Industry-Specific Metrics: SaaS, E-commerce & Marketplaces

Two companies. Same revenue. $10M ARR.

Company A - Traditional SaaS:

• 100 customers paying $100K/year
• Churn: 5% annually
• Growth: 20% YoY

Valuation: $50M (5x revenue)

Company B - SaaS with Expansion:

• 100 customers started at $50K/year
• Churn: 5% annually (same as Company A)
• But… existing customers now paying average $120K
• Net Revenue Retention: 120%
• Growth: 35% YoY

Valuation: $200M (20x revenue)

Same starting point. Same number of customers. Same churn rate.

But Company B worth 4x more.

Why?

Company B understands its industry-specific metrics:

• Expansion MRR
• Net Revenue Retention (NRR)
• Negative churn
• Quick Ratio

Company A only tracks basic metrics:

• Total revenue
• Customer count
• Churn rate

This is why industry context matters.

A 70% gross margin is:

• ✅ Amazing for e-commerce
• ⚠️ Concerning for SaaS
• ❌ Terrible for pure software

A 5% monthly churn is:

• ✅ Excellent for SMB SaaS
• ⚠️ Acceptable for consumer subscription
• ❌ Catastrophic for enterprise SaaS

Let’s learn the metrics that matter most for each business model.

Part 1: Why Industry Context Changes Everything

Same metric, different meaning:

Example: 50% Growth Rate

For a startup (Year 1):

• $0 → $1M = 50% monthly growth
• Verdict: Too slow, not venture-scale

For scale-up (Year 5):

• $20M → $30M = 50% annual growth
• Verdict: Excellent, ready for IPO

For mature company (Year 15):

• $500M → $750M = 50% growth
• Verdict: Extraordinary, market-dominating

Example: 30% Gross Margin

This is why you need industry-specific benchmarks.

Part 2: SaaS Metrics Bible

SaaS has the most developed metric frameworks because:

1. Predictable recurring revenue
2. Clear cohort behavior
3. Expansion opportunities
4. Long-term value creation

1. Quick Ratio - The Health Score

Quick Ratio measures how fast you’re growing vs. churning.

$$ \text{Quick Ratio} = \frac{\text{New MRR} + \text{Expansion MRR}}{\text{Churned MRR} + \text{Contraction MRR}} $$

Example:

Month: January

• New MRR: $50K (new customers)
• Expansion MRR: $20K (upsells, add-ons)
• Churned MRR: $15K (lost customers)
• Contraction MRR: $5K (downgrades)

$$ \text{Quick Ratio} = \frac{$50K + $20K}{$15K + $5K} = \frac{$70K}{$20K} = 3.5 $$

What it means:

• For every $1 you lose, you gain $3.50
• Rule of Thumb:
  • < 1: Losing more than gaining (crisis)
  • 1-2: Growing but struggling
  • 2-4: Healthy growth
  • > 4: Excellent growth efficiency

Why Quick Ratio > Traditional Growth Rate:

Traditional view:

• Company A: +$50K MRR (10% growth)
• Company B: +$50K MRR (10% growth)
• Look the same!

Quick Ratio view:

Company A:

• New: $40K, Expansion: $20K, Churn: $10K
• Quick Ratio: 6.0 (healthy!)

Company B:

• New: $55K, Expansion: $5K, Churn: $10K
• Quick Ratio: 6.0 (but relying on new customers only)

Company C:

• New: $80K, Expansion: $5K, Churn: $35K
• Quick Ratio: 2.4 (churn problem!)

All have same net growth, but health is very different.

