The mobile revolution has been dubbed by many as the trillion dollar revolution. While it is still hard for anyone to quantify the overall economic impact of the mobile revolution, it is clear that mobile devices and apps are changing every aspect of our lives. From news consumption, to photo sharing, to gaming, to hailing a cab to depositing a check, every moment has become a mobile moment. In fact, most consumers who have a smartphone or a tablet can’t imagine their lives without these devices and apps. We have become addicted to instant gratification and the back pocket proximity of powerful computing technology.
At Flurry, we have been at the epicenter of the mobile revolution for more than five years now and today we see activity from more than 300,000 apps and three billion app sessions every day, giving us a unique vantage point into the behavior of over a billion worldwide mobile consumers.
Today, SourceDigital13 we are sharing a peek into a day in the life of a U.S. adult mobile consumer. (We'll blog some other parts of my keynote in future posts.) For this depiction (see chart below), we have used a random sample of 15,271 U.S. iOS users and we measured their app usage throughout the month of May, 2013. We also cut the data based on a 24-hour cycle to help understand the usage throughout an entire day.
Daytime, Nighttime and Bedtime Are All Apptime
Many conclusions can be drawn from this chart. Here are a few key observations:
- App usage steadily increases over the course of the day and ultimately peaks in the evening (unlike TV which remains low then has a dramatic jump in the evening.) This is a big change of perspective for media planners who have been used to weighting their budgets toward evening TV. In an app-centric world, that spend could effectively be spread throughout the day given consumers are reaching for their devices consistently throughout their waking hours.
- Wearable computing already arrived with the smartphone. Our data confirms what many of us know from experience: smartphones, tablets and the apps installed on them appear to be glued to consumers 24/7, 365. They are with us when we wake, work, exercise, eat, play and yes, even when we sleep. We have entered the era of “wearable computing” without needing the wearable gear. Even ahead of the mainstream adoption of Google Glass or Apple’s rumored wrist device, consumers are already embracing the wearable lifestyle with smartphones and tablets.
- While gaming still consumes a large portion of the time spent on devices, other categories appear to be closing the gap when it comes to consumer attention. With the proliferation of social and photo sharing apps, consumers are switched on and sharing every aspect of their lives.
- Shopping and lifestyle apps are used around the clock. Breakfast time, lunch time, dinner time and bedtime have become shopping time.
Millennials Just Might Surprise You
We drilled further into the app usage of young adults age 25-34, a highly-desired segment for brands and advertisers. That segment of the population enjoys high disposable income and has traditionally been a prime target of CPGs, travel, entertainment and retailers.
In the next chart, we have analyzed how app usage by this group indexes against the overall population. (In this chart, 0% represents average usage across all age groups. Positive percentages reflect the degree to which app usage for the 25-34 year old age group exceeds that of iOS users in other age groups.) The results surprised us.
Given the popularity of game apps you might expect that Millennials drive that usage, but in fact they under-index for game app usage. It’s turns out that it’s the middle aged Gen X-ers who grew up with gaming consoles who are over indexing on games. Millennials also under-index on time in Utilities and News than the rest of the population. The categories in which Millennials over-index are Sports, Health and Fitness; Music, Media and Entertainment; Lifestyle and Shopping.
We then went one step further to break down gender usage within the 25-34 age group. The results are shown in the chart below.
Females age 25-34 dramatically over index in the Sports, Health and Fitness category. They spend over 200% more time in these apps then the rest of the population. Women gravitate toward self-improvement related apps while men gravitate toward entertainment. Males age 25-34 over index in Music, Media and Entertainment as well as Social and Photo-Sharing. They under-index in News & Magazines. Confirming some age-old stereotypes, women 25-34 also over-index in Lifestyle and Shopping in which they spend 75% more time than the rest of the population.
Even with more than a billion worldwide active devices, we are still in the very early days of the mobile consumer age. New apps and experiences are emerging daily. In the blink of an eye, experiences such as Ubering (the new verb for ordering a cab using the popular Uber app) and Snapchatting (in reference to using SnapChat to exchange ephemeral photos and videos) have arrived in the mainstream of society and soon, we predict, the English dictionary. Just three years ago these experiences, 100% powered by our mobile devices, didn’t even exist.
Many things will change over the next few years but we predict that mobile devices will become even more a part of the fabric of society than they are today. That means marketers and advertisers need to learn how to make mobile a central part of their marketing and media plans, not just an afterthought.
Flurry measured a 47% increase in active smartphones and tablets in the United States between April of 2012 and April of 2013. While that number sounds impressive, it actually puts the U.S. in the bottom 5% of countries for connected device growth in the past year. Worldwide, growth of these devices is exploding. To be in the top 5% of countries for growth over the past year, a country’s number of active connected devices needed to more than triple.
There are currently more than one billion active smartphones and tablets globally, and based on current growth rates we expect to reach two billion in 2014. In this report we discuss which countries are growing fastest, and the implications for the mobile ecosystem and for society more generally.
Huge Potential for Future Growth
The reason even 47% growth puts the US near the bottom of countries for tablet and smartphone growth becomes clear from comparing the size of the connected device installed base and population in five countries.
Let’s start by considering China and the U.S. These two countries currently have a similarly sized connected device installed base, but China has more than four times as many people.Combine China’s largely untapped population with its rapidly growing incomes (increasing at a rate of 8-10% a year between 2009 and 2011, according to the World Bank), and it’s not surprising that the connected device installed base in China grew by 149% between April of 2012 and April of 2013.
We expect these same forces to continue fueling growth in connected device numbers in China, and given the size of the Chinese population, those numbers could add up quickly. For example, if penetration of smartphones and tablets in China grew to that of Malaysia then 210,507,168 additional connected devices would be added to China’s installed base. We chose Malaysia as a point of comparison because it has a large Chinese population and per capita incomes where China’s are likely to be in the not too distant future.
