Average App Revenue: The Misleading Benchmark

Average revenue is one of the key performance indicators for mobile apps. It is a common practice to use category-specific average app revenue as a benchmark. By comparing your app’s performance to apps in the same category you will know for certain if your app’s monetization models are performing as designed. But is the average app revenue metric really accurate?

 

The Flaws with Average App Revenue

  1. General averages include apps that are very different from your app. By just using the game category, it is easy to conclude that the subcategories within include apps that are very different from each other. Also, there are types of game apps that perform better consistently. Even if a lot of these apps have the same concept or mechanics, they still use different monetization models.
  2. The top apps skew the numbers. The top apps actually pull up the average app revenue especially if they are earning a lot. Even if you narrow down the comparison to a specific subcategory, the difference between the revenue of a top app compared to an app ten steps down the rank is staggering! The top app would make it appear that the subcategory is earning a lot when most of the lower-ranked apps don’t even earn half of the top app’s revenue.

These flaws aren’t just limited to average app revenue. Different monetization models like in-app purchases also use an overall average for benchmarks.

 

How to Better Benchmark Apps

  1. Use apps that are very similar to your app for benchmarking. The apps should have similar functionality, features, audience, and monetization models. Select 5-10 apps from the 80th – 20th percentile your app’s category or vertical.
  2. Use average revenue per user. Narrow down your selection of apps by comparing average revenue per user. The specific metric to use is the average revenue per daily active user (ARPDAU). This is to eliminate any unfair revenue comparison based on the number of app users.
  3. Group apps into three different revenue categories. Place your benchmark apps into either the high (80th percentile), median (50th percentile) or low (20th percentile) revenue performance category. This will eliminate the ambiguity that average app revenue benchmarks provide. You can also use this to evaluate the performance of your app over time; if it is improving or getting worse.

 

There is a huge chance that apps in several categories appear to perform better than they do. And this has to do with how general averages are used as benchmarks. So in order to really know where your app stands in terms of revenue, a targeted approach is necessary.

Mobile App Usage Trends

App Usage: A Closer Look

App usage trends show persistent behaviors that can directly affect app performance. But are the users influencing app design or is it the other way around?

 

What do the figures have to say?

 

Is mobile app usage higher than other digital media platform?

Mobile apps take 52% of all time spent on digital media. Also, 85% of users prefer native mobile apps over mobile websites. This preference is very evident with how the users spent 89% of their mobile media time on apps. Mobile app usage averages to 30 hours a month while mobile web usage is only a measly 3 hours and 45 minutes. 56% of smartphone owners and 26% of tablet owners utilize apps every day. And 79% of smartphone owners and 52% of tablet owners use apps at least 26 days a month, making apps a major part of a mobile device owner’s daily routine.

 

What is the demographics of frequent app users?

Female and male smartphone users use almost the same average amount of time on mobile apps. Even in different age brackets, there is no significant divergence in the amount of time spent on apps per month. The 18-24 age bracket spends an average of 37:06 hours on mobile apps every month. The 25-34 bracket, on the other hand, spends an average of 35:40 hours of app usage time. The 35-44 bracket is not far behind with 33:57 hours. Finally, figures start to diverge from 45-54 bracket with only an average of 25:26 hours on apps and in the 55+ bracket with 21:21 hours.

 

What type of apps are most utilized by users?

With the average time on app as the basis, game apps are the most utilized apps (43%) followed by social networking apps (26%), entertainment apps (10%), utility apps (10%), news (2%) and productivity apps (2%). According to Nielsen, the increase in app usage and popularity is due to the emergence of entertainment-based app categories. There are about 115 million entertainment app users with 76% of these users playing at least one game app. Time on entertainment apps is about 13:20 hours.  The most time spent are on gaming apps (10:02hrs); music apps place a far second (2:37hrs), and then sports apps (2:05hrs).

 

But according to research, most device owners mainly use five non-native apps installed from the App Store and on average use 26-27 apps each month. This seems to reflect App Store rankings where only a handful of apps continue to dominate.

 

What are the most promising app categories?

The music category is in the lead with an average of 79% time on music apps; followed by health and fitness with 51%, social networking with 49%, travel 28%, entertainment 22%, sports 16%, games 15% and news at 14%.

 

There’s more to consider on app categories than time spent, though. But over a span of two years (2014-2015), the lifestyle and shopping category grew exponentially (81%) in terms of app sessions. This is followed by utility and productivity apps (125%) and messaging/social apps (103%). Most entertainment categories like news & magazines (49%), music (33%) and games (30%) lagged behind. This indicates that lifestyle and shopping apps have frequent launches but the entertainment apps encourage more engagement. This could because users access shopping apps, do a specific transaction (like a purchase) and then end the session. Entertainment apps encourage a different form of user engagement compared to other app categories.