2. Net Revenue Retention (NRR) - The Gold Standard

NRR measures revenue retention + expansion from existing customers.

$$ \text{NRR} = \frac{\text{Starting MRR} + \text{Expansion MRR} - \text{Churned MRR} - \text{Contraction MRR}}{\text{Starting MRR}} \times 100% $$

Example: January Cohort

Starting MRR (January): $100,000

By next January (12 months later):

• Expansion MRR: $20,000 (upsells)
• Churned MRR: $10,000 (lost customers)
• Contraction MRR: $5,000 (downgrades)

$$ \text{NRR} = \frac{$100K + $20K - $10K - $5K}{$100K} \times 100% = 105% $$

Interpretation:

• 100% NRR: Breaking even (churn = expansion)
• > 100% NRR: Negative churn (expansion > churn) 🚀
• < 100% NRR: Losing revenue from cohort

Benchmarks by company type:

Real examples:

• Snowflake: 158% NRR (incredible!)
• Datadog: 130% NRR
• Slack (at IPO): 143% NRR
• Zoom: 140% NRR

Why NRR > 100% is magical:

Scenario: 110% NRR, 0% new customer growth

You grow 10% annually without acquiring a single new customer!

This is why investors love high NRR:

• Proves product value (customers expand)
• Reduces dependency on new sales
• Compounds over time
• More predictable than new bookings

3. Gross Revenue Retention (GRR) - The Floor

GRR measures retention WITHOUT expansion.

$$ \text{GRR} = \frac{\text{Starting MRR} - \text{Churned MRR} - \text{Contraction MRR}}{\text{Starting MRR}} \times 100% $$

Using same example:

$$ \text{GRR} = \frac{$100K - $10K - $5K}{$100K} \times 100% = 85% $$

Why GRR matters:

• Shows product stickiness independent of upsells
• Can’t hide churn behind expansion
• Floor for retention

Benchmarks:

Relationship: NRR vs GRR

$$ \text{NRR} = \text{GRR} + \text{Expansion Rate} $$

Example scenarios:

Scenario B is a red flag:

• Same NRR as Scenario A
• But losing 25% of customers annually
• Heavy reliance on upsells to existing customers
• What happens when expansion saturates?

4. Logo Retention vs Revenue Retention

Two different retention measures:

Logo Retention: $$ \text{Logo Retention} = \frac{\text{Customers at End}}{\text{Customers at Start}} \times 100% $$

Revenue Retention (GRR): $$ \text{Revenue Retention} = \frac{\text{Revenue Retained}}{\text{Starting Revenue}} \times 100% $$

These can diverge:

Example: Enterprise SaaS

• Start: 100 customers, $1M MRR
• End: 90 customers, $1.1M MRR
• Logo retention: 90%
• Revenue retention: 110%

Why?

• Lost 10 small customers ($50K total)
• Remaining 90 expanded by $150K
• Result: Revenue up despite losing customers

When to focus on each:

5. Expansion MRR - The Growth Engine

Types of expansion:

1. Upsell: Higher tier plan
2. Cross-sell: Additional products
3. Seats: More users
4. Usage: Consumption-based growth

Expansion MRR calculation:

$$ \text{Expansion MRR %} = \frac{\text{Expansion MRR}}{\text{Starting MRR}} \times 100% $$

Example breakdown:

Target: 2-3% monthly expansion MRR

Real company examples:

6. CAC Payback Period - Speed to Profitability

$$ \text{CAC Payback (months)} = \frac{\text{CAC}}{\text{Monthly Revenue per Customer} \times \text{Gross Margin %}} $$

Example:

• CAC: $12,000
• Monthly ARPU: $1,000
• Gross margin: 80%

$$ \text{Payback} = \frac{$12,000}{$1,000 \times 0.80} = 15 \text{ months} $$

Benchmarks:

Why it matters:

• Cash flow impact
• Risk exposure (customers can churn before payback)
• Growth efficiency

7. Magic Number - Sales Efficiency

Magic Number measures sales & marketing efficiency.

$$ \text{Magic Number} = \frac{\text{Net New ARR (current quarter)} \times 4}{\text{Sales & Marketing Spend (previous quarter)}} $$

Example:

• Q1 S&M spend: $500K
• Q2 net new ARR: $150K

$$ \text{Magic Number} = \frac{$150K \times 4}{$500K} = 1.2 $$

Interpretation:

• < 0.5: Inefficient, slow growth
• 0.5 - 0.75: Reasonable, optimize further
• 0.75 - 1.0: Good efficiency
• > 1.0: Excellent, scale aggressively

Decision framework:

