LTV to CAC Ratio¶

Definition¶

LTV to CAC Ratio measures the relationship between the Lifetime Value (LTV) of a customer and the Customer Acquisition Cost (CAC). It helps evaluate how much revenue a customer generates over their lifetime compared to the cost of acquiring them.

Description¶

LTV to CAC Ratio is a key indicator of customer acquisition efficiency and long-term profitability, reflecting how the lifetime value of a customer compares to the cost of acquiring them. It answers the essential question: Are we spending the right amount to acquire customers who deliver value over time?

The relevance and interpretation of this metric vary:

In SaaS, a 3:1 ratio is a common benchmark for sustainable growth
In eCommerce, it indicates repeat purchase potential versus acquisition spend
In freemium models, it measures conversion ROI over user lifecycle

A high ratio (4:1+) may signal strong retention and monetization, while a low ratio (1:1 or less) suggests overspending or weak lifetime value. By segmenting by channel, persona, or plan type, you can identify where to optimize spend, adjust pricing, or refine retention plays.

LTV to CAC Ratio informs:

Strategic decisions, like budget allocation, GTM resourcing, and pricing model updates
Tactical actions, such as tightening acquisition campaigns or improving onboarding
Operational improvements, including sales enablement, customer success scaling, and CAC control

Key Drivers¶

These are the main factors that directly impact the metric. Understanding these lets you know what levers you can pull to improve the outcome

Customer Retention and Expansion: The longer customers stay and the more they expand, the higher your LTV.
Acquisition Channel Cost and Efficiency: Expensive, low-converting channels inflate CAC and lower your ratio.
Pricing vs. Support Load: Low prices paired with high cost-to-serve drag LTV, especially in SMB segments.

Improvement Tactics & Quick Wins¶

Actionable ideas to optimize this KPI, from fast, low-effort wins to strategic initiatives that drive measurable impact.

If LTV:CAC is under 3:1, segment by channel and double down on low-CAC sources like organic, referral, and PLG.
Add nurture campaigns post-activation to boost retention and prevent short-term churn.
Run a test optimizing pricing for expansion (e.g., seat-based or usage-based) in mid/high-value accounts.
Refine CAC tracking to include post-click costs like onboarding, trials, or support escalations.
Partner with RevOps to visualize this ratio by segment — not just as one blended number.

Required Datapoints to calculate the metric
- Lifetime Value (LTV): The total revenue expected from a customer over their lifetime.
  - Formula: LTV = (Average Purchase Value × Purchase Frequency) × Average Customer Lifespan
- Customer Acquisition Cost (CAC): The average cost to acquire a single customer.
  - Formula: CAC = Total Marketing and Sales Spend / Number of New Customers Acquired
- Timeframe: Specify the period for CAC and ensure it aligns with LTV calculations.
Example to show how the metric is derived

A SaaS company calculates its LTV to CAC Ratio for Q3:
- LTV: $1,500 (per customer)
- CAC: $500 (per customer)
- LTV to CAC Ratio = 1,500 / 500 = 3

Formula¶

Formula

\[ \mathrm{LTV\ to\ CAC\ Ratio} = \frac{\mathrm{Lifetime\ Value\ (LTV)}}{\mathrm{Customer\ Acquisition\ Cost\ (CAC)}} \]

Data Model Definition¶

How this KPI is structured in Cube.js, including its key measures, dimensions, and calculation logic for consistent reporting.

CustomersMarketingLTVToCAC

cube('Customers', {
  sql: `SELECT * FROM customers`,
  measures: {
    lifetimeValue: {
      sql: `${CUBE}.average_purchase_value * ${CUBE}.purchase_frequency * ${CUBE}.average_customer_lifespan`,
      type: 'number',
      title: 'Lifetime Value',
      description: 'The total revenue expected from a customer over their lifetime.'
    }
  },
  dimensions: {
    id: {
      sql: `${CUBE}.id`,
      type: 'string',
      primaryKey: true
    },
    createdAt: {
      sql: `${CUBE}.created_at`,
      type: 'time'
    }
  }
})

cube('Marketing', {
  sql: `SELECT * FROM marketing`,
  measures: {
    totalMarketingSpend: {
      sql: `${CUBE}.total_spend`,
      type: 'sum',
      title: 'Total Marketing Spend',
      description: 'Total marketing and sales spend for acquiring customers.'
    },
    numberOfNewCustomers: {
      sql: `${CUBE}.new_customers`,
      type: 'sum',
      title: 'Number of New Customers',
      description: 'Number of new customers acquired.'
    },
    customerAcquisitionCost: {
      sql: `${totalMarketingSpend} / NULLIF(${numberOfNewCustomers}, 0)`,
      type: 'number',
      title: 'Customer Acquisition Cost',
      description: 'The average cost to acquire a single customer.'
    }
  },
  dimensions: {
    id: {
      sql: `${CUBE}.id`,
      type: 'string',
      primaryKey: true
    },
    spendDate: {
      sql: `${CUBE}.spend_date`,
      type: 'time'
    }
  }
})

cube('LTVToCAC', {
  sql: `SELECT * FROM ltv_to_cac`,
  measures: {
    ltvToCacRatio: {
      sql: `${Customers.lifetimeValue} / NULLIF(${Marketing.customerAcquisitionCost}, 0)`,
      type: 'number',
      title: 'LTV to CAC Ratio',
      description: 'Measures the relationship between the Lifetime Value (LTV) of a customer and the Customer Acquisition Cost (CAC).'
    }
  },
  dimensions: {
    id: {
      sql: `${CUBE}.id`,
      type: 'string',
      primaryKey: true
    },
    calculationDate: {
      sql: `${CUBE}.calculation_date`,
      type: 'time'
    }
  },
  joins: {
    Customers: {
      relationship: 'belongsTo',
      sql: `${CUBE}.customer_id = ${Customers.id}`
    },
    Marketing: {
      relationship: 'belongsTo',
      sql: `${CUBE}.marketing_id = ${Marketing.id}`
    }
  }
})

