Illustration of a flask and stopwatch representing a timed A/B test

Amin HeshmatiJune 9, 20251 min read

Webinar Join Rate A/B Test: Do Shorter Waits Boost Attendance?

A two-minute post-registration schedule produced a higher reported webinar-join rate than a wait of Subscribe or log in to read…

A two-minute post-registration schedule produced a higher reported webinar-join rate than a wait of

Subscribe or log in to read the rest of this content.

Continue reading

Iman Nazari+1

Sep 9, 202619 min

Confidence vs PostHog: Which Experimentation Platform Fits Your Team?

An evidence-based Confidence vs PostHog comparison covering data architecture, statistical methods, guardrails, governance, pricing, tradeoffs, and a practical evaluation plan.

Diagram of a growth decision loop from next-lever decision to intervention, action, and validation, linked by an implementation evidence chain for revenue, identity, attribution, event data, and QA.

Iman Nazari

Aug 26, 202618 min

PostHog Implementation for Growth Lever Teams

A useful PostHog implementation is not an SDK installation or feature tour. It is a decision system connecting business-aware events, identity, acquisition, revenue, experiments, and QA so a growth team can identify a lever, act on it, and validate the result.

Diagram showing a true value metric passing through a calibration layer to an operational primary metric.

Iman Nazari

Aug 25, 202620 min

A/B Testing Metrics: Choose the Primary Metric Closest to Profit

The best A/B testing metric is usually the measurable outcome closest to incremental contribution per eligible visitor, user, or account. This guide separates true decision metrics, operational primaries, leading indicators, guardrails, and diagnostics—then maps ecommerce, subscription, pricing, lead-generation, marketplace, and cost-changing experiments to the metrics that should actually determine the winner.