Part 3: E-commerce Playbook

E-commerce metrics focus on:

1. Conversion efficiency
2. Transaction economics
3. Repeat behavior
4. Customer lifetime patterns

1. Conversion Funnel - Every Step Matters

Typical e-commerce funnel:

Calculate conversion at each stage:

$$ \text{Conversion Rate} = \frac{\text{Orders Completed}}{\text{Website Visitors}} \times 100% $$

$$ \text{Conversion} = \frac{2,400}{100,000} \times 100% = 2.4% $$

Benchmarks by industry:

Micro-conversions matter:

2. Average Order Value (AOV) - Revenue per Transaction

$$ \text{AOV} = \frac{\text{Total Revenue}}{\text{Number of Orders}} $$

Example:

• Revenue: $500,000
• Orders: 10,000

$$ \text{AOV} = \frac{$500,000}{10,000} = $50 $$

Ways to increase AOV:

AOV by channel:

3. Cart Abandonment Rate - The Revenue Leak

$$ \text{Cart Abandonment Rate} = \frac{\text{Carts Created} - \text{Orders Completed}}{\text{Carts Created}} \times 100% $$

Example:

• Carts created: 10,000
• Orders completed: 3,000

$$ \text{Abandonment} = \frac{10,000 - 3,000}{10,000} \times 100% = 70% $$

Average cart abandonment: 70% across all industries

Top reasons for abandonment:

Recovery tactics:

ROI of cart abandonment campaigns:

Example:

• 10,000 abandoned carts/month
• AOV: $100
• Potential revenue: $1M
• Recovery rate: 12% (with email campaign)
• Recovered revenue: $120K/month
• Campaign cost: $5K/month
• Net gain: $115K/month

4. Customer Repeat Rate - Lifetime Value Indicator

$$ \text{Repeat Purchase Rate} = \frac{\text{Customers with 2+ Orders}}{\text{Total Customers}} \times 100% $$

Example:

• Total customers: 50,000
• Customers with 2+ orders: 15,000

$$ \text{Repeat Rate} = \frac{15,000}{50,000} \times 100% = 30% $$

Benchmarks by business type:

Cohort repeat purchase analysis:

Tracking by cohort reveals:

• Repeat purchase velocity
• Long-term retention patterns
• When to intervene with campaigns

5. Customer Acquisition Cost (CAC) by Channel

E-commerce CAC varies dramatically by channel:

Blended CAC calculation:

$$ \text{Blended CAC} = \frac{\text{Total Marketing Spend}}{\text{New Customers Acquired}} $$

Example:

• Google Ads: $20K → 400 customers (CAC: $50)
• Facebook: $15K → 250 customers (CAC: $60)
• Email: $2K → 200 customers (CAC: $10)
• Total: $37K → 850 customers

$$ \text{Blended CAC} = \frac{$37,000}{850} = $43.50 $$

6. LTV:CAC Ratio for E-commerce

Target LTV:CAC ratio: 3:1 minimum

Example:

• CAC: $50
• AOV: $80
• Gross margin: 40% ($32 profit per order)
• Repeat purchase rate: 30%
• Average customer orders: 2.5

$$ \text{LTV} = $32 \times 2.5 = $80 $$

$$ \text{LTV:CAC} = \frac{$80}{$50} = 1.6:1 $$

Verdict: Below 3:1, need improvement

Options to improve:

1. Reduce CAC (better targeting)
2. Increase AOV (bundling, upsells)
3. Increase repeat rate (loyalty program)
4. Improve margins (pricing, COGS)

Part 4: Marketplace Math

Marketplaces are unique:

• Two-sided (supply AND demand)
• Network effects
• Take rate business model
• Liquidity is critical

1. GMV vs Revenue - Know the Difference

GMV = Gross Merchandise Value

• Total value of transactions
• Before taking platform fee

Revenue = Platform’s cut

• Take rate × GMV
• Actual money to the platform

$$ \text{Revenue} = \text{GMV} \times \text{Take Rate} $$

Example: Uber ride

• Ride fare (GMV): $20
• Uber take rate: 25%
• Uber revenue: $5
• Driver payout: $15

Why GMV can be misleading:

Company A:

• GMV: $100M
• Take rate: 5%
• Revenue: $5M

Company B:

• GMV: $50M
• Take rate: 20%
• Revenue: $10M

Company B has half the GMV but double the revenue!

