8 articles
Product AnalyticsA practical framework for selecting a north star metric that predicts retention, guides product decisions, and aligns teams around the outcome that matters most to your business.
PLGA practical guide to instrumenting the aha moment in PLG SaaS — covering event schema design, property standards, account-level aggregation, and the most common instrumentation failures.
Product AnalyticsA practical guide to designing an event naming convention for SaaS product analytics that stays consistent as the product grows, enables reliable cohort analysis, and prevents the event sprawl that makes data unusable.
Product AnalyticsA practical guide to building funnel visualizations that correctly represent conversion and retention, avoid the most common anti-patterns, and connect each funnel stage to the metrics that drive product decisions.
Product AnalyticsA structured framework for building a metric hierarchy from north star to team-level inputs, connecting OKRs to business outcomes and preventing the confusion between metrics that teams control and metrics that result from their work.
Product AnalyticsA complete guide to designing a product analytics instrumentation layer that captures intent, enables cohort analysis, and scales without becoming an unmaintainable event sprawl over time.
AnalyticsLearn how to use product usage data to predict SaaS churn 30–60 days before cancellation — including the 6 key signals, a usage health score formula, and an intervention playbook that reduces churn by 25–40%.
ActivationLearn the data-driven process for discovering your SaaS product's aha moment — the specific event that empirically predicts long-term retention — and how to redesign onboarding around it.