Author: Iman Nazari

Iman combines user psychology, business strategy, and experimentation to uncover what drives action and improves performance. He focuses on hypothesis development, evidence-based decision making, and turning insights into changes that can be confidently tested and scaled.

11 Sept 20266 min read

Story of 74% CVR lift in 6 months for a health brand

Ten experiments found that simplifying the page often hurt conversion. The biggest wins came from resolving uncertainty around insurance, cost, and what would happen next.

11 Sept 202622 min read

Why Experimentation Is a Must-Have for Your Business

Business experimentation is more than choosing a winning page. It reveals which customer problems deserve investment, which ideas should stop, and where to commit resources with evidence.

9 Sept 202621 min read

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.

26 Aug 202618 min read

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.

25 Aug 202622 min read

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.

24 Aug 202616 min read

CRO Redesign vs Ongoing A/B Testing: Which to Start With?

A tested one-time redesign can be rational when the current experience needs a structural reset. Ongoing A/B testing creates more long-term value when each experiment produces both deployed impact and reusable customer learning. This framework shows how to choose—and why one hypothesis does not mean changing only one UI element.

21 Aug 20268 min read

How to Evaluate a CRO Agency: Business Impact vs Win Rate

A CRO agency should be judged by the complete evidence chain it creates: trustworthy measurement, explicit hypotheses, valid experiments, verified deployments, and cumulative improvement to a meaningful business outcome. Win rate, test count, and isolated uplift are useful diagnostics, but they do not prove realized business value.

19 Aug 202621 min read

Event Tracking Plan for CRO and Product Analytics

An event tracking plan is not an event-name spreadsheet. It is the contract that defines how business questions become entities, events, trigger rules, properties, identities, revenue facts, metrics, QA, and governed analytics data. This guide includes a complete paid-subscription example and downloadable Excel template.

19 Aug 202628 min read

PostHog Audit: 12 Checks Before You Trust the Data

A PostHog audit should prove more than event delivery. These 12 checks follow the full measurement chain—from ad click and identity through event semantics, purchase value, attribution, ROAS, and production governance—so you know which decisions the data can safely support.