10-reverse-kpi-global — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited 10-reverse-kpi-global (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
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).
If you've never run a reverse KPI calc:
Before calculation:
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 benchmarksAsk user up to 4 questions:
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 BUDGETFor e-commerce (no booking step):
Revenue target
/ AOV
= ORDERS NEEDED
/ Conversion rate
= SESSIONS NEEDED (clicks)
/ CTR
= IMPRESSIONS NEEDED
× CPM / 1000
= TOTAL AD BUDGETFor 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 = SPENDUse 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
= REVENUEAlways 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% |
Use Base for budget. Use Pessimistic as buffer. Use Optimistic as stretch goal.
| 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 |
The two highest-leverage levers are usually:
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 |
| 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 |
| 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 |
| 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 % |
| 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 |
| 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 |
Before delivering reverse KPI report:
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.