2. Take Rate - The Platform’s Cut

$$ \text{Take Rate} = \frac{\text{Platform Revenue}}{\text{GMV}} \times 100% $$

Benchmarks by marketplace type:

What influences take rate:

Take rate optimization:

Initial: Low take rate to grow supply/demand

Growth: Gradually increase as network effects strengthen

Scale: Optimize take rate per segment

Example: Uber

• Launch: 5% take rate (grow driver supply)
• Growth: 15% take rate (balance supply/demand)
• Scale: 20-25% (optimize by market, surge pricing)

3. Liquidity - The Marketplace Health Metric

Liquidity = Matching efficiency

$$ \text{Liquidity} = \frac{\text{Listings that Transacted in X Days}}{\text{Total Active Listings}} \times 100% $$

Example: Rental marketplace

• Active listings: 10,000 properties
• Properties rented in 30 days: 7,000

$$ \text{30-Day Liquidity} = \frac{7,000}{10,000} \times 100% = 70% $$

Benchmarks:

Why liquidity matters:

High liquidity:

• Buyers find what they want fast
• Sellers transact quickly
• Network effects strengthen
• Retention improves

Low liquidity:

• Buyers leave empty-handed
• Sellers abandon platform
• Negative spiral begins

4. Supply/Demand Ratio - The Balance

$$ \text{S/D Ratio} = \frac{\text{Active Supply Units}}{\text{Active Demand Units}} $$

Example: Rideshare in a city

• Active drivers: 1,000
• Riders requesting: 800

$$ \text{S/D Ratio} = \frac{1,000}{800} = 1.25 $$

Interpretation:

• < 1: Supply constrained (prices high, wait times low)
• = 1: Balanced
• > 1: Demand constrained (prices low, wait times high)

Optimal S/D ratio varies:

Dynamic balancing:

• Surge pricing (Uber): Increase demand-side price when S/D < 1
• Incentives (DoorDash): Bonus for drivers when S/D < 1
• Promotions (Airbnb): Discounts to stimulate demand when S/D > 4

5. Network Density - Geographic Liquidity

For location-based marketplaces:

$$ \text{Network Density} = \frac{\text{Active Supply Units}}{\text{Geographic Area}} $$

Example: Rideshare city zones

Why density matters:

• Affects wait times
• Determines service quality
• Influences unit economics

Uber’s strategy:

1. Launch in dense downtown (easiest to achieve liquidity)
2. Expand to suburbs (maintain quality)
3. Skip rural areas (can’t achieve density)

6. Frequency and Engagement

$$ \text{Monthly Active Rate} = \frac{\text{Users Transacting This Month}}{\text{Total Users}} \times 100% $$

Benchmarks:

High-frequency marketplaces (food delivery) have:

• Lower CAC payback (faster usage)
• Stronger habits
• Better data for recommendations
• More upsell opportunities

Low-frequency marketplaces (travel) have:

• Longer CAC payback
• Need great retention tactics
• Rely on occasional high-value transactions

Part 5: Benchmarking Tables - What “Good” Looks Like

SaaS Benchmarks by Stage

E-commerce Benchmarks by Business Model

Marketplace Benchmarks by Type

Part 6: Your Metrics Dashboard by Stage

Pre-Revenue (Building Product)

Focus on:

• ✅ User engagement (DAU/MAU)
• ✅ Activation rate (% completing key action)
• ✅ Feature usage depth
• ❌ Don’t worry about: Revenue metrics yet

Example dashboard:

• Signups per week: 500
• Activation rate: 40%
• Weekly active users: 200
• Feature X usage: 60% of active users

Early Revenue ($0-1M ARR)

Focus on:

• ✅ Unit economics (does one customer/transaction make money?)
• ✅ CAC per channel
• ✅ Basic LTV calculation
• ✅ Gross margin
• ❌ Don’t worry about: Efficiency ratios yet

