Skene
Playbooks

Product-led growth playbooks

Opinionated, reusable PLG playbooks. Start with job-to-be-done playbooks when you are solving a specific problem, or segment playbooks when you need a rigid spine for a particular motion like B2B SaaS, enterprise, or developer tools.

PLG playbook collections

By job-to-be-done

Use when you have a concrete job such as reducing time-to-value or improving activation. Each playbook includes problem context, system approach, execution steps, metrics, and failure modes.

Browse job-to-be-done playbooks ↓

By segment

Use when you need a rigid PLG spine for a specific motion (for example B2B SaaS, enterprise, or developer tools). Each segment page defines constraints, activation model, explicit product signals, routing logic, expansion mechanics, and failure modes.

Browse segment playbooks →

PLG playbooks by job-to-be-done

Use these playbooks when you have a specific problem to solve, like slow time-to-value, weak activation, or fragile self-serve retention. Each one includes problem context, a system view, concrete steps, metrics, and common failure modes.

If you need step-by-step instructions for the Skene app itself (workspaces, sources, widgets, and analytics), read the product docs alongside these playbooks.

Onboarding
Activation
Time-to-value

Design onboarding, milestones, and instrumentation so new users reach a real outcome in hours instead of weeks.

Job-to-be-done: Shorten the time from signup to first meaningful outcome.

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Activation
Onboarding
Metrics

Define a precise activation event, redesign onboarding around it, and instrument progress so you can systematically lift activation.

Job-to-be-done: Increase the share of new users and accounts that reach a meaningful activation milestone within a defined window.

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Onboarding
Instrumentation
Foundations

Use proxy signals, qualitative insight, and a staged instrumentation roadmap to move from guesses to measurable onboarding.

Job-to-be-done: Design and improve onboarding journeys when product analytics are missing, incomplete, or unreliable.

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Retention
Loops
Expansion

Move beyond one-time activation by designing product loops that create habitual, compounding usage in self-serve accounts.

Job-to-be-done: Keep activated users coming back and growing usage without heavy human intervention.

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Prioritize a narrow set of journeys, metrics, and automations so a small team can operate PLG without burning out.

Job-to-be-done: Design a sustainable PLG motion when you have limited engineering, data, and customer success capacity.

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Create routing rules that use product signals to decide when sales or success should step in, instead of treating all engaged accounts the same.

Job-to-be-done: Decide when automation is no longer enough and human intervention actually helps.

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Metrics
Failure modes
Activation

Stress-test your activation definition and metrics so you can distinguish real customer success from shallow, one-off wins.

Job-to-be-done: Identify users who hit activation events but never reach durable value.

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Use product signals and targeted plays to bring back accounts that looked promising but quietly stalled before they grew.

Job-to-be-done: Re-engage accounts that showed strong early signals but plateaued before expansion or deeper adoption.

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Add expansion mechanics that feel natural inside the product so accounts can grow usage and spend without heavy, blocking sales touchpoints.

Job-to-be-done: Grow account value while preserving self-serve momentum.

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Shift your instrumentation from purely lagging outcomes to a small set of predictive product signals that give you early warning and opportunity.

Job-to-be-done: Choose signals that predict success before churn or stagnation appears.

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Failure modes
Retention
Operations

Add guardrails around releases and pricing changes so you can see and respond quickly when PLG metrics regress.

Job-to-be-done: Detect and mitigate drops in usage caused by releases, pricing changes, or UX shifts before they become permanent.

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Protect learning and trust by keeping some flows manual until you understand user behavior and edge cases well enough to automate safely.

Job-to-be-done: Decide what not to automate when PLG maturity is low.

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Introduce intermediate milestones, proxy value, and scaffolding so users stay engaged while waiting for full outcomes.

Job-to-be-done: Create momentum when real value only appears days or weeks later.

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Activation
Segmentation
Lifecycle

Define different activation journeys and success criteria for new, returning, and mature accounts so each gets the right path to value.

Job-to-be-done: Stop treating first-time users and returning accounts as the same activation problem.

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Strategy
Failure modes

Use clear criteria to decide when to rebalance from pure PLG toward hybrid or sales led motions without abandoning what works.

Job-to-be-done: Recognize when a pure PLG motion is the wrong tool for the next stage.

Open playbook →

PLG playbooks by segment

Segment playbooks give you a stable PLG spine for a given motion. Use them alongside job-to-be-done playbooks when you are designing activation, signals, and routing rules for a specific product type.

Make the product the primary growth engine for B2B SaaS: reliably move new accounts from signup to a defined activation event in under an hour, then route high-fit, high-usage accounts to sales based on product-qualified signals instead of MQLs.

Team size: Early- to growth-stage B2B SaaS companies with small product, growth, and success teams (or one person wearing all three hats).

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Design a self-serve B2B PLG wedge where a small team can reach a measurable activation event quickly, then use product-qualified signals to decide which accounts stay self-serve and which get sales-assist.

Team size: B2B companies with mixed self-serve and sales-led motions, often spanning SMB, mid-market, and the lower end of enterprise.

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Use a self-serve SaaS PLG motion to get new users to a clearly-defined first-success event in minutes, then convert that success into repeat usage and predictable upgrade paths tied to real work.

Team size: Small to mid-size SaaS teams where product, engineering, and perhaps one growth generalist drive most of the go-to-market motion.

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Optimize PLG for developer tools around a fast install + first meaningful artifact, then use workspace, team, and environment signals to decide when to move from experimentation to paid, production usage.

Team size: Developer tools teams selling to individual developers and small squads, often with lean or no dedicated sales and success teams.

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Use a self-serve PLG wedge to prove value with a small team in real work, then let product usage signals and governance needs drive the transition into enterprise sales cycles and governed contracts.

Team size: Companies selling into mid-market and enterprise where deals span multiple teams, security, and procurement stakeholders.

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Let indie developers reach a concrete first-success outcome in minutes with minimal setup, then earn upgrades through limits and features that clearly map to more shipped work or revenue.

Team size: Solo developers and very small teams building and shipping quickly, often with limited time and budget for tooling.

Open segment playbook →