 

Are app retention rates improving?

There’s a 5% increase in apps used only once (abandoned apps) from 20% in 2014. In 2014, the percentage of apps used more than eleven times (retained apps) increased to 39% but decreased to 34% in 2015.

 

What app usage trends affect app design?

Research shows that 49% of users holds their smartphones using one hand, 36% cradle their phones; only 15% hold their phones with both hands and when they do, only 10% of these people use the device in landscape mode. The way users hold their devices may be also the reason why they are more comfortable interacting at the center of their device’s screen than at the corner or extreme edges of the display.

 

 

Main source: Go-Globe Infographic

Mobile App Key Performance Indicators

List of KPIs for Mobile Apps

 

Measuring the success of an app is at the top of almost all developers’ priority. But are you sure that you’re properly measuring and analyzing the right metrics? There had always been warnings about vanity metrics, metrics that are good to look at but doesn’t really contribute to the business side of things. Actionable metrics, on the other hand, are the best performance indicators. They measure metrics that ultimately lead to revenue and scaling success of a mobile app.

 

In this article, we would discuss key performance indicators for mobile app acquisition, engagement, and revenue.

Cost per Acquisition (CPA)

CPA is measured by dividing the cost of user acquisition by the number of acquired users. User acquisition models can vary but the most common metrics are install rate, cost per install (CPI), and cost per action (CPA).

 

Retention Rate

Retention rate is an important performance indicator, more so than downloads. It can determine the success of your app over a certain period of time and determine user lifetime (LT). LT  is one factor in determining the lifetime value (LTV) of an app user.

 

Retention is mainly based on the frequency of app sessions. The retention rate of an app is determined by dividing the number of daily users by the total number or users at a given time. Common time frames for the measurement of retention rate are 1 day, 7 days, and 30 days after download. The formula for retention rate is Day X users/Day 0 users.

 

Churn Rate

The churn rate metric is the opposite of retention rate. With the use of this performance indicator, you’ll find out the percentage of users that uninstall or abandon your app. The formula is 1 – retention rate. For example, if your retention rate is 20%, you’ll have 1 – .20 = 80% churn rate.

 

Daily Active Users (DAU)/Monthly Active Users (MAU)

The DAU and MAU metrics are very important for apps that use advertising as the main revenue model. The data these metrics provide will help you analyze user trends and also to calculate app stickiness.

 

Session Length

Session length is the measurement of the length of time users spend on the app from its opening to closing. Long session lengths are a positive sign of engaged users. This performance indicator also lets you assess the efficiency of your app flows.

 

Session Interval

Session interval, on the other hand, is the time period between a user’s first and second app session. This performance metric can signal if the user deems the app to have immediate value as to run the app the second time. Analyzing session intervals can help you optimize user experience and consider contextual app notifications and prompts.

 

Lifetime Value (LTV)

Lifetime value is the measurement of potential revenue throughout the length of a user’s usage of the app. LTV is commonly the main revenue metric, showing not only the lifetime value of each app users but also the financial value of the app. There are many ways to calculate LTV, mostly depending on how you define user value.

 

Average Revenue per User (ARPU)/Average Revenue per Paying User (ARPPU)

The ARPU performance metric determines the average revenue users generate. In order to determine the ARPU, divide the lifetime revenue of the app by the number of lifetime users of the app. Tracking this metric can determine if you are acquiring (or will acquire) users with the highest LTV at the lowest CPA.

 

 

Benefits of the Shark Tank Effect on Apps

Publicity is always good they say especially in the ‘Shark Tank’. The premise of the show is straightforward enough: a budding entrepreneur comes in and makes a pitch in front of “sharks” that could potentially offer an investment deal. The main goal is to bag the deal but an entrepreneur can actually go home empty-handed and still gain more. For example, several entrepreneurs would refuse any offer from the “sharks”. So why appear on the show?  Here’s why: the show packs on an estimated $4-5 million worth of marketing exposure.

 

What is the Shark Tank Effect?

Marketing exposure is the very backbone of the Shark Tank Effect. An appearance is enough to boost an app’s downloads with some apps featured on the show amassing up to hundreds of thousands of downloads within a few hours of the show’s airing. This boost can last for several days with a secured deal helping bolster the Shark Tank Effect for a few more weeks.

