Why Financial Metrics (Averages) are Great for Presentations but Misleading for the Readers. The Problems with ARPU

When analyzing business performance, financial metrics like averages often take center stage in presentations. Their appeal lies in simplicity: averages are easy to calculate, effortless to understand, and present a polished narrative for stakeholders. Metrics like average revenue per user (ARPU) are especially popular in industries like SaaS, telecommunications, and streaming, where they provide a snapshot of revenue generation per customer.

However, the problem lies beneath this polished exterior. Averages can mask critical variations and nuances in data, leading to interpretations that may misrepresent reality. For example, ARPU often hides disparities in user behavior, customer segmentation, and revenue distribution. Averages make the good look great, the bad look acceptable, and the true story somewhere in between.

In this article, we’ll explore how averages, while ideal for presentations, can mislead readers when used without context or deeper analysis. Using ARPU as our primary example, we’ll unpack the limitations of averages and highlight strategies to ensure more transparent and insightful financial reporting.

The Problem with Averages (ARPU)

Averages are easy to compute, but they often hide the real story. ARPU is no exception.

Consider this: Your SaaS company has 1,000 customers. One large enterprise client pays $10,000 per month, while the rest pay $15 each. The ARPU? Around $25. But does that average tell you anything about the typical customer or the health of your business? Hardly.

Revenue per customer rarely follows a neat, bell-curve distribution. Instead, it often skews toward a power-law distribution, where a small group of high-value customers generates the bulk of your revenue. In such cases, ARPU can paint an overly rosy picture by obscuring the fragility of a revenue stream heavily reliant on a few accounts.

Metrics are the lifeblood of any business, especially in the SaaS world. Investors, boards, and executives alike lean on them to gauge the health and trajectory of a company. But not all metrics are created equal.

Among the commonly revered KPIs—ARR, MRR, CAC, LTV, churn—one stands out for its ability to mislead as much as inform: Average Revenue Per User (ARPU). Often presented as a hallmark of business performance, ARPU can mask critical truths and, at its worst, create a false narrative about your company’s health.

The Origins of ARPU

ARPU’s roots lie in the early 2000s telecom industry, where it provided a simple way to evaluate how much revenue each subscriber generated. This made sense when most revenues came from relatively homogeneous, per-user fees. But as subscription-based models spread across industries—from gaming to SaaS—the metric came along for the ride, gaining a reputation as an essential KPI for understanding customer value. The Problem with Averages (ARPU) is that users confuse context and generalize results.

Why ARPU Can Be Misleading

1. It Can Rise While the Business Declines

ARPU can increase even as overall revenue or customer count shrinks. For example, losing a significant number of low-paying customers will boost the average—even though your total revenue and market share are eroding.

ARPU’s allure lies in its simplicity: divide total revenue by the number of customers. The problem? It can create an illusion of growth when your customer base is shrinking. For example:

If you lose low-paying customers but retain a few high-paying ones, ARPU rises while revenue and customer health decline.
Adding one high-value client can skew the average, hiding the fact that your core business remains stagnant.

This happens because ARPU averages across a customer base, ignoring the distribution of revenue contributions—a critical oversight in businesses where revenue often follows a power law distribution, with a few high-paying customers driving the majority of income.

2. It Lacks Profitability Context

ARPU doesn’t account for the cost of acquiring or servicing users. If you’re spending $600 to acquire a customer who generates $400 in annual revenue, a high ARPU isn’t much comfort.

Metrics like median revenue per user or revenue segmentation by customer tier provide a much clearer picture than ARPU alone. For example:

Blended ARPU: When large enterprise clients coexist with small SMBs, ARPU masks the disparity.
Cohort ARPU: Observing ARPU trends by customer acquisition cohorts reveals whether newer customers contribute more or less value than older ones.

Without such granularity, you risk misinterpreting trends and making flawed strategic decisions.

ARPU focuses purely on revenue and ignores costs. It cannot:

Indicate whether acquiring or retaining customers is cost-effective.
Highlight customers whose service costs outweigh their revenue contributions.

Pairing ARPU with metrics like Customer Acquisition Cost (CAC) and Gross Margins is necessary to evaluate true profitability.

3. It Masks Pricing Potential

Not all customers derive the same value from your product, yet many companies fail to segment pricing effectively. If your ARPU is $100, it could mean you’re undervaluing high-usage customers who might be willing to pay significantly more.

4. It Ignores Retention Risk

High-paying customers are not inherently more loyal. Some churn due to dissatisfaction or shifting needs, and others because of over-aggressive pricing tactics. ARPU won’t warn you about these retention risks.

A common misconception is equating ARPU with Lifetime Value (LTV). While ARPU reflects short-term revenue, LTV accounts for:

Retention: ARPU may rise while churn increases.
Expansion Revenue: ARPU doesn't distinguish between upsells and new customers.
Lifetime Duration: LTV provides insight into the longevity of revenue streams, which ARPU cannot.

For true unit economics, combining LTV and CAC is far more meaningful.

The Way Forward

1. Segment, Segment, Segment

Replace ARPU with segmented revenue metrics. Break your customer base into cohorts—by size, industry, geography, or lifecycle stage—to understand which groups are driving growth and which are stagnating.

2. Focus on LTV and Retention

Lifetime Value (LTV) and retention rates provide deeper insights into whether customers are sticking around and generating sustainable value. Combine these metrics with churn analysis

to reveal vulnerabilities in your revenue streams.

3. Adopt Value-Based Pricing

ARPU doesn’t account for customers who would happily pay more. By introducing pricing tiers that better align with the value you’re delivering, you can maximize revenue without alienating smaller customers.

4. Analyze Revenue Distribution

Visualize how revenue is distributed across your customer base. Look for patterns or dependencies on a small subset of high-value clients, and build strategies to diversify and fortify your revenue streams.

Observe ARPU trends within acquisition cohorts to understand the quality of new vs. existing customers.

5. Investigate Outliers

Instead of obsessing over averages, focus on the extremes. What’s driving revenue spikes or declines? What differentiates your best and worst-performing segments? These insights are far more actionable than a single ARPU figure.

Use ARPU to surface questions—not answers—about your business. Delve deeper into customer segmentation and cost structures for actionable insights.

6. Always Provide Context

Pair ARPU with:

Customer counts (absolute and churned).
Revenue segmentation by tiers or cohorts.
Retention and expansion revenue metrics.

Averages Hide the Truth

Seth Godin famously said, “Averages almost always hide insights instead of exposing

them.” The same applies to ARPU. It may look like a handy shorthand for customer value, but in reality, it often glosses over the nuances that matter most.

Consider this scenario:

A SaaS company reports a $300 ARPU.
In reality, 10% of its customers pay $3,000/month, while the remaining 90% pay $50/month.

Relying on the average obscures the revenue fragility tied to dependency on a small subset of high-paying customers.

So, the next time someone asks for your ARPU, don’t just hand over the number. Share the story behind it—the segments, trends, and risks it conceals. Because in SaaS, as in life, the truth is rarely average.

The Bottom Line

ARPU’s simplicity is both its strength and weakness. As a standalone metric, it’s insufficient for understanding the true health of a SaaS business. When analyzed in context and paired with complementary KPIs, ARPU becomes a valuable piece of a larger puzzle.

By rejecting averages as the sole truth and embracing a nuanced approach to data, you can uncover the real insights necessary to drive sustainable growth. In SaaS, the devil—and the opportunity—is in the details.