What is ARPU? How to calculate, benchmark, and improve average revenue per user

ARPU, or average revenue per user, is one of the clearest signals of how much value your product creates for the people who use it. The formula is simple—total revenue divided by total active users over a set period—but the number carries a lot of weight. It shapes pricing, informs the product roadmap, tells investors how healthy a business is, and helps teams see whether the changes they ship actually move revenue.

Here's what ARPU is, how to calculate it, how to read it against industry benchmarks, and how to improve it. We'll also look at how it relates to customer lifetime value (LTV) and ARPPU, and how a platform like Mixpanel connects ARPU to the behavior behind it.

ARPU is the average revenue a company generates per user, usually measured monthly or annually. You take all the revenue earned in a period and divide it by the number of active users in that same period.

There's no universally "good" ARPU. Different industries, regions, and business models produce wildly different numbers, so the metric is most useful in two ways: as a trend you watch over time, and as a benchmark against direct competitors with similar models. Investors and VCs also lean on ARPU to gauge the health of a business and decide whether to invest.

ARPU is especially valuable for companies that rely on a subscription model, like those in SaaS and media, and for businesses with large user bases, as you see in ecommerce and consumer apps.

The formula is as follows:

So, if a company makes $10,000 per month from 1,000 users, ARPU is $10,000 ÷ 1,000 = $10. A different company that's also making $10,000 per month, but from only 100 users, has an ARPU of $10,000 ÷ 100 = $100. In the second case, each user generates 10 times more revenue per month, a difference that tells you a lot about pricing, positioning, and the kind of customer each business attracts.

A quick note on the time window: pick one (monthly or annual), keep it consistent, and make sure the revenue and the user count cover the same period. Mixing a monthly revenue figure with an annual user count is one of the easiest ways to produce a misleading ARPU.

ARPU itself isn't new, but the way teams use it has shifted over the past few years:

There's no universal "good" ARPU to measure yourself against, but it helps to see the metric in the wild. The three companies below all report ARPU directly in their public financial filings, which makes these figures about as verifiable as a revenue number gets. They also show how much ARPU depends on the business behind it and on how each company defines the metric.

All three of these examples are ad-supported consumer platforms, yet their ARPU ranges from $1.78 to $5.04, and that's before you account for the denominators. Reddit divides by daily active uniques, Snap by daily actives, and Pinterest by monthly actives, all over a single quarter. 

So these numbers aren't truly comparable even to each other, let alone to a subscription SaaS product reporting monthly ARPU per account. The lesson is that ARPU only means something inside a consistent definition. Pick yours, hold it steady, and compare against your own history and direct competitors rather than a headline figure from a different model.

Raising ARPU means growing the revenue you earn from the users you already have. That's usually more efficient than spending to acquire replacements. While individual companies require individual processes to improve ARPU, below are some levers that tend to matter most:

The difference between a low and high ARPU isn't necessarily the product; sometimes, it's how that product is priced and packaged. Test per-seat versus per-account pricing, tier structure, and add-on modules. For example, usage-based or hybrid components let revenue scale with the value customers get.

When an existing customer adds seats, usage, a premium feature, or an add-on, ARPU rises without a new acquisition cycle. Identify the moments and behaviors that precede expansion, then build flows that nudge more users toward them.

Bundling complementary features into a higher tier (including AI-powered capabilities) gives customers a clear reason to pay more and gives you a structured path to a higher ARPU.

Compare ARPU across user segments to find your most valuable groups, then study the events and behaviors tied to them. Use those insights to tailor onboarding, cross-sell campaigns, and lifecycle messaging that move more users in that direction.

ARPU and retention are linked. Losing customers, particularly large ones, drags ARPU down. Spotting churn risk early and addressing it protects the revenue base you've already built.

In freemium models, moving even a small share of free users to paid plans lifts ARPU directly. Look at what paying users did before they converted, and design experiences that guide free users along the same path.

ARPU is most powerful when assessed alongside related revenue metrics. Two of the most important are customer lifetime value (LTV) and average revenue per paying user (ARPPU). Here's how they compare at a glance.

Both ARPU and customer lifetime value (LTV) show how much revenue users generate, but over different windows. LTV captures the average revenue a company earns from a user across their entire relationship, while ARPU is usually measured monthly or annually. ARPU indicates short-term value; LTV focuses on long-term retention and revenue, which makes it especially useful for forecasting.

Watching them together surfaces gaps. A company might acquire lots of new paying users (high ARPU) yet struggle to keep them (low LTV). Looking at ARPU alone would hide that churn problem; comparing the two pinpoints it.

ARPPU, or average revenue per paying user, shows how much revenue each paying user generates. It's calculated like ARPU, but the denominator is paying users only: total revenue ÷ number of paying users.

ARPPU is especially useful for freemium businesses, where most users are on a free plan and only some pay. ARPU can be skewed when a small group of high-value payers contributes most of the revenue; ARPPU accounts for that, so comparing both gives a more detailed picture. ARPPU also lets you segment paying users and study their behavior, so you can find lookalike audiences and guide more free users toward paid plans.

Using ARPU well takes a clear understanding of your customer base and your product. There are a few traps that are easy to fall into.

Historically, ARPU has been hard to work with inside a product analytics platform because revenue data is fluid: it changes with upgrades, downgrades, refunds, and chargebacks, and it usually lives in the data warehouse, separate from product behavior. That separation forces teams to file requests with the data team and makes it hard to connect product decisions to revenue.

Mixpanel Revenue Analytics closes that gap. With Warehouse Connectors, including Mirror and Profile History, Mixpanel stays in sync with your warehouse, so revenue data stays accurate even as it changes. From there, you can calculate ARPU, LTV, and return on ad spend (ROAS) directly in Mixpanel, alongside the product interactions that drive them, without custom formulas or manual work.

Because revenue and behavior sit in one place, you can ask questions that move ARPU rather than just report it: which features drive upgrades, how engagement shifts before a user upgrades or downgrades, and which segments generate the most revenue. Features like cohort analysis reveal the behaviors of high-value users, and ready-made ecommerce and SaaS revenue templates let you visualize ARPU next to churn, LTV, and ARPPU. You can explore a live example in Mixpanel's public ecommerce KPIs dashboard.

That's the real value of tracking ARPU in a product analytics platform: You see the numbers move and why they moved, which helps you figure out what to do next.

There's no universal benchmark. It depends entirely on your model, market, and pricing—compare against your own trend and direct competitors, not an industry average.

Divide total revenue by the total number of active users over the same period: ARPU = total revenue ÷ total active users. Keep the revenue window and the user count aligned to the same month or year.

Most companies measure ARPU monthly, since that aligns with subscription cycles and financial reporting. Many also track it annually for a smoother, longer-term view. The key is consistency, so trends are comparable over time.

MRR (monthly recurring revenue) shows your total recurring revenue; ARPU shows the average revenue per user. ARPU is more granular—it puts individual customer spending under the microscope—while MRR captures the overall size of your recurring revenue base.

ARPU divides revenue across all active users, including those on free plans. ARPPU divides revenue across paying users only. ARPPU is especially helpful for freemium businesses, where a large free base can pull ARPU down and obscure how well paying users actually monetize.

ARPU tells you how much value each user creates. To grow it, you need to see the behavior behind the number.