Map the funnel

A defining and beautiful attribute of PLG is the product’s deep integration throughout the entire customer funnel. Our first step is mapping the funnel’s stages and growth milestones (or “aha moments”) that users should experience at each stage.

Data foundation

Once the funnel is mapped, we build a model that serves as our scorecard for identifying high-leverage opportunities and measuring initiative outcomes. This model relies on minimum-viable data infrastructure, typically including product analytics with robust event tracking and a unified customer database that consolidates product, marketing, sales, and support data.

Picking a focus area

To maximize impact and compound both outcomes and learnings, focusing experimentation on a single area is most effective. Common focus areas include product-led acquisition, activation, monetization, or engagement. We help you make this decision by analyzing data (identifying your funnel's rate-limiting step), assessing traffic volume, and aligning with your overall product vision.

Equipping PLG toolkit

Once your focus area is defined, we'll help you implement the essential toolkit for running effective experiments and delivering exceptional customer experiences. This typically includes an experimentation platform and lifecycle marketing system, plus any specialized tools specific to your focus area

Assembling the growth team

Once your focus area and metrics are defined, we help build a dedicated team to own them. The ideal PLG experimentation team is a cross-functional "pod" with both the capability and autonomy to run complete experiments independently. These pods typically include a growth product manager, designer, engineer, and data analyst, with additional focus area specialists when necessary. We can either help you recruit internal talent or provide our ready-to-go experimentation teams.

Experimentation processes + communication

Having a systematic process is essential for sustainability and scalability of an experimentation program. We've developed a proprietary scrum-based framework that helps teams generate hypotheses, prioritize experiments, conduct controlled tests, and share learnings. If you build an internal experimentation pod, we can train your team to implement this methodology.