Marketing Metrics That Matter: KPIs to Track

Vanity Metrics vs. Actionable Metrics

Not all metrics are created equal:

Vanity metrics (feel good, don't drive decisions):

What they are: Numbers that look impressive but don't indicate business health

Examples:

• Total followers (10K followers, but 5 actually buy = useless)
• Impressions (1M people saw ad, but 0.01% clicked = ineffective)
• Page views (10K visits, but 99% bounced immediately = bad)
• Likes on social posts (validation, but doesn't pay bills)

Why they're dangerous:

• Create false sense of success
• Don't correlate to revenue
• Can't be optimized toward meaningful goals

Actionable metrics (inform decisions, drive improvement):

What they are: Numbers that measure progress toward business goals and can be optimized

Examples:

• Conversion rate (% visitors who buy—directly tied to revenue)
• Customer Acquisition Cost (CAC—tells you if marketing is profitable)
• Customer Lifetime Value (LTV—reveals long-term profitability)
• Return on Ad Spend (ROAS—measures campaign effectiveness)

Why they matter:

• Directly tied to business outcomes (revenue, profit)
• Can be tested and improved
• Enable strategic decisions (spend more here, cut there)

The test:

Ask: "If this number improves, does revenue increase?"

✅ Yes: Actionable metric (track it) ❌ No or unclear: Vanity metric (ignore it)

Core Marketing Metrics (Universal)

Track these regardless of business type:

1. Return on Investment (ROI) ⭐⭐⭐⭐⭐

What it measures: Profitability of marketing efforts

Formula:

ROI = (Revenue - Marketing Cost) / Marketing Cost × 100

Example:

• Spent $5,000 on ads
• Generated $20,000 revenue
• ROI = ($20,000 - $5,000) / $5,000 × 100 = 300%

Interpretation: For every $1 spent, you made $3 profit

What's good:

• Negative ROI: Losing money (stop immediately or fix)
• 0-100%: Breaking even to modest profit (okay, but optimize)
• 200%+: Strong performance (scale up)
• 500%+: Excellent (pour more budget in)

Limitations: Doesn't account for long-term value (customer might buy again)

2. Customer Acquisition Cost (CAC) ⭐⭐⭐⭐⭐

What it measures: How much it costs to acquire one customer

Formula:

CAC = Total Marketing + Sales Costs / Number of New Customers

Example:

• Marketing spend: $10,000
• Sales team salaries: $5,000
• New customers acquired: 50
• CAC = ($10,000 + $5,000) / 50 = $300

Costs one customer $300 to acquire

What's good:

• Depends on industry and product price
• Rule: CAC should be 1/3 or less of Customer Lifetime Value (LTV)
• If LTV = $1,000, CAC should be ≤ $333

Track by channel:

• Facebook Ads CAC: $250
• Google Ads CAC: $400
• Email marketing CAC: $50

Optimize: Double down on low-CAC channels

3. Customer Lifetime Value (LTV or CLV) ⭐⭐⭐⭐⭐

What it measures: Total revenue from a customer over entire relationship

Formula (simplified):

LTV = Average Purchase Value × Purchase Frequency × Customer Lifespan

Example (subscription):

• Average monthly subscription: $50
• Average customer stays: 24 months
• LTV = $50 × 24 = $1,200

Example (e-commerce):

• Average order: $75
• Orders per year: 3
• Customer lifespan: 5 years
• LTV = $75 × 3 × 5 = $1,125

What's good:

• LTV > 3x CAC: Healthy, sustainable
• LTV = CAC: Breaking even, unsustainable
• LTV < CAC: Losing money on every customer (disaster)

Strategy: Increase LTV (retention, upselling) and/or decrease CAC

4. Conversion Rate ⭐⭐⭐⭐⭐

What it measures: Percentage of people who complete desired action

Formula:

Conversion Rate = (Conversions / Total Visitors) × 100

Example:

