Monetization

MONETIZATION - Do Produto ao Revenue

Selective Reading Rule

Start with:

• references/senior-master-standard.md
• references/usage-routing.md
• references/quality-checklist.md

Then load only the inherited docs, scripts, assets, or examples that match the user's actual task.

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

pip install stripe

## Ou

npm install stripe

## 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

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)

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)

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

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

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)

Sinais De Churn Iminente

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)

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

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

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

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

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 analysis

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.