Canada and India provide an even more dramatic comparison. They currently have similarly sized installed bases of smartphones and tablets, but India’s population is 36 times as big as Canada’s. Of course, India’s device penetration won’t catch up to Canada’s overnight, but when India’s rate of penetration equals the current rate in China, then 197,561,626 additional devices will be added to the worldwide installed base. Given India’s connected device installed base grew by 160% in the past year, we don’t think that’s going to take that long to happen.
For those keeping count, that means that the world’s number of connected devices will increase by more than 400 million (or about 40%) when the rate of penetration in India reaches the current rate of penetration in China, and the rate of penetration in China reaches the current rate of penetration in Malaysia.
100%+ Growth is the New Normal
India and China’s large populations make them dramatic examples, but their rates of growth don’t even put them at the top of the charts.Use of smartphones and tablets grew in every country in the world last year except for the three (The Central African Republic, Niger, and South Korea) shown in red in the map below. South Korea was one of the earliest adopters of mobile technology, and it appears that its market is now saturated. The countries in orange (mainly the English speaking countries, Western European countries, and the most connected parts of Asia) are other early adopters of mobile technology. Those markets still grew at rates of up to 99%, but a lot of that growth was the result of people adopting tablets as second devices.
The countries in yellow and green all saw their mobile installed bases more than double in the one year period between April of 2012 and April of 2013.That phenomenal rate of growth is all the more impressive considering what a large proportion of the world’s land mass and population those countries represent. The mobile markets of all of the large BRIC countries (Brazil, Russia, India, China) grew by between 100 and 199% (the growth rate for the yellow countries on the map). Much of the rest of South America and parts of Africa also grew at that same rate.
The number of active connected devices in countries in green in the map grew at 200% or more in the year to April 2013; those shown in the darker green had growth of 300% or more. Many of these hyper-growth countries are relatively small and not particularly affluent, so their fast growth in the past year may be a reflection of their wireless infrastructure catching up enough to allow their citizens to participate in the mobile revolution.
Implications for the Mobile Ecosystem
The discussion up to now clearly points to rapid growth in the connected device installed base coming predominantly from countries that have a lot of headroom for growth because their current rate of penetration is relatively low. That has the potential to change the foundation of the mobile ecosystem. We have become used to a world in which connected devices are reasonably expensive and replaced fairly frequently, and in which apps for those devices are developed by people in relatively affluent countries. As we look toward the connected device installed base doubling to more than two billion, we expect more of a focus on lower-cost devices that are also possibly more robust (to allow for less frequent replacement since that may be unaffordable in lower income countries). We also expect to see greater diversity of apps and app developers as apps are developed to meet the needs of increasingly diverse device users.
Things get even more interesting when we consider what people might be doing with all of those devices. Of course, they will still provide communication and entertainment, but we expect mobile devices to play an increasingly large role in many aspects of life including enabling commerce in growing economies, facilitating medical care in remote areas, and ensuring that people throughout the world have access to world-class educational resources. We can’t wait to see what else the next billion smartphones and tablets will be used for!
Over the past four years, Apple’s iOS and Google’s Android have been locked into a two horse race for mobile OS ownership. In the past year, there has been a lot of focus on the rise of Android and its lead in device market share. More recently, many analysts started questioning the true value of Android’s market share especially in the high-end smart phone and tablet markets. At Flurry, we felt that it was important to take a step back and look beyond straight device or activation numbers to simply understand what market or markets are being contested.
In this report we do just that, arguing that there is more than one race for mobile market share occurring simultaneously. We analyzed four years worth of Flurry’s data to understand who is ahead in which contests, discuss the apparent strengths and weaknesses of the competitors, and consider the implications for the overall mobile ecosystem.
Android Leads In Device Market Share
It is clear from announcements from device manufacturers such as Apple and Samsung that Android is winning the race for device market share. Flurry’s own data supports this. The number of Android devices we are tracking worldwide doubled in the past year, reaching 564 million as of April of 2013. While the installed base of iOS devices that we track has also grown over that time, Android pulled ahead in active device share in late 2012 and has maintained that position ever since. This is shown in the chart below. This lead followed a period of just over a year in which the number one spot was changing hands. Prior to that Apple dominated the connected device market following the launch of first iPhone and then iPad. Approximate launch dates of some of the major iOS and Android devices are also shown on the chart as points of reference.
iOS Leads In App Market Share
In spite of Android’s rapid rise and current lead in device market share, iOS continues to lead in terms of time spent in apps. Total time in Android apps nearly equaled that in iOS apps in March of 2012, but it has declined somewhat since then, after the launch of the 3rd generation iPad.
Considering that there are more active Android devices than iOS devices but iOS users collectively spend more time in apps, it’s not surprising that more time per device is spent in iOS apps than in Android apps. The exact proportion of time spent in apps per Android device relative to iOS devices is shown below.
Why Doesn't App Share Follow Device Share?
An obvious question that arises when looking at the charts above is why app usage shares don’t follow device shares. We think there are at least three possible explanations.
One is that at least up until now the two dominant operating systems have tended to attract different types of users. Once Apple established the app ecosystem many of the consumers who purchased iOS devices were doing so to be able to run apps on those devices. They were buying a computer that fit in their pocket or purse. In contrast, many Android devices were provided free by carriers to contract customers upgrading feature phones. To the extent that those customers were just buying replacement phones, apps may be a nice add-on, but not a central feature of the device.
A second possible reason for why Android’s share of the app market lags its share in the device market is that the fragmented nature of the Android ecosystem creates greater obstacles to app development and therefore limits availability of app content. Hundreds of different device models produced by many manufacturers run the Android operating system. App developers not only need to ensure that their apps display and function well on all of those devices, but they also need to contend with the fact that most devices are running an old version of Android because the processes for pushing Android updates out to the installed base of Android devices are not nearly as efficient as those for pushing iOS updates to iOS device owners.
