Finance
monetization - Claude MCP Skill
Estrategia e implementacao de monetizacao para produtos digitais - Stripe, subscriptions, pricing experiments, freemium, upgrade flows, churn prevention, revenue optimization e modelos de negocio SaaS.
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Documentation
SKILL.md# MONETIZATION - Do Produto ao Revenue
## Overview
Estrategia e implementacao de monetizacao para produtos digitais - Stripe, subscriptions, pricing experiments, freemium, upgrade flows, churn prevention, revenue optimization e modelos de negocio SaaS. Ativar para: integrar Stripe, criar planos de assinatura, pricing strategy, upgrade/downgrade, webhook de pagamento, trial gratuito, churn, LTV/CAC, unit economics, modelo de negocio.
## When to Use This Skill
- When you need specialized assistance with this domain
## Do Not Use This Skill When
- The task is unrelated to monetization
- A simpler, more specific tool can handle the request
- The user needs general-purpose assistance without domain expertise
## How It Works
> Price is what you pay. Value is what you get. - Warren Buffett
> A monetizacao perfeita captura valor proporcional ao valor entregue.
---
## A Regra De Ouro
Usuarios pagam quando:
1. O produto resolve um problema real (need)
2. A solucao e melhor que alternativas (differentiation)
3. O preco e percebido como justo (value perception)
4. O momento de cobranca e natural (timing)
## Erros Classicos
- Cobranca antes de mostrar valor (kill activation)
- Preco muito baixo (sinaliza baixa qualidade)
- Planos demais (paralisia de escolha)
- Trial sem carta de credito (baixa conversao)
- Churn invisivel (sem alertas de cancelamento iminente)
---
## Setup Inicial
```bash
pip install stripe
## Ou
npm install stripe
```
```python
## Config.Py
import stripe
import os
stripe.api_key = os.environ["STRIPE_SECRET_KEY"]
STRIPE_WEBHOOK_SECRET = os.environ["STRIPE_WEBHOOK_SECRET"]
PLANS = {
"free": None,
"pro": os.environ["STRIPE_PRICE_PRO"],
"business": os.environ["STRIPE_PRICE_BIZ"],
}
```
## Criar Customer E Subscription
```python
def create_customer(email: str, name: str, user_id: str) -> str:
customer = stripe.Customer.create(
email=email,
name=name,
metadata={"user_id": user_id}
)
return customer.id
def create_subscription(customer_id: str, price_id: str, trial_days: int = 14):
subscription = stripe.Subscription.create(
customer=customer_id,
items=[{"price": price_id}],
trial_period_days=trial_days,
payment_behavior="default_incomplete",
expand=["latest_invoice.payment_intent"],
)
return {
"subscription_id": subscription.id,
"client_secret": subscription.latest_invoice.payment_intent.client_secret,
"status": subscription.status
}
```
## Checkout Session (Recomendado Para Conversao)
```python
def create_checkout_session(
customer_id: str,
price_id: str,
success_url: str,
cancel_url: str,
trial_days: int = 14
) -> str:
session = stripe.checkout.Session.create(
customer=customer_id,
mode="subscription",
line_items=[{"price": price_id, "quantity": 1}],
subscription_data={"trial_period_days": trial_days},
success_url=success_url + "?session_id={CHECKOUT_SESSION_ID}",
cancel_url=cancel_url,
allow_promotion_codes=True,
)
return session.url
```
## Customer Portal (Self-Service)
```python
def create_portal_session(customer_id: str, return_url: str) -> str:
session = stripe.billing_portal.Session.create(
customer=customer_id,
return_url=return_url,
)
return session.url
```
## Webhook - Processar Eventos
```python
from fastapi import Request, HTTPException