Example dashboard:

• Monthly revenue: $50K
• Customers: 25
• ARPU: $2K
• CAC: $3K (6-month payback)
• Gross margin: 70%

Growth Stage ($1-10M ARR)

Focus on:

• ✅ CAC payback period
• ✅ LTV:CAC ratio
• ✅ Retention cohorts
• ✅ Quick Ratio (SaaS) or Repeat Rate (E-commerce)
• ✅ Burn rate and runway

Example dashboard:

• ARR: $5M
• Net new ARR: $150K/month
• CAC payback: 14 months
• LTV:CAC: 3.2:1
• NRR: 105%
• Burn: $200K/month
• Runway: 18 months

Scale Stage ($10M+ ARR)

Focus on:

• ✅ Efficiency metrics (Magic Number, Rule of 40)
• ✅ Expansion revenue
• ✅ Sales productivity
• ✅ ROIC
• ✅ Path to profitability

Example dashboard:

• ARR: $50M
• Growth rate: 40%
• Operating margin: 0% (breakeven)
• Rule of 40: 40% ✓
• NRR: 115%
• CAC payback: 10 months
• Magic Number: 1.1

Part 7: Red Flags Checklist

🚨 Universal Red Flags (Any Business)

🚨 SaaS Red Flags

🚨 E-commerce Red Flags

🚨 Marketplace Red Flags

Part 8: Key Takeaways - Industry-Specific Wisdom

For SaaS:

1. NRR > 100% is the holy grail — grow without new customers
2. Quick Ratio > 4 = healthy growth
3. CAC payback < 12 months for efficient scaling
4. GRR shows true retention — expansion can mask churn
5. Magic Number > 0.75 before scaling sales

For E-commerce:

1. Repeat rate = everything — one-time buyers are expensive
2. Conversion rate improvements compound forever
3. AOV increases are fastest path to profitability
4. LTV:CAC > 3:1 minimum for sustainable growth
5. Cart abandonment recovery is low-hanging fruit

For Marketplaces:

1. GMV ≠ Revenue — take rate matters more
2. Liquidity is life — match supply and demand fast
3. Balance S/D ratio in every geographic market
4. Network effects take time — expect J-curve
5. Frequency drives value — high-frequency marketplaces have better economics

Universal Truth:

Context matters more than absolute numbers.

• Know your industry benchmarks
• Track the right metrics for your stage
• Compare to similar businesses, not all businesses

Series Navigation

Previous: Valuation & Investment Math

Full Series: Business Math Series

Your Action Plan

1. Identify your business model:

• SaaS → Focus on retention, expansion, efficiency
• E-commerce → Focus on conversion, AOV, repeat rate
• Marketplace → Focus on liquidity, take rate, balance

2. Set up your dashboard:

• 5-7 core metrics for your industry
• Track weekly (not monthly)
• Cohort-based when possible

3. Benchmark against your stage:

• Early revenue → Unit economics
• Growth → Efficiency ratios
• Scale → Profitability path

4. Find your red flags early:

• LTV:CAC ratio
• Retention/churn metrics
• Burn rate and runway

5. Optimize the right metrics:

• Focus on 1-2 metrics per quarter
• A/B test improvements
• Measure, iterate, repeat

Further Resources

SaaS:

• SaaS Metrics 2.0 by David Skok
• Andreessen Horowitz’s 16 Startup Metrics
• ChartMogul Blog

E-commerce:

• Shopify’s E-commerce Benchmarks
• Baymard Institute (UX & conversion research)
• Retention Science Blog

Marketplaces:

• Marketplace 100 by a16z
• Bill Gurley’s marketplace essays
• Lenny’s Newsletter (marketplace deep dives)

Congratulations! You’ve completed the Business Math Series. You now have the frameworks, formulas, and benchmarks to:

• Evaluate any business model
• Calculate the metrics that matter
• Make data-driven decisions
• Predict success before scaling

Remember: Math doesn’t lie. Measure what matters. Scale what works. 📊

Full Series: Business Math Series