The final possible explanation for the differences in device and app usage shares relates to the first two. It is that the arguably larger and richer ecosystem of apps that exists for iOS feeds on itself. iOS device owners use apps so developers create apps for iOS users and that in turn generates positive experiences, word-of-mouth, and further increases in app use.
While app share and device share are two key races in the competition for mobile supremacy, they are not the only races. Another that has been in the news recently is the race for profits, in which Apple is the clear leader. Apple also currently appears to be winning the race for developer attention – probably both because of its share of app usage as described above and because both surveys and anecdotal evidence indicate that iOS device owners tend to generate greater advertising and in app purchase revenue.
A side race that Android appears to be winning is that for the emerging world, where its lower prices and open architecture give it an advantage. Apple has taken notice of that and is fighting back with incentives, monthly payment plans and cash backs in several emerging countries. In India, for example, a Times of India article suggests that these programs have given the iPhone a 400% boost in sales in the past few months.
As we’ve shown, there are multiple contests for mobile market share occurring simultaneously. That raises a question about whether that is a temporary state that will eventually give way to a clear overall winner or if there can be multiple long-term winners. For the moment it seems as though the consumer is winning in that they are able to choose devices from two dominant ecosystems as well as several smaller ecosystems.
Flurry now measures apps used on more than 1 billion smartphones and tablets each month. As connected devices reach critical mass, marketers are more seriously incorporating mobile into the marketing mix. But there are pros and cons. While the collective size of the mobile audience is rivaling that of TV and other media, it still requires aggregating the audiences of many apps to reach what can be reached through a few TV programs. That said, the numbers are likely closer than you think. Additionally, mobile offers unique ways to engage consumers given its “always on, always present” characteristics.
In this report, we look into what it takes to reach comparably sized audiences across different media like television, print, online and mobile apps. We also drill down into how the size and engagement of the mobile app audience varies across days of the week and hours of the day, and how it presents unique opportunities.
Let’s start by considering when people use apps.
The chart above shows how app usage varies over the course of a day, cut by weekend versus weekday. Data used for this chart comes from the top 250 iOS and top 250 Android apps measured by Flurry Analytics during February 2013. Through the top apps Flurry sees, app usage spikes during primetime to a peak of 52 million consumers. Make a mental note of that number, because we’ll revisit it a little later.
Comparing weekday to weekend curves, the general shape is similar. App usage ebbs overnight and then grows throughout the day, peaking in the early evening. While weekends also have a distinct primetime window, they see higher daytime usage across the day between 9:00 AM – 5:00 PM, ostensibly when someone would normally be working. However, the overall difference in audience size during the day between weekdays and weekends is not substantially different. Let’s look at 11:00 AM, for example, when the number of people using apps varies the most between weekdays and weekends. The size of the audience during this time is only 25% greater on weekends. Looking at it another way, this means that during the normal workday, people use apps at least 75% as much as they do on weekends. This creates a unique opportunity for advertisers to reach desired audiences over the course of the day via mobile.
The App Audience: Big But Fragmented
Now, let’s return to that 52 million primetime app user number. To get to an audience of that size, you’d need to combine the circulation of the largest 200 weekend newspapers in the U.S. or combine the audiences for the 3 most highly rated primetime TV shows during a good TV week (e.g., The Big Bang Theory).
We believe this comparison says a couple of important things about the app audience: first that it has reached critical mass, and second that it is still highly fragmented relative to more traditional forms of media. Additionally, while we don’t compare costs in this study, it is far more affordable to reach an audience on mobile versus Print or TV.
Now let’s consider how the app audience compares to the audience that is reachable through larger digital devices like laptops and computers. Flurry measured 224 million monthly active users of mobile apps in the United States in February of this year. During the same month, comScore counted 221 million desktop and laptop users of the top 50 digital properties in the United States. From this, we conclude that the U.S. audience that is reachable through apps, albeit more fragmented, is now roughly equal to that which can be reached on laptops and desktops.
There’s An Audience for That, on Mobile.
Earlier this year, Morgan Stanley analyst Benjamin Swinburne showed that “There has been a 50 percent collapse in broadcast TV audience ratings since 2002.” As the prized 18 – 49 year old demo is further lured to digital media, marketers need to adjust. But the mobile industry also needs to do more to make media planning and buying more efficient for advertisers and agencies.
The more mobile ad networks increase their ability to deliver the right combination of reach and targeting, the easier it will be for advertisers to invest in mobile and leverage the unique value it offers. Mobile, in particular, can deliver different ads to different users within the same app or the same ad to similar types of people across different apps, based on the varying interests of those individuals. Dynamic segmentation is much more possible on mobile compared to earlier forms of broadcast media. Now, fast forward one year from now, by which time Flurry estimates the installed base of smartphones and tablets will have doubled to 2 billion active devices per month. That should leave marketers of nearly every product thinking: on mobile, there’s an audience for that.
Five years ago, the iPhone ushered in the era of mobile computing. Today, more than a billion consumers are “glued” to these devices and their applications, impacting nearly every aspect of their lives. For businesses, opportunities seem endless and disruption is everywhere. The list of disrupted industries is long, including communications, media and entertainment, logistics, education and healthcare, just to name a few.
The past five years at Flurry have been wildly exciting. We joined an industry just as gas was forming to ignite a Big Bang, and we’re still orienting ourselves within its rapidly expanding universe. Since early 2008, we’ve worked with tens of thousands of developers to integrate our analytics and ad platforms into their apps. Today our services have been added to more than 300,000 applications and we measure usage on more than 1 billion monthly active smart devices.