 

The Shark Tank Effect is considered as a popular example of the impact of publicity on a product. The same effect is attributed to an app featured in tech websites like TechCrunch and Mashable. There’s even something called “The TechCrunch Effect” that works similarly to the Shark Tank Effect. In this effect, featured start-ups experience a snowball effect from almost all aspect of the business from inquiries, orders and down to capital investments. For apps, benefits can be:

 

Mass Exposure

According to a study, mass exposure is the second most effective publicity strategy for apps (the most effective being featured in the new apps charts). In the USA alone, there are 285 million TV viewers as of the fourth quarter of 2014. About 7.9 of these people watch Shark Tank. TechCrunch peak on a million visitors while Mashable can peak up to 4.9 million visitors for a given month.

 

Promotion of Virality

In the same study, mass exposure exhibits an epidemic curve right after a publicity event. For excellent apps, the magnitude of the curve is larger but the duration of the epidemic is shorter. The Shark Tank show, therefore, provides a different type of virality. Most viral apps circulate through recommendations with the app first tested before it receives marketing exposure. But some apps featured on Shark Tank don’t hold up to the audience’s expectations  and thus, don’t really make the most out of the effect.

 

Gives the App Credibility 

Being associated with a trusted brand can create a “halo effect” wherein the audience’s’ impression of your app is based on the perceived image of the brand that endorses it. Even though Shark Tank and TechCrunch don’t necessarily endorse your app, the trust the audience has for these names creates an impression that the featured apps are legitimate and are pre-screened.

 

Increase of Visibility in More Ways

One of the indirect effects of publicity is the increase in visibility as search frequency of the app’s keywords increases. The app’s ranking in these keywords increases so is its ranking in mobile SERPs. The app’s exposure in social media also increases as it becomes viral. The audience would also most likely access your app’s web page for more information instead of downloading it directly from the App Store. Some blogs and review sites may even cover the app as an analysis on the before and after effects of the publicity.

 

 

 

 

Pokemon GO Logo

Pokémon Go App Revenue

How Profitable is Pokémon Go?

 

The Pokémon Go app is said to be the biggest game app in US history, crushing records with app revenue double the industry average. But does it keep on getting better from there? Pokémon Go actually made $35 million in its first two weeks! Therefore, it seems like there is no stopping the Pokémon Go phenomenon but is the app here to stay or is it just another hype?

 

App Revenue and Key Performance Metrics

Acquisition

  • 4-5 million app installs a day
  • In the US alone, the app was downloaded more than 7.5 million times from both the Google Play store and iOS App Store.
  • Just two days after its release, Pokémon Go was installed on 5.16% of all Android devices in the US.

 

Engagement

  • On July 14, 2016, the app reached 26 million active users for both Android and iOS and as of July 18, 2016, it dropped to about 21 million active users.
  • As of July 8, 2016, average time in app (for Android) is 43 minutes and 23 seconds, considerably higher than social apps like WhatsApp (00:30:27), Instagram (00:25:16), Snapchat (00:22:53) and Messenger (00:12:44).

 

Retention

  • The app’s retention rate is double the industry average with about 7 out of 10 downloaders returning to the app the next day.
  • On its first week, about 60% of downloaders from the US use it daily.

 

 

Monetization

  • The app’s revenue is also double that of the average for casual games. Casual games average revenue per daily active user (ARPDAU) is only $0.10 while Pokémon Go reached $0.25 ARPDAU.
  • As of July 11, 2016, Pokémon Go is earning $1.6 million (for the iOS app only) a day.
  • Pokémon Go’s paid users are ten times that of Candy Crush’s.

 

Positive Contributors in Making Pokémon Go Stick

  1. Pokémon had been around for a decade – it’s not just a hype, it’s a cultural phenomenon. The app is just a new approach in targeting an established market. As long as there are Pokémon fans, the app will thrive.
  2. There’s much room for expansion. Pokémon Go can expand its content offerings relative to the Pokémon franchise. Right now, the app only features the original 150 Pokémons but there are about 570 other Pokémon as of Pokémon X/Y’s release and more to come with the release of Pokémon Sun and Moon.
  3. The app also has great monetization opportunities. This starts with the very premise of the game. The user either needs to spend a lot of time on the game to progress or purchase in-app items to bypass the process. Therefore, the app depends on the number of users and not on whales for effective monetization.

 

The massive success of Pokémon Go undeniably contributed to the boost in Nintendo shares (up to 24.52%). But an analyst believes that in order to contribute real impact to Nintendo’s profits, the app should earn a minimum of $140-196 million every month consistently.