• Website visitors: 10,000
• Purchases: 200
• Conversion Rate = (200 / 10,000) × 100 = 2%

What's good (varies by industry):

• E-commerce: 1-3% average, 5%+ excellent
• SaaS: 3-5% (trial to paid), 10%+ excellent
• Lead gen: 2-5% (visitor to lead), 10%+ excellent

Micro-conversions:

• Email signup rate
• Add-to-cart rate
• Checkout completion rate

Track conversion rates at each funnel stage, optimize bottlenecks

5. Return on Ad Spend (ROAS) ⭐⭐⭐⭐⭐

What it measures: Revenue generated per dollar spent on ads

Formula:

ROAS = Revenue from Ads / Ad Spend

Example:

• Ad spend: $2,000
• Revenue attributed to ads: $10,000
• ROAS = $10,000 / $2,000 = 5

Interpretation: For every $1 spent on ads, generated $5 revenue

What's good:

• ROAS < 1: Losing money
• ROAS = 1: Breaking even
• ROAS 2-4: Profitable (typical)
• ROAS 5+: Excellent

Note: ROAS measures revenue, not profit (still need to subtract product costs)

Awareness Metrics (Top of Funnel)

Measuring reach and discovery:

6. Impressions

What it measures: How many times your content was displayed

Use case: Brand awareness campaigns

Good for: Understanding reach potential

Limitation: Doesn't mean anyone engaged or remembered

Pair with: Engagement rate, brand lift studies

7. Reach

What it measures: Unique people who saw your content

Difference from impressions:

• Impressions: Total views (same person 3x = 3 impressions)
• Reach: Unique viewers (same person 3x = 1 reach)

Better metric than impressions (measures actual audience size)

8. Brand Awareness Lift

What it measures: Increase in people who recognize your brand

How to measure:

• Survey control group (didn't see ads): "Have you heard of [Brand]?"
• Survey exposed group (saw ads): "Have you heard of [Brand]?"
• Calculate difference (lift)

Example:

• Control: 10% awareness
• Exposed: 25% awareness
• Lift: 15 percentage points

Use: Brand campaigns where direct conversion isn't goal

Engagement Metrics (Interest Stage)

Measuring audience interaction:

9. Engagement Rate ⭐⭐⭐⭐

What it measures: How actively audience interacts with content

Formula (social media):

Engagement Rate = (Likes + Comments + Shares) / Followers × 100

Or (for individual posts):

Post Engagement Rate = (Likes + Comments + Shares) / Impressions × 100

What's good (Instagram):

• 1-3%: Average
• 3-6%: Good
• 6%+: Excellent
• 10%+: Outstanding (or very small, engaged niche)

Use: Evaluate content quality, audience relevance

10. Click-Through Rate (CTR) ⭐⭐⭐⭐⭐

What it measures: Percentage of people who clicked after seeing content

Formula:

CTR = (Clicks / Impressions) × 100

Example:

• Email sent: 10,000
• Clicks: 300
• CTR = (300 / 10,000) × 100 = 3%

What's good (varies by channel):

• Email: 2-5% average, 10%+ excellent
• Google Search Ads: 2-5%, 8%+ excellent
• Facebook Ads: 0.9% average, 2%+ good
• Display Ads: 0.05-0.1%

Higher CTR = more relevant/compelling content

11. Bounce Rate ⭐⭐⭐⭐

What it measures: Percentage who leave site after viewing one page

Formula:

Bounce Rate = (Single-Page Sessions / Total Sessions) × 100

What's good:

• Blog: 65-90% (normal—people read one article, leave)
• E-commerce: 20-45% (higher is concerning)
• Landing page: 30-50%

High bounce rate signals:

• Irrelevant traffic (targeting wrong audience)
• Slow page load
• Poor content/design
• Misleading ad copy

Pair with: Time on page (low time + high bounce = bad)

12. Time on Page / Session Duration ⭐⭐⭐⭐

What it measures: How long people engage with content

What's good:

• Blog: 2-3 minutes (depends on length)
• Product page: 1-2 minutes
• Homepage: 30 seconds - 1 minute

High time on page + low bounce = engaged audience

Conversion Metrics (Bottom of Funnel)

Measuring sales and leads:

13. Lead Conversion Rate ⭐⭐⭐⭐⭐

What it measures: Percentage of leads who become customers

Formula:

Lead Conversion Rate = (Customers / Leads) × 100

Example:

• Leads generated: 500
• Customers: 50
• Lead Conversion Rate = (50 / 500) × 100 = 10%

What's good:

• B2B: 2-5% (longer sales cycles)
• B2C: 5-15%

Optimize: Lead quality (better targeting), sales process (follow-up speed, nurturing)

14. Cart Abandonment Rate ⭐⭐⭐⭐⭐

What it measures: Percentage who add to cart but don't purchase

Formula:

Cart Abandonment = (Carts Created - Purchases) / Carts Created × 100

Example:

• Carts created: 1,000
• Purchases: 300
• Abandonment = (1,000 - 300) / 1,000 × 100 = 70%

Industry average: 69.8% (yes, very high)

Why people abandon:

• Unexpected shipping costs
• Required account creation
• Complicated checkout
• Just browsing (not ready to buy)

Reduce through: Free shipping thresholds, guest checkout, abandoned cart emails, transparent pricing

15. Average Order Value (AOV) ⭐⭐⭐⭐⭐

What it measures: Average amount spent per transaction

Formula:

AOV = Total Revenue / Number of Orders

Example:

• Revenue: $50,000
• Orders: 500
• AOV = $50,000 / 500 = $100

Increase through:

• Upselling ("Upgrade to Pro for $20 more")
• Cross-selling ("Customers also bought...")
• Bundles
• Free shipping minimum ("Spend $50 for free shipping")

5% increase in AOV = 5% revenue increase (without acquiring more customers)

Retention Metrics (Post-Purchase)

Measuring loyalty and repeat business:

16. Customer Retention Rate ⭐⭐⭐⭐⭐

What it measures: Percentage of customers who remain customers over time

Formula:

Retention Rate = ((Customers at End - New Customers) / Customers at Start) × 100

Example (monthly):

• Customers start of month: 1,000
• Customers end of month: 1,100
• New customers acquired: 200
• Retention = ((1,100 - 200) / 1,000) × 100 = 90%

What's good:

• SaaS: 90-95% monthly (5-10% churn)
• E-commerce: 20-30% (repeat purchase within year)

Why it matters: Retaining customers costs 5-25x less than acquiring new ones

17. Churn Rate ⭐⭐⭐⭐⭐

What it measures: Percentage of customers who stop being customers

Formula:

Churn Rate = (Customers Lost / Total Customers at Start) × 100

Example:

• Customers start: 1,000
• Customers lost: 50
• Churn = (50 / 1,000) × 100 = 5%

Inverse of retention: 5% churn = 95% retention

What's good:

• SaaS: <5% monthly, <60% annually
• E-commerce: Varies widely

Reduce churn: Better onboarding, customer success, product improvements

18. Repeat Purchase Rate ⭐⭐⭐⭐

What it measures: Percentage of customers who buy again

Formula:

Repeat Purchase Rate = (Customers Who Purchased 2+ Times / Total Customers) × 100

Example:

• Total customers: 1,000
• Customers with 2+ purchases: 300
• Repeat Rate = (300 / 1,000) × 100 = 30%

What's good:

• E-commerce: 20-40%
• Subscription: Should be 80%+ (or they churn)

19. Net Promoter Score (NPS) ⭐⭐⭐⭐

What it measures: Customer satisfaction and likelihood to recommend

How it works:

• Survey: "How likely are you to recommend us to a friend?" (0-10 scale)
• Promoters (9-10): Love you, will refer
• Passives (7-8): Satisfied but not enthusiastic
• Detractors (0-6): Unhappy, might leave negative reviews