On the five-year anniversary of launching Flurry Analytics, we took some time to reflect on the industry and share some insights. First, we studied the time U.S. consumers spend between mobile apps and mobile browsers, as well as within mobile app categories. Let’s take a look.
Today, the U.S. consumer spends an average of 2 hours and 38 minutes per day on smartphones and tablets. 80% of that time (2 hours and 7 minutes) is spent inside apps and 20% (31 minutes) is spent on the mobile web. Studying the chart shows that apps (and Facebook) are commanding a meaningful amount of consumers' time. All mobile browsers combined, which we now consider apps, control 20% of consumers' time. Gaming apps remain the largest category of all apps with 32% of time spent. Facebook is second with 18%, and Safari is 3rd with 12% Worth noting is that a lot of people are consuming web content from inside the Facebook app. For example, when a Facebook user clicks on a friend’s link or article, that content is shown inside its web view without launching a native web browser (e.g., Safari, Android or Chrome), which keeps the user in the app. So if we return to the chart and consider the proportion of Facebook app usage that is within their web view (aka browser), then we can assert that Facebook has become the most adopted browser in terms of consumer time spent.
The App World
Five years into its existence, the app economy is thriving, with The Wall Street Journal recently estimating annual revenue of $25 billion. Once again, we have to appreciate that this economy did not exist until 2008. As we looked for possible signs of slowing, we could not find any, largely due to the fast adoption of tablets just after smartphones.
In fact, not only is the installed base of devices growing, but also the number of apps consumers use. Our next insight comes from studying how many apps the average consumer launches each day. For this snapshot, we compared three years of worldwide data, taking the 4th quarters of 2010, 2011 and 2012.
From left to right, we see that the average number of apps launched per day by consumers climbs from 7.2 in 2010 to 7.5 in 2011 and finally to 7.9 in 2012. This is not a material change, which is a good thing. To us, the steady growth rate indicates that the app economy is not yet experiencing saturation, as consumers steadily use more apps over time. And while there are more apps in the store, large numbers of them have short lifespans, such as books, shows and games. Assertions that people are using fewer apps in 2012 than they did in 2010 appear to be incorrect. While one could observe that consumers use only 8 apps per day among the million+ available between the AppStore and Google Play, one also needs to remember that the 8 apps each consumer uses varies widely. This creates a marketplace that can support diversified apps.
Finally, we studied a sample of more than 2.2 million devices that have been active for more than 2 years to understand the mix of new versus existing apps people use over time. To do so, we compared Q4 2012 to Q4 2010.
The chart above shows that, on average, only 17% of the apps used in Q4 2010 were in use earlier in the year on a device compared to 37% in Q4 2012. That means that 63% of the apps used in Q4 2012 were new, and most likely not even developed in 2011 (or possibly poorly adopted). We believe that with consumers continuing to try so many new apps, the app market is still in early stages and there remains room for innovation as well as breakthrough new applications.
The Web World
Looking again at the first chart in this study, while also considering the latest numbers from IDC, which projects that tablets will outsell desktops this year and notebooks next year, we draw the conclusion that the web, as we know it, is already facing a serious challenge. Does this mean the web is dead? We don’t believe so. On the contrary, we believe that the web will change and adapt to the reality of smartphones and tablets. Websites will look and behave more like apps. Websites will be optimized for user experience first and search engine optimization second. This supports the trend of mobile first and web second, which brings both mobile app and user experience design to the mobile web. Simply compare Target’s app on iPhone to its mobile web site (target.com) accessed from the iPhone. The mobile web site looks and behaves similarly to the Target app, albeit a little bit slower.
… and Facebook
Continuing to think about the first chart, it appears that mobile, once perceived as Facebook’s Achilles' heel, has become Facebook’s biggest opportunity. Consumers are spending an average of nearly 30 minutes per day on Facebook. Add to that Facebook's massive reach, as well as their roughly billion mobile users per month and you have a sizable mobile black hole sucking up peoples' time. The 30 minutes a day is a worldwide average which means a large group spends even more time on Facebook (possibly hours) watching and participating in what has become the ultimate reality show in which the actors are you and your friends.
The disruptive force of the mobile app economy has created opportunities, rising stars, instant millionaires, dinosaurs and plenty of confusion. However, one undeniable truth is that tablets and smartphones are eating up desktops, and notebooks and apps (including the Facebook app) are eating up the web and peoples’ time.
Flurry now detects about 1 billion smartphones and tablets in use around the world every month. In the last 30 days, we saw activity on more than 2,000 unique device models. As the device base grows, we’re seeing an increasing variety of screen sizes, from sub-smartphones to full-size tablets and beyond. This poses both challenges and opportunities for developers who must consider how audiences, usage behavior and app category affinities vary by form factor.
This report reveals which form factors and screen sizes consumers use most, and for what categories. For this study, we focused on the top 200 device models, as measured by active users in Flurry’s system, which represent more than 80% of all usage. Doing so, five groups emerged based on screen size:
1. Small phones (e.g., most Blackberries), 3.5” or under screens
2. Medium phones (e.g., iPhone), between 3.5” - 4.9” screens
3. Phablets (e.g., Galaxy Note), 5.0” - 6.9” screens
4. Small Tablets (e.g., Kindle Fire), 7.0” - 8.4” screens
5. Full-size tablets (e.g., the iPad), 8.5” or greater screens
Mid-Sized Smartphones Dominate. Phablets are a Fad.
The top bar in the chart below shows how the top 200 device models break down by form factor in the market. Starting from the left, 16% of devices have screen sizes that are 3.5 inches or fewer in diagonal length. 69% of devices are between 3.5 inches and 4.9 inches, which includes iPhone. The light gray are made up of “phablets” such as the Galaxy Note. The orange are small tablets such as the Kindle Fire and iPad Mini. Finally, the far right shows that 7% of the device models in use are full sized tablets such as the iPad. The two bars below show distributions by active devices (taking into account that some device models have more users than others) and the number of app sessions (taking into account that some device models get used for more app sessions per user than others), respectively.