import stripe
async def stripe_webhook(request: Request):
payload = await request.body()
sig_header = request.headers.get("stripe-signature")
try:
event = stripe.Webhook.construct_event(
payload, sig_header, STRIPE_WEBHOOK_SECRET
)
except ValueError:
raise HTTPException(status_code=400, detail="Invalid payload")
except stripe.error.SignatureVerificationError:
raise HTTPException(status_code=400, detail="Invalid signature")
handlers = {
"customer.subscription.created": handle_subscription_created,
"customer.subscription.updated": handle_subscription_updated,
"customer.subscription.deleted": handle_subscription_deleted,
"invoice.payment_succeeded": handle_payment_succeeded,
"invoice.payment_failed": handle_payment_failed,
"customer.subscription.trial_will_end": handle_trial_ending,
}
handler = handlers.get(event["type"])
if handler:
await handler(event["data"]["object"])
return {"status": "ok"}
```
## Verificar Status Da Subscription
```python
def get_subscription_status(customer_id: str) -> dict:
subscriptions = stripe.Subscription.list(
customer=customer_id,
status="all",
limit=1
)
if not subscriptions.data:
return {"tier": "free", "status": "none"}
sub = subscriptions.data[0]
return {
"tier": get_tier_from_price(sub.items.data[0].price.id),
"status": sub.status,
"trial_end": sub.trial_end,
"current_period_end": sub.current_period_end,
"cancel_at_period_end": sub.cancel_at_period_end,
}
```
---
## Framework De Pricing Para Saas
**Metodo 1: Value-Based Pricing (Recomendado)**
```
1. Calcule o valor economico entregue ao usuario
Ex: produto economiza 2h/semana = R$ 200/mes de valor
2. Capture 10-30% do valor criado
Ex: R$ 29/mes = 14% do valor
3. Valide com pesquisa de willingness-to-pay
4. Teste 3 price points (A/B test)
```
**Metodo 2: Competitive Anchor**
```
Referencia: ChatGPT Plus = $20/mes (R$ 100)
Anchor: Notion = R$ 32/mes
Posicao: Pro = R$ 29/mes (mais barato que ChatGPT, similar ao Notion)
Mensagem: Tudo que o ChatGPT faz, por voz no Alexa
```
## Psicologia De Pricing
```
R$ 29/mes (nao R$ 30 - efeito do digito esquerdo)
Plano anual com desconto claro: R$ 249/ano (economize R$ 99)
Destaque no plano que voce quer vender (visual hierarchy)
Ancoragem: mostra o plano caro primeiro
Trial sem cartao para ativacao, com cartao para retencao
Badge Mais popular no plano middle
```
## Estrutura De Planos (3 E O Numero Certo)
| Feature | Free | Pro | Business |
|---------------------|---------|------------|------------|
| Preco | Gratis | R$ 29/mes | R$ 99/mes |
| Conversas/mes | 50 | Ilimitado | Ilimitado |
| Memoria | 7 dias | 1 ano | Permanente |
| Board especialistas | Nao | Sim | Sim |
| Multi-usuarios | Nao | Nao | Ate 10 |
| API access | Nao | Nao | Sim |
| Suporte | Nao | Email | Priority |
---
## Sinais De Churn Iminente
```python
CHURN_SIGNALS = {
"high_risk": [
"nao logou nos ultimos 14 dias",
"uso caiu >70% em 2 semanas",
"abriu cancelamento mas nao concluiu",
"ticket de suporte aberto sem resolucao",
],
"medium_risk": [
"nao logou em 7 dias",
"uso caiu >40%",
"nao completou onboarding",
"nunca usou feature core",
]
}
```
## Sequencia Anti-Churn
```
Dia 0: Usuario nao usa por 7 dias
-> Email: Sentimos sua falta. O que aconteceu?
Dia 3: Sem resposta
-> Push/Email: case study de usuario similar com sucesso
Dia 7: Nao voltou
-> Email: oferta especial (20% off por 3 meses)
Dia 14: Trial expirando
-> In-app modal + email urgente: Sua conta vai dormir em 3 dias
Dia 30: Cancelou
-> Offboarding email: Lamentamos ver voce ir.
