-backed experiment designed and launched

A real experiment hypothesis formed from your audit findings, with the right metric, sample size, and success criteria. Not a template — your experiment, running in your product.

Tracking governance doc so it doesn’t break again

The process and standards your team needs to keep analytics clean as the product evolves. Who approves new events. How the taxonomy is maintained. What the naming conventions are.

THE CURRICULUM

3 weeks. 6 live sessions. Everything applied to your own product.

WEEK 1

Why Your Analytics Is Lying to You

SESSION 1

The 6 ways analytics silently breaks

Double-firing, identity stitching failures, attribution gaps, consent misconfiguration, event taxonomy drift, governance collapse. What each one looks like in the data, how it happens, and how to detect it. Live audit walkthrough using a real stack.

SESSION 2

Audit your own stack

Students run the ProductQuant audit framework on their real product — live. We look at your events, your dashboards, your configuration. You share your screen; the cohort reviews together. You leave Session 2 knowing your top broken findings.

Async — before Week 2

Complete the event audit worksheet. Document every event in your product: status (working, broken, missing), issues, recommendations. Bring your top 3 broken findings to Week 2.

WEEK 2

Building Decision-Ready Dashboards

SESSION 3

Activation analytics

Defining your real aha moment — not “logged in” or “completed onboarding” but the specific in-product action that predicts whether a user stays. Building the funnel that shows when users actually get value. How to measure time-to-value and why it matters more than activation rate.

SESSION 4

Retention and churn signals

The 3 in-product behaviours that predict churn 60 days out. Not NPS, not support tickets — specific usage patterns you can see in your event data today. Building the cohort charts that surface them.

Async — before Week 3

Build your activation funnel and one retention chart in your own analytics tool. Screenshot and share in the cohort Slack for feedback before Session 5.

WEEK 3

Running Your First Data-Backed Experiment

SESSION 5

Experiment design

Forming a hypothesis from your audit findings. Choosing the right primary metric. Calculating sample size. The most common statistical errors B2B SaaS teams make when running experiments — and how to avoid them.

SESSION 6

Reading results and making the call

When is a result actionable? What do you do when it’s inconclusive? How to turn experiment learnings into roadmap input. How to communicate results to stakeholders who don’t understand p-values.

Async — before Session 6

Submit your experiment design doc for feedback before the final session. Jake reviews each one and leaves comments. Session 6 opens with a walkthrough of common issues across the cohort.

THE WORK

Real outcomes from the analytics approach behind this cohort.

HEALTHCARE SAAS

>99%

PHI exposure reduced after analytics audit

90%+

analytics cost reduction after stack consolidation

Three-tool analytics stack consolidated to PostHog. Events that were silently sending PHI to third-party tools caught and fixed. Cost dropped by more than 90%.

B2B SAAS — FEATURE PRIORITY

43%

actual frequency of Feature #2 (team believed 88%)

2×

gap between belief and reality, found by auditing data

Feature #2 was the team’s second priority. The audit found only 43% of users actually used it — against the 88% the team believed. Roadmap corrected before the next sprint.

FORMAT

Live, small-cohort, applied to your real product.

Duration

3 weeks

6 live sessions, 2×/week, 75 minutes each

Async work

~2 hrs/week

Worksheets and builds applied to your own product, reviewed by Jake before the next session

Cohort size

12 seats max

Small enough that everyone gets airtime. Jake reviews every async submission personally.

Platform

Zoom + Slack

Live sessions on Zoom. Async work and cohort discussion in a private Slack channel.

Timezone

GMT-friendly

Sessions scheduled to work for EU and US East. Exact times confirmed with cohort on registration.

Recording

All sessions

Every session recorded. Access for 12 months after the cohort ends.

WHO’S TEACHING

Jake McMahon — ProductQuant

Jake McMahon

8+ years building growth systems inside B2B SaaS · Behavioural Psychology + Big Data (Masters)

The audit framework you run in Week 1 is the same one I use for every client engagement. The dashboards you build in Week 2 are the same dashboards I’ve built for healthcare SaaS, HR platforms, and growth-stage B2B products.

This isn’t a course built from a template. It’s built from the specific work of diagnosing analytics that doesn’t work and fixing it — then distilling the approach into something you can apply to your own product in three weeks.

Sessions are small on purpose. I review every async submission. If your event taxonomy is broken, I’ll tell you what’s wrong with it specifically — not generically.

Questions.

Or get in touch →

Which analytics tools does this work with? +

PostHog, Mixpanel, and Amplitude are the primary tools covered. The audit framework and dashboard process apply to any event-based analytics tool. If you’re on a different platform, get in touch before registering.

Do I need to share my analytics data with the cohort? +

You share what you’re comfortable sharing. Most participants share their screen during live sessions showing dashboards and event lists, but no raw user data or PII is shared with the group.

What if I can’t make a live session? +

All sessions are recorded. You can submit async work and questions even if you miss a session. That said, the live review format is where most of the value is — plan to attend at least 4 of the 6.

When is the next cohort? +

Dates are confirmed when enough waitlist registrations are in. Join the waitlist and you’ll get first access to cohort dates, with no obligation to enroll.

Is this on Maven? +

The cohort may be listed on Maven. Joining the waitlist here guarantees access regardless of platform, and may include early-cohort pricing.