Formula:

NPS = % Promoters - % Detractors

Example:

• 100 responses: 60 promoters, 20 passives, 20 detractors
• NPS = 60% - 20% = 40

What's good:

• 50+: Excellent
• 30-50: Good
• 0-30: Room for improvement
• Negative: Crisis (fix immediately)

Channel-Specific Metrics

Track these for individual channels:

Email Marketing:

• Open rate: 15-25% average
• CTR: 2-5%
• Unsubscribe rate: <0.5% (higher = poor targeting/content)
• Spam complaint rate: <0.1%

Social Media:

• Follower growth rate: (New Followers / Total Followers) × 100
• Engagement rate: As calculated above
• Share of voice: Your mentions vs. competitor mentions

SEO/Organic Search:

• Organic traffic: Sessions from search engines
• Keyword rankings: Position for target keywords (top 3 = best)
• Domain Authority (DA): Moz metric (40+ is good)
• Backlinks: Quality > quantity

Paid Search (Google Ads):

• Quality Score: 7-10 (lowers cost-per-click)
• Cost Per Click (CPC): Varies by keyword competitiveness
• Conversion rate: 3-5% average

Setting Up Your Marketing Dashboard

Track metrics systematically:

Tools:

Free:

• Google Analytics: Website traffic, conversions, behavior
• Google Search Console: SEO performance
• Facebook/Instagram Insights: Social media metrics
• Email platform analytics: (Mailchimp, ConvertKit)

Paid:

• Google Data Studio: Custom dashboards (free but connects to paid tools)
• HubSpot: All-in-one marketing analytics
• Tableau: Advanced visualization

Create weekly/monthly dashboard:

Key sections:

1. Revenue metrics:

• Total revenue
• Revenue by channel
• MRR/ARR (for subscriptions)

2. Acquisition:

• New customers
• CAC by channel
• Traffic sources

3. Conversion:

• Conversion rates (overall, by channel)
• AOV

4. Retention:

• Retention rate
• Churn rate
• NPS

5. Channel performance:

• Email: Open rate, CTR
• Social: Engagement, follower growth
• Paid ads: ROAS, CPC

Review schedule:

Daily: Campaign performance (if running active ads) Weekly: Traffic, conversions, channel performance Monthly: Full analysis, trends, strategy adjustments Quarterly: Goal review, strategic pivots

Using Metrics to Make Decisions

Data → Insight → Action:

Example decision framework:

Observation: Facebook ads ROAS dropped from 5 to 2

Questions:

• What changed? (creative fatigue, audience saturation, competition?)
• When did it drop? (gradual or sudden?)
• Which campaigns affected? (all or specific ones?)

Actions:

• Refresh ad creative
• Test new audiences
• Adjust targeting
• If persists, reallocate budget to better-performing channel

Observation: Email open rate declining (25% → 15%)

Questions:

• List health? (need to clean inactive subscribers?)
• Subject line quality? (test new approaches)
• Send frequency? (emailing too often?)

Actions:

• Segment list, remove inactive
• A/B test subject lines
• Reduce frequency, see if improves

Track actionable metrics over vanity metrics: ROI (revenue minus cost divided by cost), CAC (total marketing cost divided by new customers), LTV (average purchase × frequency × lifespan—should be 3x+ CAC), conversion rate (conversions divided by visitors—e-commerce 1-3% average), and ROAS (ad revenue divided by ad spend—5+ excellent). Measure awareness (impressions, reach), engagement (CTR, bounce rate, time on page), conversions (cart abandonment 70% average, AOV), and retention (churn rate under 5% monthly, NPS 30-50+ good). Use Google Analytics, create dashboards reviewing weekly metrics, monthly trends, quarterly strategy. Transform data into decisions: identify drops, ask why, test solutions, reallocate budgets.