Notice that while 16% of the device models in the market are small phones, they account for only 7% of active devices once users per device are taken into account and 4% of overall app sessions. The opposite is true for tablets, which account for 7% of the top 200 device models yet 15% of all active users and 13% of all app sessions. On the small end, we believe this is because smaller device models, including most BlackBerry devices, are older and therefore have fewer active users per model. They are also not as well-suited to apps because of their small screen sizes. Full-size tablets, however, are ideal for using applications and therefore see a disproportionately higher percent of sessions. They also tend to have more users per device model since this class of devices has been dominated by iPad.
The ‘Is it a phone or is it a tablet’ devices otherwise known as phablets have attracted interest, but currently command a relatively small share (2%) of the device installed base, and their share of active users and sessions is also relatively small.
Form Factor Varies by OS
Not surprisingly, the form factor share of device models and active device users varies by operating system. The chart below shows share of active users by form factor for the different OSs. Inspecting the chart, medium phones are the dominant form factor on all operating systems, except Blackberry, which still has more active users on small phones. Android owns the phablet market and also has the greatest proportion of devices using small tablets. iOS has the greatest share of active devices using large tablets. The only Windows device models that are in the top 200 device models in terms of active users are medium-sized phones.
Tablets Are Gaming Machines
The chart below shows how total time spent in select popular categories is distributed across form factors.
Starting at the top, notice that nearly a third of time spent playing games take places on larger devices, namely full-sized tablet, small tablets and phablets. And while they command consumer time spent, they represented only 15% of device models in use in February and 21% of individual connected devices. These differences are statistically significant.
Studying books and videos, it’s somewhat surprising that tablets, which possess larger screens, do not see a larger proportion of time spent. An explanation for the high concentration in time spent in smartphones could be that consumers watch videos from their smartphones on-the-go (e.g., commuting to work on public transit), whereas they opt for a bigger screen to watch video (e.g., computer or TV) when at work or home. We expect that tablets may represent a greater share of time spent in book and video apps in the future as tablet ownership expands and tablet owners branch out into more types of apps.
Consumers Signal Preference for Smartphones & Tablets
As OEMs experiment with an ever-expanding array of form factors, developers need to remain focused on devices most accepted and used by consumers. From our study, consumers most prefer and use apps on medium-sized smartphones such as the Samsung Galaxy smartphones and full-sized tablets like the iPad. In particular, smaller smartphones under-index in terms of app usage compared to the proportion of the installed base they represent, and would suggest they are not worth developers’ support. Phablets appear to make up an insignificant part of the device installed base, and do not show disproportionately high enough app usage to justify support. Tablets, on the other hand show the most over-indexing of usage, especially in games. The success some game developers are having with a tablet-first strategy, like dominant game maker Supercell, may also inspire developers of other types of apps to consider focusing on tablets.
GDC is in San Francisco this week, just next to Flurry’s headquarters. By the size of the crowds, we (very scientifically) estimate that attendance should easily surpass last year’s record of 22,500. Having tracked the growth of mobile games for several years, we weren’t surprised to see more than 30 sessions during the week focused on smartphone and tablet gaming.
Here’s the big picture, based on our estimates: There are now over 1 billion active smartphones and tablets using apps around the world every month. And of all the apps consumers use, games command more than 40% of all time spent. Looking at revenue, games also dominate. Today, for example, 22 of the top 25 grossing apps in the U.S. iTunes App Store apps are games. Gamers spend money, and game makers are in love.
In this installment of research, Flurry studies how age, gender and engagement vary across key game types. Understand this, and a game developer can design a more engaging game that appeals to the right audience. In short, they can build a better business. In this study, we included more than 200 of the most successful free iOS games, with a total audience of more than 465 million month active users. For a better comparison, we organized these games by their game type (aka game mechanic) instead of traditional, less granular genres. Let’s start by looking at how different kinds of games appeal to gamers by age and gender.
The chart above plots game types by age and gender. From left to right, we show what percent of the game audience is female, with the far right equaling 100% female. The opposite is true for males. For example, 0% female equals 100% male. From bottom to top, we show the average age of the game type’s user base, between 20 to 50 years old. Putting it together, games in the upper right quadrant are preferred by older females. Games in the lower right are preferred by younger females. Games in the lower left are preferred by younger men, and so on.
Young Men and Their Competition
Inspecting the chart, the tightest cluster appears in the lower left; specifically, game types such as Shooters, Racing, and Action RPG skew younger and more male. Card-battle and Strategy games also skew toward younger males. The only genre that skews toward males over 35 is Casino/Poker, with pure poker games skewing even more male than the game type as a whole. This appears to leave a big gap in the market for developers who can create games that appeal to middle-aged and older men.
While men tend to gravitate toward competitive games, women gravitate toward games that are less competitive and tend to be played in a more enduring way. These include Management/Simulation games where players can build out an environment, Social Turn-Based games in which they can play over time with friends, and Match3/Bubble Shooters and Brain/Quiz games, to which users can frequently return when they have a few spare minutes. Slots and Solitaire are both solo-play game types that skew toward females who are over 40, suggesting that they serve as long-term time-fillers.
From a marketing perspective, mobile game publishers can also leverage this knowledge to design targeted campaigns appropriate for the kind of audience to which a game appeals. Flurry’s ad network, AppCircle, allows publishers to target specific demographics for efficient spending.
From Courting to Betrothed
We find that mobile gamers tend to prefer playing a few kinds of games and demonstrate highly predictable play patterns. In other words, they form relationships with their games. Savvy publishers understand these dynamics and use them to inform acquisition strategy, gameplay design, and both in-app purchase and ad-based monetization tactics.
