Advertising KPIs
If every KPI exists to prompt a decision, which of your metrics prompt no action — and why are you still tracking them?
KPI Decision Map
The glory metrics (ROAS, revenue) get the attention. The collision metrics (breakdown speed, creative fatigue, attribution quality) shape reality. If you can't name the decision a metric drives, kill it.
| KPI | Raw Data Source | Decision It Prompts | Action It Triggers | Bad Data Risk |
|---|---|---|---|---|
| CPM | Ad server logs (impressions served) | Is this audience worth buying? | Shift budget between placements | Paying premium for bot traffic |
| CPC | Platform click tracking | Is traffic cost sustainable? | Adjust bids, pause expensive keywords | Optimizing toward accidental clicks |
| CTR | Impressions / clicks (platform-reported) | Does the creative resonate? | A/B test creative, refine targeting | Chasing clickbait over intent |
| CVR | Landing page + CRM events | Is the funnel converting? | Rewrite landing page, fix checkout | Attributing conversions to wrong source |
| CPA | Ad spend / CRM acquisitions | Can we afford this customer? | Kill or scale campaigns | Over/under-investing in channels |
| CPL | Form submissions + ad spend | Is lead generation efficient? | Adjust targeting, tighten qualification | Counting junk leads as pipeline |
| ROAS | Revenue (attributed) / ad spend | Is this campaign profitable? | Scale winners, kill losers | Crediting organic revenue to paid |
| LTV:CAC | Cohort revenue data + acquisition cost | Are we acquiring the right customers? | Shift from acquisition to retention | Short cohorts mask churn |
| Payback | Monthly revenue x margin / CAC | Can cash flow sustain growth? | Accelerate or throttle spend | Underestimating true CAC |
Metric Hierarchy
Business outcomes sit at the top. Everything below exists to serve them.
| Level | Metrics | What They Show |
|---|---|---|
| Business | Profit, market share | Did advertising create value? |
| Revenue | ROAS, LTV:CAC, payback | Are we making money? |
| Conversion | CVR, CPA, CPL | Are we efficient? |
| Engagement | CTR, engagement rate | Are we relevant? |
| Reach | Impressions, CPM | Are we visible? |
The trap: Optimizing reach without measuring conversion. High impressions with low conversion = wasted spend.
Funnel Stage Map
| Stage | Primary Metrics | Secondary Metrics |
|---|---|---|
| Awareness | CPM, Reach, Brand Lift | Share of Voice, Ad Recall |
| Consideration | CTR, Engagement Rate, Time on Site | Video Completion Rate, Content Downloads |
| Conversion | CVR, CPA, CPL | Form Completion Rate, Add-to-Cart Rate |
| Retention | LTV, Repeat Purchase Rate, NPS | Churn Rate, Email Engagement |
| Advocacy | Referral Rate, UGC Volume | Reviews, Social Mentions |
Traffic Metrics
CPM
(Total Ad Spend / Impressions) x 1,000
| Industry | Average CPM (2025) |
|---|---|
| Online Marketplaces | $2.71 |
| E-commerce | $11-17 |
| Finance & Insurance | $20-32 |
| SaaS / B2B | $28-42 |
| Healthcare | $36.82 |
Google Ads average: $11.12 across industries.
CPC
Total Ad Spend / Number of Clicks
| Industry | Average CPC (2025) | YoY Change |
|---|---|---|
| Online Marketplaces | $0.14 | - |
| E-commerce | $0.80-1.40 | +12.88% |
| Finance & Insurance | $1.60-3.10 | +8% |
| Software | $3.88 | - |
| SaaS / B2B | $2.40-5.20 | +15% |
| Attorneys & Legal | $8.58 | - |
| Beauty & Personal Care | - | +60.11% |
CPC increased 12.88% YoY across Google Ads. Companies using first-party data kept CPC growth below 7%.
CTR
(Clicks / Impressions) x 100
| Industry | Average CTR (2025) |
|---|---|
| Arts & Entertainment | 13.10% |
| Animals & Pets | 10.36% |
| Travel | 9.76% |
| Attorneys & Legal | 5.97% |
| E-commerce | 1.6-2.1% |
| Finance & Insurance | 0.9-1.5% |
| SaaS / B2B | 0.8-1.3% |
Google Ads average: 6.66% in 2025. Vertical video creatives see 10-18% higher CTR.
Conversion Metrics
CVR
(Conversions / Total Visitors) x 100
| Industry | Average CVR (2025) |
|---|---|
| Animals & Pets | 13.07% |
| Physicians & Surgeons | 11.08% |
| Automotive | 8.73% |
| Finance & Insurance | 5-9% |
| Apparel & Fashion | 3.99% |
Google Ads average: 7.52%. Going (travel company) changed 3 words on their CTA button — 104% increase in CVR.
CPA
Total Ad Spend / Number of Acquisitions
| Business Model | Average CPA (2025) |
|---|---|
| E-commerce | $22-38 |
| Finance & Insurance | $40-75 |
| SaaS / B2B Lead | $45-95 |
| Attorneys & Legal | $131.63 |
| B2B Average | ~$200 |
Two levers: CPA = CPC x (1/CVR). Lower what you pay per click OR improve conversion rate.
CPL
Total Ad Spend / Number of Leads
| Industry | Average CPL (2025) | YoY Change |
|---|---|---|
| All Industries | $70.11 | +5.13% |
| Restaurants & Food | $24.80 | +21.96% |
| Arts & Entertainment | $37.57 | +39.52% |
| Real Estate | $44.70 | +38.57% |
| Attorneys & Legal | $131.63 | - |
Cost per lead rose from $66.69 (2024) to $70.11 (2025).