Note: This is a reference implementation and should be used as a starting point. You’ll need to adapt it to match your own data model and schema

Positive & Negative Influences¶

Negative influences

Factors that drive the metric in an undesirable direction, often signaling risk or decline.
- High Acquisition Costs: Increased costs in acquiring customers inflate CAC, reducing the LTV to CAC Ratio.
- Low Conversion Rates: Inefficient channels with low conversion rates increase CAC, negatively impacting the LTV to CAC Ratio.
- High Support Costs: High costs to serve customers, especially in low-margin segments, reduce LTV, lowering the LTV to CAC Ratio.
- Customer Churn Rate: Higher churn rates decrease the LTV by shortening the revenue period from each customer, negatively affecting the LTV to CAC Ratio.
- Discounting Strategies: Excessive discounting can reduce the revenue per customer, lowering LTV and negatively impacting the LTV to CAC Ratio.
Positive influences

Factors that push the metric in a favorable direction, supporting growth or improvement.
- Customer Retention Rate: Higher retention rates increase the LTV by extending the revenue period from each customer, thus improving the LTV to CAC Ratio.
- Customer Expansion Rate: Increased upselling and cross-selling to existing customers boost LTV, enhancing the LTV to CAC Ratio.
- Acquisition Channel Efficiency: Efficient channels that convert well at a lower cost reduce CAC, thereby improving the LTV to CAC Ratio.
- Pricing Strategy: Optimized pricing that balances value and cost can increase LTV by maximizing revenue per customer.
- Customer Lifetime: Extending the average customer lifetime increases the total revenue generated per customer, improving the LTV to CAC Ratio.

Involved Roles & Activities¶

Involved Roles

These roles are typically responsible for implementing or monitoring this KPI:

Finance
Marketing
Product Marketing (PMM)
Sales Manager
Activities

Common initiatives or actions associated with this KPI:

Revenue Management
Lead and Demand Gen
Sales Enablement
Retention
CLTV Modeling

Funnel Stage & Type¶

AAARRR Funnel Stage

This KPI is associated with the following stages in the AAARRR (Pirate Metrics) funnel:

Revenue
Acquisition
Type

This KPI is classified as a Lagging Indicator. It reflects the results of past actions or behaviors and is used to validate performance or assess the impact of previous strategies.

Supporting Leading & Lagging Metrics¶

Leading

These leading indicators influence this KPI and act as early signals that forecast future changes in this KPI.
- Product Qualified Leads: Product Qualified Leads (PQLs) indicate strong product engagement and high propensity to become paying customers. An increase in PQLs forecasts a rise in customer LTV and can reduce CAC, thus improving the LTV to CAC Ratio.
- Deal Velocity: Faster deal velocity signals quicker conversions, which can lower CAC and bring in customers who may have higher LTV due to more decisive buying signals, positively impacting the LTV to CAC Ratio.
- Activation Rate: A higher activation rate means more users are reaching meaningful engagement early, increasing the likelihood of longer retention (higher LTV) and improved conversion efficiency (potentially lower CAC) for a stronger LTV to CAC Ratio.
- Customer Loyalty: Customer loyalty predicts longer retention and higher repeat purchases, directly increasing LTV. As loyal customers are less costly to retain, this strengthens the LTV to CAC Ratio.
- Net Promoter Score: A higher Net Promoter Score reflects high customer satisfaction and likelihood to refer, which can lead to more efficient CAC and higher LTV through increased retention and advocacy, thus improving the LTV to CAC Ratio.
Lagging

These lagging indicators confirm, quantify, or amplify this KPI and help explain the broader business impact on this KPI after the fact.
- Customer Lifetime Value: Customer Lifetime Value (CLV) is the numerator in the LTV to CAC Ratio. Increases in CLV directly improve the ratio, quantifying the long-term revenue generated per customer.
- Customer Acquisition Cost: Customer Acquisition Cost (CAC) is the denominator in the LTV to CAC Ratio. Reductions in CAC directly improve the ratio, making customer acquisition more efficient relative to lifetime revenue.
- Customer Churn Rate: Churn Rate impacts the length of customer relationships and thus LTV. A higher churn rate reduces LTV and weakens the LTV to CAC Ratio by lowering the return on acquisition investments.
- Conversion Rate: Conversion Rate influences how efficiently prospects become paying customers. Higher conversion rates imply more efficient acquisition (lower CAC) and potentially better customer fit (higher LTV), both improving the ratio.
- Net Revenue Retention: Net Revenue Retention reflects the ability to retain and expand revenue from existing customers, contributing to higher LTV. Strong NRR boosts the LTV to CAC Ratio by increasing the value derived from each acquired customer.