In the chart below, we map game types by usage and retention. On the y-axis we show the number of times per week consumers play different game types. On the x-axis we show how long different games retain their user (i.e., Flurry defines Rolling Retention as the percentage of users that return to the game 30 days after first use, or any day after that). To see how usage and gender work together, we’ve also colored-coded game types by whether they are more male, female or neutral in appeal. Let’s take a look.
The chart above reveals that different strategies should be employed for different kinds of games. It also shows, loosely, that women are more committed while men are more fickle. Sound familiar in life? Hmmm. For the gaming industry, the universal take away is that to optimize engagement, retention, and monetization, developers must tailor their mechanics and messaging to match their ideal target audience. Let’s take a tour of the quadrants.
“Players” try a lot of different games, play for only a short time and tend to be found in highly competitive games (e.g., “Player vs. Player style games). While fickle, they tend to have a high willingness-to-pay in order to progress faster in a game or increase their ability to compete at a high level versus other players. Attracting the right users through targeted acquisition can pay off, as those that stay will pay. Notably, Card-Battle games have very low retention but off-the-charts monetization, extracting enormous revenue from the small number of users that stick. One implication is that these games need to be highly polished at launch with updates ready to go, as gamers will discard games quickly and move on if the game fails to resonate. From a design standpoint, these games should offer immediate opportunities for users to advance by purchasing upgrades and boosts. For the users that might not spend, a lucrative option is to offer in-game currency for watching video ads.
“Going Steady” game types are found in the lower right quadrant of the chart. Usage is less frequent but retention is very high. While these gamers don’t play as often, they are loyal. This group of games tends to be easy-to-learn and easy-to-return-to even after a lapse in playing. They lend themselves to quick play while in a “wait state” (e.g., waiting in line, taking a bus or perhaps checking out of the meeting or class they’re in). Since these are not particularly immersive or competitive games, they are less likely suited to in-app purchase. However, they can generate significant ad impressions over time, and can be designed to show banner or interstitial ads without being overly disruptive to the experience. For games with larger audiences, publishers are utilizing mediation platforms that enable the use of multiple ad networks in one system, ensuring maximized fill and ad-revenue for each space.
“Committed” comprise of consumers who play games for the long-haul. As such, game makers should think of it like a marriage. Think about appoint mechanics like setting a date (hey, even married people need to keep it fresh). These games should be designed with deep content and not try to sell too hard to their users too quickly. From a monetization perspective, commitment-oriented games have great potential for in-app purchases since users of those games are likely to value such purchases and amortize them over long periods of gameplay. And while only the largest titles have achieved this to-date, this group of games are great candidates for in-app product placement. Additionally, with high impressions counts, it is worth publishers’ investment to implement monetization platforms that make ad spaces available to real-time bidded ad exchanges, ensuring they reach the brands and advertisers that value their audiences.
“Infatuated” consumers have fallen hard and fast for their games, but the candle that burns twice as bright burns half as long. They have crushes, and show binge behavior. During the “crush” window, the developer needs to work hard to extract as much revenue as possible. As such, developers must provide vast amounts of content to the users, consistently, in a short-window. Matching monetization to game type, the competitive nature of Strategy games, and Slots users’ incessant desire for in-game currency, make a solid in-app purchase strategy paramount. Sales, events, and purchase opportunities timed with key moments of emotional investment can drive significant profits for publishers.
There’s a Pebble on the Beach for Everyone
In gaming, there are a vast number of game types that attract distinct audiences. And these different consumer segments display very different usage patterns, which have direct implications on monetization strategies. As in life, where the richest relationships are borne from knowing oneself and his or her partner, game companies must also understand both. Only then can you get the most out of the relationship.
Just as a company might look to metrics such as their Net Promoter Score or individuals might look to their Klout Score to judge their social media influence, app developers want benchmarks to evaluate how their apps are doing relative to other apps.
To provide benchmarks, we studied apps by their retention and size of user base. We also compared these two dimensions to see how they relate to one another. For example, do apps with more users have stronger retention than those with fewer users due to network effects? Do apps with smaller audiences see higher retention because they focus more on the interests of a particular segment?
Apps By Number of Users
We started our investigation by identifying the apps that Flurry tracks that had at least 1,000 active users at the start of November 2012. That eliminated apps that were being tested or were no longer being supported. We then split apps into three equal-sized groups based on their total number of active users. To be in the top third of apps, an app needed to have 32,000 active users. To be in the top two-thirds, it needed to have 8,000.
Apps By Retention
We followed a similar process to categorize apps based on retention. For this analysis, retention was defined as the percent of people who first used an app during November 2012, who also used it again at least once more than 30 days after their first use. To be in the top third for retention, an app needed to have at least 37% of those who started using the app in November do so again more than 30 days later. To be in the top two-thirds, 22% of new users in November needed to use the app again more than 30 days later.
Combining User Numbers with Retention
Having classified apps into three groups based on both active users and retention, we then compared how the two metrics relate to one another. The proportion of apps that fall into each of the nine categories that result from considering retention and active users jointly is shown in the table below. If active users and rolling retention were completely independent, then approximately 11% of apps would be in each of the nine categories. As shown in the table, the mid level categories for each metric follow that general pattern, but the categories in the corners of the table don’t. The differences between what the distribution across the nine categories is, and what it would be if the two dimensions were completely independent, is statistically significant.
Fifteen percent of apps are in the enviable position of being the top third for active users and also in the top third for rolling retention. We refer to those as Superstar apps since they perform well on both dimensions. These apps are best positioned to generate revenue regardless of their monetization model. Another 17% of apps are at the opposite extreme: they are in the bottom third for both user numbers and retention. We refer to that category as a Black Hole. Apps in this “cell” could be relatively new apps that are still trying to establish a user base, old declining apps or apps that are of poor quality.