Revenue Metrics
ROAS
Revenue Generated / Ad Spend
| Business Model | Typical ROAS |
|---|---|
| E-commerce | 3.2x - 4.1x |
| Brand campaigns | 2.0x - 3.0x |
| High-margin products | 5.0x+ |
Below 1:1 = losing money. Above 5:1 = possible underinvestment. ROAS captures attributed revenue only — brand-building won't show up here.
LTV:CAC
Customer Lifetime Value / Customer Acquisition Cost
| Ratio | Interpretation |
|---|---|
| < 1:1 | Burning money |
| 1:1 - 3:1 | Danger zone |
| 3:1 - 5:1 | Healthy |
| > 5:1 | May be under-investing |
Improving retention by 5% can increase profits by 25-95%. Omnichannel customers show 30% higher LTV.
CAC Payback
CAC / (Monthly Revenue per Customer x Gross Margin)
| Business Model | Healthy Payback |
|---|---|
| E-commerce | 1-3 months |
| SaaS | 8-12 months |
| Enterprise B2B | 12-18 months |
If payback exceeds 18 months, cash flow strangles growth.
Channel Benchmarks
| Channel | Key Metric | 2025 Benchmark |
|---|---|---|
| ROI | $36-40 per $1 spent | |
| Click-to-Open | 5.3% (true engagement metric) | |
| Welcome CVR | 2.84% | |
| Back-in-Stock CVR | 5.84% | |
| Open Rate | 42.35% (distorted by Apple Mail Privacy) | |
| Engagement Rate | 3.56% (2 posts/week optimal) | |
| Engagement Rate | 2.12% (2 posts/week optimal) | |
| Growth | +28% YoY (3-5 posts/week) | |
| TikTok | Follower Growth | Highest of all platforms (daily) |
| Google Ads | Quality Score Impact | Higher score = 50%+ CPC reduction |
| Retargeting | Opportunity | 97% of visitors leave without converting |
54% of marketing managers now prioritize engagement over vanity metrics like followers.
Measurement Triad
Best-in-class measurement combines three approaches:
| Method | Purpose | Strength | Weakness |
|---|---|---|---|
| MMM | Strategic allocation | No tracking needed, privacy-safe | Slow, aggregate level |
| MTA | Tactical optimization | Journey mapping, real-time | Requires tracking, incomplete |
| Incrementality | Causal proof | Ground truth calibration | Expensive, limited scale |
Use all three. MMM for budget allocation. MTA for daily optimization. Incrementality for validating both.
Attribution
Single-touch attribution lies. Most journeys involve multiple touchpoints.
| Model | What It Credits | Bias |
|---|---|---|
| First-touch | Top of funnel | Over-funds awareness |
| Last-touch | Bottom of funnel | Over-funds closing |
| Linear | Equal across all | Over-weights low-value |
| Time-decay | Recent touches | Under-values brand |
| W-shaped | First, middle, last | Requires sophistication |
Blockchain opportunity: Timestamped, immutable touchpoint records create transparency in attribution. Every interaction verified, not estimated.
The Fraud Tax
| Channel | Invalid Traffic Rate (2025) |
|---|---|
| Desktop Web | 19% of clicks |
| Mobile Web | 9% of clicks |
| Mobile App | 22-28% of clicks |
| CTV | 18% of traffic |
One in five clicks may not be human.
Warning Signs
| Pattern | Diagnosis | Fix |
|---|---|---|
| CTR rising, CVR falling | Wrong audience or misleading creative | Tighten targeting |
| CPC rising faster than revenue | Competitive pressure | Improve quality score, diversify |
| ROAS strong, LTV declining | Acquiring wrong customers | Shift from acquisition to retention |
| High reach, low engagement | Wasted impressions | Narrow audience, improve relevance |
| CPL dropping, pipeline flat | Lead quality problem | Score leads, not just count them |
DePIN Comparison
| Metric | Traditional Data Source | DePIN Data Source | Improvement |
|---|---|---|---|
| Location targeting | IP address, GPS estimate | GEODNET centimeter precision | 100x accuracy |
| Weather-based targeting | Regional forecast | WeatherXM hyperlocal | Real-time, block-level |
| Foot traffic | Estimated from samples | DePIN sensor network | Verified, continuous |
| Map freshness | Quarterly updates | Hivemapper real-time | Always current |
Review Checklist
- Do metrics ladder up to revenue, not vanity?
- Is attribution model appropriate for sales cycle length?
- Are you comparing against relevant industry benchmarks?
- Do you have first-party data strategy for privacy changes?
- Are you measuring incrementality, not just correlation?
- Is fraud detection part of your measurement stack?
- Do finance and marketing agree on what success means?
Context
- Data Flow — Naming system and data footprint that KPIs measure against
- Principles — What truths guide measurement
- Players — Who's measured
- Platform — Tools that generate the data
- Performance — General performance principles
Links
Questions
If every KPI exists to prompt a decision, which of your metrics prompt no action — and why are you still tracking them?
- When CPC rises 12.88% YoY but CVR stays flat, what does that tell you about the gap between traffic cost and conversion value?
- Which row in the Decision Map has the worst data quality — and is that where the most money leaks?
- If one in five clicks isn't human, what does that do to every metric that uses clicks as a denominator?
- What is the most important metric you're not tracking?