10-reverse-kpi-global

# Reverse KPI Calculation (Global)

Calculate marketing budget by working backward from revenue goal — or forward from available spend to expected revenue. Universal math; currency and benchmark numbers vary per region (US/EU/SEA/LATAM).

---

## For newbies — Read this first

If you've never run a reverse KPI calc:

1. **Reverse KPI = working backward from a goal.** Instead of "I'll spend $5K and see what happens," you say "I want $50K in revenue, so I need X impressions, Y leads, Z customers — therefore the budget is $W."
2. **It works in two directions:**
   - Backward: Revenue target → required spend (when you have a goal)
   - Forward: Available spend → expected revenue (when you have a budget)
3. **You always run 3 scenarios.** Pessimistic (worst case), Realistic (base case), Optimistic (best case). One number is dangerous — three numbers force you to stress-test.
4. **Conversion rates are the leverage.** Small changes in conversion (e.g., 50% → 55%) cascade up the funnel and change your budget significantly.
5. **Currency matters.** A 5% margin in USD is different in EUR, BRL, or VND. Always pick the right region variant for your benchmarks.
6. **Don't trust round numbers.** "100 leads" is suspicious — real funnels produce odd numbers like 87 or 213.
7. **Time horizon affects budget.** A $50K monthly target needs different planning than a $50K annual target. Always specify the period.

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## Step 0 — Read context + select region variant

Before calculation:

1. **Read `.agents/product-marketing-context-global.md`** — get product, AOV, region, currency, target market.
2. **Pick region variant for benchmark conversion rates and CPM/CPL:**
   - `variants/01-us.md` — USD, US benchmarks
   - `variants/02-eu.md` — EUR/GBP, EU benchmarks
   - `variants/03-sea.md` — USD/local, SEA benchmarks
   - `variants/04-latam.md` — USD/BRL/MXN, LATAM benchmarks
3. **Confirm direction:** Reverse (revenue → spend) or Forward (spend → revenue)?

### Information gathering

Ask user up to 4 questions:

1. **What is the goal?** Revenue target $X/month? Or available budget $Y to allocate?
2. **Product/service and AOV?** Average order value or deal size in your currency.
3. **Industry and current channel mix?** Industry niche? Channels currently running? Any existing CPL/CPM data?
4. **Campaign duration?** 1 month? Quarter? 6 months? Phased?

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## Two calculation directions

### Direction 1 — Reverse: Revenue → Budget

Use when: "I want to hit $200K/month — how much ad spend do I need?"

```
Revenue target
  / AOV (average order value)
  = ORDERS NEEDED
  / Booking → Customer rate
  = BOOKINGS NEEDED
  / Lead → Booking rate
  = LEADS NEEDED
  / Click → Lead rate
  = CLICKS NEEDED
  / CTR
  = IMPRESSIONS NEEDED
  × CPM / 1000
  = TOTAL AD BUDGET
```

For e-commerce (no booking step):

```
Revenue target
  / AOV
  = ORDERS NEEDED
  / Conversion rate
  = SESSIONS NEEDED (clicks)
  / CTR
  = IMPRESSIONS NEEDED
  × CPM / 1000
  = TOTAL AD BUDGET
```

For B2B (longer funnel):

```
Revenue target
  / ACV (annual contract value)
  = CUSTOMERS NEEDED
  / Win rate
  = OPPORTUNITIES NEEDED
  / SQL → Opportunity rate
  = SQL NEEDED
  / MQL → SQL rate
  = MQL NEEDED
  / Lead → MQL rate
  = LEADS NEEDED
  → continue with CPL × LEADS NEEDED = SPEND
```

### Direction 2 — Forward: Budget → Revenue

Use when: "I have $50K — how much revenue can I expect?"

```
Budget
  / CPM × 1000
  = IMPRESSIONS
  × CTR
  = CLICKS
  × Click → Lead rate
  = LEADS
  × Lead → Booking rate
  = BOOKINGS
  × Booking → Customer rate
  = ORDERS
  × AOV
  = REVENUE
```

---

## 3-Scenario sensitivity analysis (universal)

### Scenario structure

Always run three scenarios:

| Variable | Pessimistic | Realistic (Base) | Optimistic |
|----------|-------------|------------------|------------|
| CPM | Industry avg + 30% | Industry avg | Industry avg − 20% |
| Click → Lead | Industry avg − 15% | Industry avg | Industry avg + 15% |
| Lead → Booking | Industry avg − 10% | Industry avg | Industry avg + 10% |
| Booking → Customer | Industry avg − 10% | Industry avg | Industry avg + 10% |

### Reading the results

- **Pessimistic** = budget needed for safety / FX swings / first-month learning curve
- **Realistic (Base)** = the actual planning number
- **Optimistic** = aspiration target, used for stretch KPI or commission triggers

> Use Base for budget. Use Pessimistic as buffer. Use Optimistic as stretch goal.

### Sensitivity (which lever moves the budget most?)

| Variable | Base value | Change +10% | Budget change | Sensitivity |
|----------|-----------|-------------|---------------|-------------|
| CPM | [#] | +10% | +10% | **Direct 1:1** |
| CTR | [#]% | +10% | -9% | **High** |
| Click→Lead | [#]% | +10% | -9% | **High** |
| Lead→Booking | [#]% | +10% | -9% | **High** |
| Booking→Customer | [#]% | +10% | -9% | **High** |
| AOV | [#] | +10% | -9% (fewer orders needed) | **Indirect** |

### 80/20 rule

The two highest-leverage levers are usually:

1. **CPM** — controlled by creative + targeting → optimize via A/B testing
2. **Lead → Booking** — controlled by sales/CS quality → optimize via script + response speed

---

## Break-even calculation

```
Break-even orders = Fixed costs / (AOV − Variable cost per order)
Break-even days = Break-even orders / (Avg orders per day)
```

| Item | Value |
|------|-------|
| Fixed costs/month (rent, salary, tools, software) | [#] |
| Ad spend (variable, but allocated upfront) | [#] |
| Total fixed | [#] |
| AOV | [#] |
| Variable cost per order (COGS, shipping, fees) | [#] |
| Profit per order | AOV − VarCost = [#] |
| Break-even orders | Total fixed / Profit per order |
| Break-even days | BE orders / 30 |

| Result | Meaning | Action |
|--------|---------|--------|
| BE < 50% of expected orders | Safe — good margin buffer | Can scale spend |
| BE = 50–80% of expected | Tight — limited margin | Optimize cost first |
| BE > 80% of expected | Risky — easy to lose | Cut costs or raise AOV |

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## Budget alloc