Possibly the most interesting apps are in the bottom right and top left corners of the table. We refer to the 6% of apps in the bottom right category as Red Dwarfs because they have a relatively small user base yet are doing well on retention. Those are likely to be successful long tail apps. In the opposite corner from that are 6% of apps we refer to as Shooting Stars since they have a lot of users, but may fade away quickly due to poor retention.
Time Spent by Retention and Active Users
Unsurprisingly, the average number of minutes per month users spend in high retention apps is greater than in low retention apps. This can be seen going from left to right in each row of the table. For example, Superstar apps have almost twice the average number of minutes per user than Shooting Star apps, 98 minutes versus 50 minutes. This correlation between average time per user and retention is statistically significant.
Average time per user per month is also positively correlated with the number of active users. This can be seen by looking from the bottom to the top of each column in the table. For example, users spend more than 50% more time in Superstar apps than in Red Dwarfs. Once again, this correlation is statistically significant; however the correlation between time per user and retention is stronger than that between time per user and active users.
Retention, Retention, Retention
These results imply that developers need to make retention their top focus. Developers can impact retention by shaping and modifying the app experience. It’s within their control. Furthermore, the association between retention and time spent implies that retention drives revenue. More repeat usage means more opportunities to generate revenue from in-app purchase and advertising. Finally, the more useful and compelling an app, the better it retains users, making acquisition efforts more efficient. Acquiring aggressively before an app retains well can be a costly mistake. On the flip side, an app that retains well can generate powerful word of mouth, which is the ultimate (and free) promotional machine. The more a developer masters retention, the better their chances of turning their Red Dwarfs into Superstars.
Suppose you’re an app developer who wants to ensure that your app is optimized to function well on 80% of the individual connected devices currently in use (e.g., my iPad, your Windows phone). How many different device models (e.g., Kindle Fire HD 8.9" Wi-Fi, Galaxy S III) do you think you need to support? 156. Maybe you’re okay with having your app optimized for only 60% of active devices. That still means that you need to support 37 different devices. Even getting to 50% means supporting 18 devices, as shown below. If you’re a large or particularly thorough app developer, reaching 90% of active devices will require supporting 331 different models.
The dominance of iOS and Android platforms has obscured the proliferation of connected device models. During January, Flurry detected 2,130 different device models with active users (defined as having app sessions during January), including 500 different device models with at least 175,000 active users.
20% of Device Models Is Still a Big Number
Using the 80/20 rule, the market for devices might even seem concentrated: just over 7% of device models account for 80% of active users. Still, the large total number of device models in use poses challenges for developers.
It’s obvious that different apps are required for different platforms. Developers can choose to serve only a portion of the app market by developing apps for only a subset of operating systems (and consequently a subset of device models). Even having made that choice, though, adaptations may be required to accommodate different versions of the same platform (e.g., iOS 6.x versus iOS 5.x, forked versions of Android, etc.), smartphones versus tablets and the increasingly wide variety of screen sizes and aspect ratios in which those devices are now available.
Developing apps on the device models that represent the majority of devices currently in active use has become an expensive and time-consuming process. Not optimizing or testing apps on devices being used by even a minority of people exposes developers to negative user experiences and potentially to buying expensive devices to troubleshoot problems as they arise.
Is the Market for App Development Ripe for Consolidation?
This fragmentation has the potential to change the app ecosystem by making it harder for small developers to compete since they are unlikely to have the resources to support the growing list of device models currently in use. They may also be disadvantaged in economies of scale in promotion (including word of mouth) if their apps are not available or do not work well on most device models. Scale is likely to be increasingly important when it comes to app development and that may lead to consolidation within the app development industry.
Developer surveys, such as Vision Mobile’s, consistently show that the revenue distribution for app developers is highly skewed: only a minority of developers make more than $500 per app per month. The increasing need for scale to ensure full functionality on the full range of connected device models in use may help explain why. The growing challenge of discoverability in an increasingly crowded app market is also likely to be part of the explanation.
So what is a small developer to do? One strategy is to focus on the device models used by the greatest number of people. Surveys consistently show that developer commitment to iOS is disproportionately strong relative to the market share for iOS devices. Our results suggest this trend is probably a consequence of developers seeking efficiency (the most users for the least work) because device models running on the iOS platform average 14 times the number of active users than device models running on other platforms. This is shown in the chart below in which the average number of active users for device models running on different operating systems are indexed to Android (where Android = 1).
It’s difficult to fully disentangle platform from manufacturer and comparing devices made by Apple to devices made by the three other device manufacturers with the greatest average number of active users per device model tells a similar story. This is shown in the chart below – this time indexed so the average number of active devices per Samsung device model = 1. As shown in the chart, on average Apple device models have more than seven times as many active users as Samsung device models and more than four times as many as Amazon device models.
App Sessions Are More Concentrated than Active Devices
Of course, some people use their devices more than others and many developers prefer to target heavier app users. So what about app sessions? They are somewhat more concentrated than active devices. As shown below, for developers to ensure they were optimized on the devices responsible for 50% of app sessions conducted during January, they would have needed to support only eight different device models and to cover 80% of sessions they would have needed to support 72 different device models. That’s still a lot of device models, but it’s less than half the device models required to reach 80% of active devices.
In addition to having more active devices per device model than other platforms, iOS device models average more app sessions per active device than device models running on other platforms. This is shown below, again using an index for which app sessions per active Android device are set to one. This further clarifies why developer support for iOS is disproportionate to iOS’ share of the installed device base. Developers can reach more active devices by developing for a smaller number of device models on iOS and they can also capture the attention of very active users. People who have iOS devices tend to have more app sessions, creating more opportunities for in app purchases, advertising revenue and paid app purchases.
