What is average revenue per user (ARPU)?

ARPU is a metric that stands for average revenue per user. In short, it’s the average amount of revenue generated by each active user of your app over a given period of time.

While average revenue per user was originally primarily used in the telecom industry, it has become useful for all types of digital businesses, from SaaS providers to social media networks and mobile apps.

In a mobile marketing context, ARPU is similar to lifetime value (LTV). It’s a way to calculate or determine the value of your users, or of groups of users you’ve organized into segments and cohorts. ARPU is a very important metric for app marketers and developers, because it reveals the amount of money being generated by a user within a specific, business relevant time frame.

ARPU is calculated by dividing your total revenue by your total number of users during the time period you want to measure. This could be a week, month, year, season, or any time frame relevant to a specific campaign or strategy where you want to measure revenue per user or revenue per customer.

Average revenue per user is an important user acquisition metric for mobile marketers, as well as an important business metric for product managers and executives. For marketers, comparing the average revenue per user across different campaigns, networks, and channels, can provide insight into the quality of users coming from those sources. From here, clear insights into return on ad spend (ROAS) and return on investment (ROI) can be determined. In conjunction with LTV, ARPU enables calculation of the user acquisition costs needed to maintain a positive ROAS. Marketers can also use ARPU to calculate how many new users need to be acquired to his specific revenue targets.

Average revenue per user also helps app developers better understand their customer base and pricing strategy. If an app’s ARPU is too low, there may be too much focus on low-revenue customers, or products and services may be underpriced. Running pricing experiments, A/B tests, and focusing marketing efforts on high-revenue users is the key to increasing ARPU.

When measuring any mobile marketing KPI or metric, including what makes a good ARPU, defining good is highly subjective. Depending on campaign spend, scale, total number of users, app vertical, and business model, the benchmarking figures can differ drastically. For example, shopping apps should have a high ARPU due to comparatively large baskets and in-app purchases, RPG games will likely see frequent, small IAPs from item purchases, and hyper casuals will have lower ARPU due to ad revenue reliance. Hybrid casuals will likely drive revenue from both ads and IAP. Subscription or freemium models will have highly specific and less frequent purchase patterns, such as an annual sign-up or renewal. In this sense, adopting/including additional metrics that fit under the ARPU umbrella is advised for more specific insights.

Average revenue per user can be improved by implementing any kind of strategy that aims to reduce acquisition costs and increase revenue. Similar to how determining what makes a good ARPU is heavily vertical and business model dependent, optimizing to improve ARPU will also need to be addressed on a case-by-case basis. There is no one size fits all. There are, however, several key areas of focus that will apply to almost any mobile marketing strategy, including those aimed at improving ARPU.

1. User acquisition and retention optimization: Finding the ideal balance between spend on user acquisition for volume and investing in the features and user experiences required to retain a long term and high LTV user base is always a complicated tightrope to walk. Ultimately, the strategy should be highly integrated.

2. Reactivation and re-engagement: Users who have previously churned or are inactive are often highly valuable. By identifying the churn point or reason for canceling a subscription, you can retarget with personalized advertising that addresses user issues directly. Conversion rates from re-engagement campaigns should be higher than a regular UA campaign.

3. Get pricing right: If the cost of items or subscriptions is too high, your conversion rate will be low and users will turn to the competition. On the other hand, if it’s too low, you will likely generate a higher number of total purchases, but total revenue will still be low. It’s also probable that cohorts will respond to different pricing packages, making segmentation an essential element in pricing. Calculating cohort ARPU is also a great way to gain insight into the revenue generated by new users. The calculation looks like this:

   Total revenue in time frame A from users acquired in time frame B / Total numbers of users acquired in time frame B = Cohort ARPU.

4. Up-sell and find opportunities: As with pricing, different segments will react differently to up-selling. Some users will be happy to make a large purchase immediately, others will likely want to stagger their purchases. For example, in a gaming app, one user might like to buy a small coin bundle to purchase the exact item they’re after, others users might want to buy bigger bundles if it results in a lower cost per coin. In a subscription app, some users might buy a 12-month subscription directly, while others might like to go month-by-month. Understanding the different user patterns and habits, and how to find the opportunities to consistently engage them will prove fruitful.

Average revenue per user and LTV are closely related but are different from one another. The main difference is the time frame—ARPU looks at revenue per user from a defined time period, while LTV measures value (revenue) from an entire user journey (lifetime). If the time period measured happens to be the same, this is the one scenario where the results can be identical. This generally happens if a user churns early, or within the time frame that your ARPU calculation is capturing.

Imagine, for example, that your ARPU is set to measure revenue from users from a specific month where you ran a high-spend UA campaign, like an e-commerce app in November. If your ARPU calculation is capturing the month of November as its time frame, and the user makes an in-app purchase and then uninstalls your app within that month, their individual LTV will be the same as their individual ARPU. Generally speaking, LTV is a broader and more all-encapsulating metric for the true value of a user, while ARPU is granular and specific.

Adjust’s robust suite of attribution and analytics tools make measuring ARPU easy. All marketing efforts can be measured in one place, for lightning-fast decision making and smart budget allocation. ARPU is available in Datascape as a cohort metric, along with a large range of other cohort related KPIs, including lifetime value and revenue per paying user.

To learn more about Datascape, Adjust, and how we can help you grow your app, request a demo today.