What is Average Revenue Per User?
With Vicky Freed, Chief Strategist @ Differly
In this episode, Allan and Lauren talk to Vicky Freed, Chief Strategist, Loyalty, Data, and Customer Performance at Differly, about Average Revenue per User (ARPU). Vicky explores what ARPU is, how to segment it effectively, calculation methods, and which businesses should prioritize tracking it.
What is Average Revenue per User?
Average Revenue per User (ARPU) is the total revenue generated divided by the number of active users or customers over a specific period. It's a foundational metric for understanding how much value each customer generates and identifying opportunities to grow revenue through pricing, upselling, or customer retention.
ARPU matters because it reveals whether your business model is sustainable and scalable. A rising ARPU signals that customers are spending more or that your retention strategies are working. A declining ARPU can indicate churn, reduced engagement, or market saturation—all signals that warrant investigation.
Why ARPU is critical for growing companies
For SaaS, e-commerce, and subscription-based businesses, ARPU is one of the most actionable metrics. It directly ties customer value to business health. Unlike total revenue (which can mask underlying problems), ARPU isolates the per-user economics and makes it easy to spot trends.
When you track ARPU over time, you can answer questions like: Are we retaining high-value customers? Are our pricing changes working? Is our product becoming more or less valuable to the market?
How to segment and calculate ARPU
Segmentation is where ARPU becomes powerful. Instead of a single company-wide number, break ARPU down by:
- Customer cohort: Users acquired in the same month or year often have different lifetime value patterns
- Product tier or plan: Premium customers generate more revenue than free-tier users
- Geography or region: Market maturity and purchasing power vary by location
- Customer segment: B2B vs. B2C, enterprise vs. SMB, or industry verticals
The basic calculation is simple:
ARPU = Total Revenue / Number of Active Users
But the nuance lies in how you define "active users" and the time period. A 30-day ARPU differs from an annual ARPU. Choose a consistent period that matches your business cycle.
For subscription businesses, you might also track:
- Monthly Recurring Revenue (MRR) per user: Isolates predictable, recurring income
- Annual Recurring Revenue (ARR) per user: Useful for longer sales cycles or annual contracts
- Gross ARPU: Revenue before refunds or discounts
- Net ARPU: Revenue after refunds, cancellations, and adjustments
Which businesses should track ARPU?
ARPU is essential for:
- SaaS and subscription platforms: Where recurring revenue and retention drive growth
- E-commerce and marketplaces: Where average order value and purchase frequency matter
- Freemium models: Where monetization depends on converting free users to paying customers
- Advertising-supported platforms: Where revenue scales with user base and engagement
Businesses with a single, one-time transaction model (like real estate or high-ticket B2B sales) may find ARPU less actionable than metrics like Average Deal Size or Customer Lifetime Value. However, even in these cases, ARPU can reveal important patterns about customer acquisition and retention efficiency.
The relationship between ARPU and other metrics
ARPU doesn't exist in isolation. It connects to:
- Customer Acquisition Cost (CAC): If your CAC is rising faster than ARPU, your unit economics are deteriorating
- Customer Lifetime Value (CLV): ARPU is a building block for CLV; multiply ARPU by average customer lifespan
- Churn rate: Rising churn often precedes declining ARPU
- Net Revenue Retention: For subscription businesses, NRR shows whether existing customers are generating more or less revenue over time
Understanding these relationships helps you spot whether growth is sustainable or fragile.
Metrics mentioned in this episode
Want to dive deeper into metrics and KPIs? Explore MetricHQ, Klipfolio's online resource for metric definitions, examples, and best practices.