Viewed at the manufacturer level, Apple device models average more sessions per device than device models made by the other manufacturers previously shown. This is shown below, again indexed so that average sessions per Samsung device = 1.
The App Development Company
With competition in the device market heating up, manufacturers seem likely to fill and expand product lines with an increasing number of devices intended to differentiate themselves and address the preferences of specific types of users. That implies that it will only become more difficult for developers to optimize, test and support their apps for use on all device models. And yet doing exactly that is likely to be increasingly important for app developers given the market for apps is also becoming more crowded and more competitive, making negative user experiences more damaging. Promoting apps and leveraging that investment in promotion across as many potential users as possible will also become all the more critical. Putting all of this together, we expect a future in which app developers are less frequently individuals with a creative idea and a laptop and more frequently, companies designed to develop, produce and distribute apps at scale.
Flurry recently revealed that China’s installed base of smartphones and tablets surpassed that of the United States. Further, two thirds of all app sessions now occur outside the United States. With the app market becoming increasingly international, developers need to better understand how app consumer behavior varies across different countries to remain competitive.
This report focuses on how the top 30 heaviest app using countries vary in terms of app usage. As developers build apps for the largest international markets, they need to consider deviating from what has worked in the United States, the former number one market. Can developers simply localize for different markets, or are there meaningful cultural differences in app usage to consider? How different is behavior in China and India, the world’s two most populous countries?
For this study, Flurry grouped countries according to their similarity in app category usage using cluster analysis. Cluster analysis is a statistical technique that creates groupings based on associations; in this case, among the proportions of app users who use different categories of apps. This technique controlled for differences in populations, device penetration rates and app store taxonomies. We ran this analysis for the top 20,000 apps in the 30 heaviest app using countries as of January 2013. For purposes of this report, we focus on app categories used by at least 5% of app users in at least one country cluster. We also excluded social networking, since use of those apps tends to be more country-specific.
Membership in the resulting country clusters are discussed next, followed by a description of some of the differences in app engagement across country clusters.
App Usage Around the Globe
The cluster analysis process produced six country groupings shown in the map below and the country list that follows.
As shown in the map above, the first group of countries in blue is made up of countries that tended to be early adopters of mobile technologies.
The second category, in purple, is comprised of the most hyper-connected parts of Asia: South Korea, Hong Kong and Taiwan.
China and Japan had app usage patterns that were unique to them, making each country its own cluster.
Most of the countries in green are neighbors in South East Asia; however, app usage patterns across the Pacific in Mexico also put it in that same category.
The final category, in yellow, includes many large countries, such as Brazil, Russia and India as well as smaller but influential countries such as Switzerland and Israel. Besides sharing similarities in app usage, these countries tend to have lagged behind the Mobile Pioneer and Connected Asia countries in adopting mobile technologies.
Countries shown in gray were not included in the analysis because they are not among the 30 heaviest app using countries.
Interest In Gaming Is Global. Genre Preferences Are Local
The chart below shows the proportion of app users who used apps within each of the gaming categories shown, as defined in Google Play, during January 2013.
Overall, games are the most-used types of apps in each country cluster, with the biggest Android game category being Arcade and Action games for all country clusters. While Android game categories follow a similar rank ordering across country clusters, there is clear variation between clusters. For example, compared to app users in Japan, almost twice the proportion of app users in the Equatorial Pacific country cluster use Android Arcade and Action games. And while countries in the Mobile Pioneers’ cluster are among the most enthusiastic users of Casual Games and Brain and Puzzle Games, they are less enthusiastic users of Arcade and Action games compared to those in most other country clusters.
The chart below shows similar data for iOS apps within each of the gaming categories as defined by the Apple App Store. Please note that these classifications have changed over time and that games are assigned to categories by developers; however those things are common to all countries and therefore should not, on their own, result in differences between countries.
Once again, note that the main Games category attracts a large proportion of people who use any iOS apps, and that the Equatorial Pacific has the greatest proportion of users and Japan has the least though the differences are not as great for iOS as they are for Android. It’s interesting to note that while Japan tends to lag the other country clusters in the proportion of device users engaging with most game app categories, the country that gave us karaoke leads in the proportion of app users who use iOS Music Games.
Interest In Productivity and Utility Apps Varies
While Japanese app users are disproportionately unlikely to play most types of games (with the exception of music, as noted above), they are disproportionately likely to use productivity and utility apps. Chinese app users are also disproportionately heavy users of these more functional types of apps.
Use of More Lifestyle-Oriented Apps Maps To Offline Behavior
Hobbies often associated with Japan came through in app usage for music games, and also in use of lifestyle-oriented apps in terms of Japanese enthusiasm for photography. Japanese device owners are more likely than device owners in other country clusters to engage with photography apps on both iOS and Android devices. Entertainment categories within both app stores are fairly broad so it’s not entirely clear why, but those from China and the Lumbering Giant country clusters are disproportionately heavy users of Entertainment apps on both of the major mobile operating systems.
Mapping the Future of Apps
While this analysis only scratches the surface of variation in usage of 20,000 apps across more than 800 million devices being used in 30 different countries, it shows systematic variation across country clusters even at a high level. This has important implications considering the great potential for growth of connected devices and app use in countries and country groupings such as China and the Lumbering Giants, given their large populations and relatively low current rate of device penetration. App usage patterns in those places don’t always mirror those in Mobile Pioneer countries, which up until now have been the source of a lot of app development. For example, productivity and utility apps are more popular in China and Japan than they are in the United States. Differences such as these suggest that app developers in Mobile Pioneer countries may need to give greater consideration to the usage patterns and preferences of those in other countries or else that we may see growing app developer communities in some of those other countries.