10 reverse kpi global
Skill minhnv0807/ai-business-skills/skills/en/10-reverse-kpi-global
Reverse KPI calculation for global marketing budgets — work backward from revenue goal to required spend. Universal math, currency-specific per region (US/EU/SEA/LATAM). 3-scenario sensitivity analysis (pessimistic/realistic/optimistic). Trigger: 'reverse KPI', 'budget calculation', 'KPI breakdown', 'marketing budget plan', 'campaign budget'.From its SKILL.md
npx -y skills add minhnv0807/ai-business-skills --skill 10-reverse-kpi-globalAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its file declares
Copied from the file, not written here
The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
10.0 KB, ~2.6k tokens by cl100k_base, as published. Nobody here has run it
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:
- 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."
- 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)
- 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.
- Conversion rates are the leverage. Small changes in conversion (e.g., 50% → 55%) cascade up the funnel and change your budget significantly.
- Currency matters. A 5% margin in USD is different in EUR, BRL, or VND. Always pick the right region variant for your benchmarks.
- Don't trust round numbers. "100 leads" is suspicious — real funnels produce odd numbers like 87 or 213.
- Time horizon affects budget. A $50K monthly target needs different planning than a $50K annual target. Always specify the period.
Step 0 — Read context + select region variant
Before calculation:
- Read
.agents/product-marketing-context-global.md— get product, AOV, region, currency, target market. - Pick region variant for benchmark conversion rates and CPM/CPL:
variants/01-us.md— USD, US benchmarksvariants/02-eu.md— EUR/GBP, EU benchmarksvariants/03-sea.md— USD/local, SEA benchmarksvariants/04-latam.md— USD/BRL/MXN, LATAM benchmarks
- Confirm direction: Reverse (revenue → spend) or Forward (spend → revenue)?
Information gathering
Ask user up to 4 questions:
- What is the goal? Revenue target $X/month? Or available budget $Y to allocate?
- Product/service and AOV? Average order value or deal size in your currency.
- Industry and current channel mix? Industry niche? Channels currently running? Any existing CPL/CPM data?
- Campaign duration? 1 month? Quarter? 6 months? Phased?
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:
- CPM — controlled by creative + targeting → optimize via A/B testing
- 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 |
Budget allocation by phase
| Phase | % of budget | Duration | Goal | Primary KPI |
|---|---|---|---|---|
| Teaser / Awareness | 15% | Week 1 | Curiosity, brand build | Reach, video views, saves |
| Soft launch | 20% | Week 2 | Test creative, first leads | CPL, lead, A/B test data |
| Full launch | 40% | Weeks 3–4 | Scale winners, drive sales | ROAS, orders, revenue |
| Maintenance + retarget | 25% | Week 5+ | Retarget, nurture, repeat | CPA, LTV, retention |
Example allocation (budget $80K/month)
| Phase | % | Amount | Days | Daily |
|---|---|---|---|---|
| Teaser | 15% | $12K | 7 | $1,714/day |
| Soft launch | 20% | $16K | 7 | $2,286/day |
| Full launch | 40% | $32K | 14 | $2,286/day |
| Maintenance | 25% | $20K | balance | depends on remaining days |
Channel allocation principles
- Proven channel → 60-70% of budget. Don't dilute by spreading evenly.
- New / test channel → 15-20% of budget. Enough to gather data, not enough to bleed cash.
- Retarget → 10-15% of budget. Highest ROAS — target previously engaged users.
- Switch channels when ROAS < 2x for 2 weeks. Don't wait too long.
ROI projection timeline
| Phase | Duration | Expectation | Track |
|---|---|---|---|
| Testing | Weeks 1–2 | No orders yet, testing creative + audience | CPM, CTR, CPL |
| First results | Weeks 3–4 | First orders, ROAS still low | First orders, leads |
| Optimization | Month 2 | ROAS improving, stabilizing | ROAS, CPA |
| Scale | Month 3+ | Stable ROAS, controlled budget increases | ROAS held, revenue up |
| Mature | Month 6+ | Self-running, enough data to forecast | LTV, retention, organic % |
Rules of thumb
| Rule | Explanation |
|---|---|
| First 2 weeks lose money | Learning cost — don't panic, don't pause |
| Base ROAS achieved by month 2 | Month 1 is testing, don't judge ROAS yet |
| Scale budget max 20%/week | Faster scaling = performance drops, CPM rises |
| ROAS drops 30% when scaling | Normal — wider audience = lower conv rate |
| Retarget ROAS 2-3x prospecting | Always allocate budget for retargeting |
Cross-reference
| Need | Skill |
|---|---|
| Full marketing plan first | 00-marketing-plan-global |
| Current performance to inform calc | 03-performance-eval-global |
| Competitive spend benchmarks | 08-competitor-research-global |
| Customer insight to refine conv rates | 09-customer-insight-global |
| Post-campaign data analysis | 13-data-analysis-global |
Quality checklist
Before delivering reverse KPI report:
- Region variant selected — currency and benchmarks match user's market
- Direction confirmed (reverse vs forward)
- Industry-specific conversion rates used (not generic averages)
- All 3 scenarios calculated (pessimistic, base, optimistic)
- Sensitivity analysis identifies top 2 levers + how to improve them
- Break-even calculated with risk grade
- Phase allocation has specific timeline
- Channel allocation matches industry mix
- ROI timeline realistic (no "ROAS 5x in week 1" promises)
- Total budget consistent across phase + channel breakdowns
- Seasonality noted if campaign falls on Q4/Tet/Carnival/Black Friday
- Currency conversion documented if cross-border
What ships with it: 4 files
32.2 KB alongside SKILL.md
variants/
- 01-us.md6.8 KB
- 02-eu.md8.1 KB
- 03-sea.md8.0 KB
- 04-latam.md9.3 KB
Gives 0 of the 12 instructions most marketing audience skills give in ~2.6k tokens
Counted across 690 of the 894 authors here whose files we hold, read 2026-08-07
- Apply Poppins font to headingsin 41 of 690, across 6 files
- Apply Lora font to body textin 41 of 690, across 6 files
- Use Arial fallback for headingsin 39 of 690, across 4 files
- Use Georgia fallback for body textin 39 of 690, across 4 files
- Maintain text hierarchy and formattingin 39 of 690, across 4 files
- Use accent colors for non-text shapesin 38 of 690, across 3 files
- Use RGB values for precise color matchingin 38 of 690, across 3 files
- Use brand colors for primary text and backgroundsin 36 of 690, across 1 file
- Read product marketing context file before asking questions, starting, or auditingin 35 of 690, across 23 files
- Use active voice instead of passive voicein 26 of 690, across 10 files
- Implement or generate appropriate JSON-LD structured datain 24 of 690, across 17 files
- Prioritize clarity over clevernessin 22 of 690, across 8 files
Said here and by no other author read
- ask user four information questions
- calculate budget backward from revenue goal
- calculate revenue forward from available spend
- run three scenarios for sensitivity analysis
- select the correct region variant
- use industry-specific conversion rates
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.