-> 3 meses depois: reativacao com novidades
```
## Exit Survey (Obrigatorio)
```python
CANCELLATION_REASONS = [
"Muito caro",
"Nao uso o suficiente",
"Falta funcionalidade X",
"Encontrei alternativa melhor",
"Problemas tecnicos",
"Outro"
]
## Falta Feature -> Roadmap + Notificacao Quando Lancar
```
---
## Calculos Essenciais
```python
def calculate_unit_economics(
mrr: float,
customers: int,
new_customers: int,
churned: int,
cac_total: float,
):
arpu = mrr / customers
churn_rate = churned / customers
ltv = arpu / churn_rate
cac = cac_total / new_customers
ltv_cac = ltv / cac
months_to_recover_cac = cac / arpu
return {
"ARPU": f"R$ {arpu:.2f}",
"Churn Rate": f"{churn_rate*100:.1f}%",
"LTV": f"R$ {ltv:.0f}",
"CAC": f"R$ {cac:.0f}",
"LTV/CAC": f"{ltv_cac:.1f}x",
"Payback": f"{months_to_recover_cac:.1f} meses",
"Status": "Saudavel" if ltv_cac > 3 else "Otimizar"
}
```
## Benchmarks Saas B2C Brasil
| Metrica | Ruim | Ok | Bom | Excelente |
|-----------------------|-------|--------|--------|-----------|
| Churn Mensal | >7% | 5-7% | 2-5% | <2% |
| LTV/CAC | <1x | 1-3x | 3-5x | >5x |
| Payback | >18m | 12-18m | 6-12m | <6m |
| Conversao trial->pago | <3% | 3-8% | 8-15% | >15% |
| MoM Growth | <5% | 5-10% | 10-20% | >20% |
---
## Dashboard De Revenue (Metricas Diarias)
```
MRR atual: R$ XX.XXX
New MRR (novos assinantes): +R$ X.XXX
Expansion MRR (upgrades): +R$ XXX
Contraction MRR (downgrades): -R$ XXX
Churned MRR (cancelamentos): -R$ XXX
Net New MRR: +/- R$ XXX
ARR (Annualized): R$ XX.XXX x 12
Churn Rate: X.X%
Net Revenue Retention: XXX% (meta: >100%)
```
## Automacao De Revenue Com Stripe
```python
async def check_usage_and_upsell(user_id: str, usage: dict):
if usage["conversations_this_month"] >= 45:
await send_upgrade_prompt(
user_id=user_id,
message="Voce esta usando 90% do seu limite. Faca upgrade para Pro.",
cta_url=f"/upgrade?utm=usage-limit"
)
```
---
## 7. Comandos Rapidos
| Comando | Acao |
|----------------------|------------------------------------------|
| /stripe-setup | Configura Stripe do zero |
| /pricing-analysis | Analisa estrategia de pricing atual |
| /churn-playbook | Sequencia anti-churn personalizada |
| /unit-economics | Calcula LTV/CAC e saude financeira |
| /upgrade-flow | Design do fluxo de upgrade |
| /revenue-dashboard | Template de dashboard de revenue |
| /trial-optimization | Otimiza conversao de trial |
## Best Practices
- Provide clear, specific context about your project and requirements
- Review all suggestions before applying them to production code
- Combine with other complementary skills for comprehensive analysis
## Common Pitfalls
- Using this skill for tasks outside its domain expertise
- Applying recommendations without understanding your specific context
- Not providing enough project context for accurate analysis
## Related Skills
- `analytics-product` - Complementary skill for enhanced analysis
- `growth-engine` - Complementary skill for enhanced analysis
- `product-design` - Complementary skill for enhanced analysis
- `product-inventor` - Complementary skill for enhanced analysisSignals
Information
- Repository
- arlenagreer/claude_configuration_docs
- Author
- arlenagreer
- Last Sync
- 5/10/2026
- Repo Updated
- 5/7/2026
- Created
- 4/10/2026
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