Install
$ agentstack add skill-minhnv0807-ai-business-skills-10-reverse-kpi-global ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
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Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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 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
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: minhnv0807
- Source: minhnv0807/ai-business-skills
- License: MIT
- Homepage: https://opa.business
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.