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This skill helps you build and scale profitable SaaS by orchestrating pricing, retention, and growth with data-driven decision making.

npx playbooks add skill openclaw/skills --skill saas

Review the files below or copy the command above to add this skill to your agents.

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SKILL.md
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---
name: SaaS
description: Build and scale profitable software-as-a-service with viral growth, retention, and monetization strategies.
metadata: {"clawdbot":{"emoji":"💎","os":["linux","darwin","win32"]}}
---

# SaaS Rules

## Work Orchestration
Route requests to specialized agents:
- Pricing/packaging → analyst + product manager agents
- Churn analysis → analyst agent
- Growth loops → marketing + product agents
- Technical architecture → developer + architect agents
- Sales motion → sales agent

Run financial models for any monetization decision.

## The Only Metrics That Matter
- MRR and MRR growth rate — everything else is vanity
- Net Revenue Retention (NRR) — >100% means you grow without new customers
- CAC payback period — months to recover acquisition cost
- Churn rate — monthly for SMB, annual for enterprise

If NRR < 100%, fix retention before spending on acquisition.

## Pricing
- Price on value delivered, not cost to serve — 10x value = room for 3x price
- Annual plans with discount capture cash and reduce churn
- Three tiers: free/trial, growth, scale — anchoring works
- Raise prices on new customers first, grandfather existing — test elasticity
- Usage-based pricing aligns incentives but complicates forecasting

## Viral Growth Loops
- Product must have inherent shareability — bolted-on referrals don't work
- Powered-by badges, shared workspaces, public outputs — user success = distribution
- Viral coefficient > 1 means exponential growth — measure invites per user
- Time-to-value must be minutes, not days — slow activation kills virality
- Free tier is marketing spend — model it as CAC

## Retention Over Acquisition
- Reducing churn 5% often beats increasing acquisition 20%
- Onboarding determines retention — first 7 days predict everything
- Track activation metrics, not just signups — what action predicts retention?
- Reactivation campaigns for dormant users before they churn
- Exit surveys reveal fixable problems — ask churned users why

## Go-to-Market
- Self-serve for low ACV (<$5k), sales-assist for mid, enterprise sales for high
- Product-led growth: let users experience value before sales contact
- Content + SEO compounds — paid acquisition doesn't
- Founder-led sales until you close 50 deals — then hire sales

## Scaling
- Automate customer success before hiring more CSMs
- Feature parity across plans kills upsell — differentiate meaningfully
- Platform/API unlocks enterprise deals and stickiness
- Multi-tenant architecture from day one — single-tenant doesn't scale

## Common SaaS Mistakes
- Launching lifetime deals for quick cash — destroys unit economics
- Adding features for single customers — product becomes unmaintainable
- Discounting to close deals — trains customers to wait for discounts
- Building enterprise features before having enterprise sales
- Ignoring expansion revenue — upsell is cheaper than new logo

## Financial Model
- Model cohorts, not aggregates — behavior differs by signup month
- Unit economics must work at scale, not just with founder magic
- Cash runway = survival — SaaS is capital intensive before profitable
- Gross margin > 70% or you're not really SaaS

Overview

This skill helps founders and product teams build and scale profitable SaaS businesses using proven strategies for pricing, retention, viral growth, and monetization. It codifies the metrics, go-to-market motions, and operational rules needed to turn product usage into predictable revenue. The guidance focuses on measurable outcomes: MRR growth, NRR, CAC payback, and cohort economics.

How this skill works

The skill routes problems to specialized playbooks (pricing, churn analysis, growth loops, architecture, and sales) and runs financial cohort models to evaluate monetization choices. It prioritizes retention-first interventions and offers tactical rules for pricing tiers, viral features, onboarding funnels, and scaling operational processes. Recommendations are actionable and metric-driven so teams can test changes quickly.

When to use it

  • Designing pricing tiers, discounts, or usage-based plans
  • Diagnosing growth slowdowns or high churn
  • Building product-led viral features or referral mechanics
  • Planning go-to-market motion for self-serve, mid-market, or enterprise
  • Preparing to scale customer success and operational processes

Best practices

  • Optimize retention before increasing acquisition spend; fix NRR < 100% first
  • Price on delivered value and use annual plans to capture cash and reduce churn
  • Make time-to-value minutes, not days, and instrument activation metrics
  • Model cohorts and unit economics, not just aggregate revenue
  • Differentiate plan features to enable upsell and avoid parity across tiers

Example use cases

  • Running a pricing experiment: test new rates for new customers while grandfathering existing ones
  • Reducing churn: redesign onboarding and measure first-7-day activation signals
  • Building a viral loop: embed shareable outputs and measure invites per user
  • GT M strategy: choose self-serve for low ACV, sales-assist for mid-market, enterprise sales for high ACV
  • Scaling operations: automate routine customer success workflows before hiring more CSMs

FAQ

What single metric should I watch first?

MRR and its growth rate are primary; combine with NRR to understand organic expansion versus net churn.

When should I add enterprise features?

Only after you have repeatable sales to enterprise-sized customers; building ahead of demand wastes resources.