Growth Marketing Through Full-Funnel Experiments

Growth starts with knowing what to scale. We choose a North Star Metric that reflects customer value and ties to revenue, then break it down into its drivers. Then we build an AARRR funnel with real numbers to find the weakest spot.

• Acquisition, Activation, Retention, Revenue and Referral, with conversion between stages
• A breakdown of the North Star Metric into metrics you can move
• Cohort retention analysis by channel and segment
• Product analytics in Amplitude, Mixpanel or GA4

An idea the team likes and a strong hypothesis are two different things. A hypothesis has a reason grounded in data, an expected effect and a metric that tells us the result. We prioritize the backlog by impact, confidence and cost, so the tests with the most potential go first.

• The format “if we do X, metric Y will change, because Z”
• Hypothesis sources in data, interviews, session recordings and feedback
• Prioritization with ICE or RICE
• An experiment card with the test design and decision criteria

A test with too small a sample or the wrong metric leads to false conclusions, and the team ships changes that don’t work. We calculate sample size and duration in advance, pick the method for the job and read results with statistics, not by eye.

• A/B and multivariate tests for pages, onboarding and pricing
• Holdout tests to measure the long-term effect of campaigns
• Fake door tests to check demand for a feature before building it
• Pre-launch and post-launch checklists to avoid common mistakes

Acquiring a new user costs many times more than keeping an existing one. We build lifecycle messaging for every stage, from activation to reactivation, and measure it by its impact on retention and LTV, not by open rates.

• A lifecycle map from activation to engagement, retention and reactivation
• Segmentation by behavior, RFM and lifecycle stage
• Triggered email, push and in-app flows
• Frequency caps so you don’t wear out your audience