Product Analytics and A/B Tests Developers Can Trust
Experimentation & Product Analytics: leave with an event taxonomy, funnel and cohort reports, and a powered A/B test with guardrails.
Not scheduled yet — no date, time or fee fixed. The most-voted topic is hosted next.
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Learn this topic with a mentor
Don't want to wait for the webinar? Pick how you'd like help. Nothing is paid now — you see the fee before anything is booked.
- Bring your own work — code, campaign, report or plan
- Mentor matched to this topic
- Time, format and fee confirmed by email first
What this session would cover
Proposed outline — the mentor finalises the agenda once this topic is scheduled.
- 1Why experimentation & product analytics matters — the common problem: Analytics events are inconsistent and experiments are called before they're significant.
- 2Core concepts in plain language: Hypotheses, success metrics, event taxonomies, funnels, cohorts, activation
- 3Going further: retention, controlled experiments, A/B testing, statistical power, guardrail metrics, causal inference
- 4Framework walkthrough: Double Diamond, Jobs to Be Done, Lean Startup (Build–Measure–Learn), North Star Metric
- 5Practical workflow, built live: An event taxonomy, funnel and cohort reports, and a powered A/B test with guardrails.
- 6How to measure it: Activation rate, Retention cohort, Experiment velocity, Validated assumptions
- 7An illustrative case (a fictional example, not a client result), then live Q&A on your own situation
Who it's for
- • Developers building their own products
- • Product-minded engineers and founders
- • Operations teams automating workflows
You'd leave with
- An event taxonomy, funnel and cohort reports, and a powered A/B test with guardrails.
- A working understanding of Double Diamond and Jobs to Be Done
- A short list of measures to track: Activation rate, Retention cohort, Experiment velocity
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