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.
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.
Regardless of a company’s earlier success, thriving in the new mobile app economy depends on engagement and retention. After acquiring users, the real battle to keep and ultimately monetize consumers begins. In the brave new world of “mobile first,” engagement is the new battleground.
This research is a redux to one of Flurry’s most popular reports, entitled Mobile Apps: Money, Models and Loyalty. Released three years ago, the initial report organized app category usage into a loyalty matrix. We do the same again now, while also acknowledging that a lot has changed in the app economy since then. To start, there is an order of magnitude more available apps in the App Store, now brimming with over 700,000 app choices for consumers. We are three generations beyond the then-new iPhone 3GS. We have since met the iPad, and perhaps tomorrow will meet the iPad Mini.
Combined, smart devices – iOS and Android smartphones and tablets – are the fastest adopted technology in history; adopted faster than electricity, televisions, microwaves, personal computers, cell phones, the Internet, dishwashers, stoves, and a whole lot more. Last month, Mark Zuckerberg, CEO of Facebook – the number two most visited website on the web – declared “we are now a mobile company” explaining that “you just could do so much better by doing native [application] work” versus using languages like HTML5 on top of browsers. Each month, approximately 600 million of Facebook’s 1 billion monthly active users already accesses Facebook via mobile.
Each app category has different user engagement and loyalty characteristics. Understanding a given app audience based on the category to which it belongs can inform a company’s app acquisition, retention and monetization strategies. For this analysis, we use a sample of apps used more than 1.7 billion times each week. In total, more than 80,000 companies use Flurry Analytics across more than 230,000 apps to understand consumer behavior and improve their apps.
The above matrix plots application categories by how often they’re used compared to how long consumers continue to use them over time. Specifically, we plot the 90-day retention rate of app categories on the x-axis against the frequency of use per week on the y-axis. We lay the “scatterplot” out in a Cartesian coordinate system with four quadrants. For our categories, we started by taking the application categories defined by Apple in the App Store. In cases where a cluster of applications within a parent category showed meaningful usage differences, we created a sub-category. For example, Flurry divides games into Social Games and Single Player Games given how differently consumers use these sub-categories.
Quadrant I includes apps that are used intensively and to which consumers are loyal over time. News and Communication apps are the two categories that appear in this category. On average, because these apps tend to have stable, growing audiences, they are best positioned to generate advertising revenue or charge a subscription. Consumers perceive these apps to deliver enduring value over time.
Quadrant II is comprised of apps that are used intensively, but for finite periods of time. They are perceived by consumers to deliver value in bursts. Streaming Music, Dating and Social Games best typify this quadrant. Consider for a moment why Dating is a category that appears in this quadrant. For most people, we can assume that finding a long-term “significant other” is the ultimate goal of dating. As a result, the app maker should expect customer churn. While usage may be high during the time when a consumer looks for a suitable partner, once that person is found, usage stops. An implication could be that to maintain a growing audience, apps in this category require heavy, constant acquisition to find consumers who are “in the market” for dating. Ironically, the better the app is at match making, the more churn it should expect.
Quadrant III contains apps that are used infrequently and have high churn. They contain the most “one-and-dones.” Personalization is an example that makes sense for this quadrant, since a consumer uses this app to change her screen saver or select a theme for her operating system. Once this set-up is complete, it’s unlikely that the user will need to re-use this application. Since the app’s value is diminished almost immediately, applications with this kind of usage pattern are best served with premium pricing models; that is, charging the consumer before providing access to the content.
Quadrant IV is made up of apps that are used infrequently but deliver very high value when used. Even though they’re used only occasionally, these apps can remain on a consumer's handset almost indefinitely. For example, consider how useful an airline, hotel or rental car-booking app is to a business traveler. While the app remains unused between business trips, its value spikes as soon as the next business trip needs to be scheduled.
Which Pill to Take
The quadrant an app falls into can help the content creator decide what business model is best. On average, Quadrants I and IV (the right-hand side) are better suited to subscription and advertising-supported models. The main reason is that these apps have perceived enduring value by consumers over a long period of time, and therefore more successfully retain their user bases. For ad-supported apps, high repeat usage translates into more ad impressions served. Categories on the left-hand side, Quadrants II and III, are better suited for one-time download fees. Additionally, quadrants II and IV (top left and bottom right) are likely best for in-app purchase models. For Quadrant II, the intense usage means that consumers find very high value during a short window. This creates the opportunity to offer new content or functionality during “binge” usage. Adroit social game makers are masters at driving in-app purchases during a consumer’s greatest moment of engagement. For Quadrant IV, because the user will return again and again, there also exists the possibility to find new ways of increasing value, which includes offering add-on functionality or content for a fee.
For more data, the table below provides 30, 60 and 90-day retention rates as well as weekly frequency of use numbers. Note that some of the categories included in the table below are not included in the matrix chart above.
Compared to Flurry’s 2009 analysis, 90-day retention rates have increased from 25% to 35%. Additionally, frequency of use has decreased from 6.7 in 2009 to an average of 3.7 now. We attribute increased retention rates to increased quality in the market, driven by more competition. With tens of thousands of more companies building apps and hundreds of thousands of more available apps, the quality of apps has risen dramatically. Simply put, app makers are getting better at holding a consumer's attention longer. Additionally, we believe usage rates are lower because consumers have more choice than ever and are splitting their time across more applications. While Flurry included 19 categories in its 2009 report, we now include 30 distinct categories as the industry has matured and more distinct verticals have appeared.
Brave New World
With more than a billion smartphones and tablets now in use, as well as the eventual move of apps into the living room through connected TV efforts by the likes of Apple and Google, digital distribution is changing the way the world does business. No matter what category your app belongs to, understanding and improving user engagement is the new currency of doing business in the new digital world.
Before Harry met Sally in the late ‘80s, the dating process typically involved an introduction from a friend. Then, with the Internet and email, dating evolved. By the time we were watching the movie You’ve Got Mail - and actress Meg Ryan was cementing her status as a romantic comedy lead - the concept of online dating was going main stream.
As a social ritual, dating is a human behavior easily accelerated by technology. And it’s big business. One recent study estimated that nearly 1 in 5 singletons, who have access to the Internet, use Internet dating. Another report stated that 17% of recent marriages in the U.S. were the result of online dating websites. In size, combining North American and European markets, the online dating industry well exceeds $2 billion in revenue. Within the world of mobile apps, the largest category on iOS and Android, behind gaming, is Social Networking, in which dating apps appear. Given the voracious consumer usage we’re observing, it may also be the smartphone’s second killer app.
In this report, Flurry compares the usage of dating websites (combined desktop and mobile web) to native mobile applications over the past 12 months. For Internet consumption, we built a model using publicly available data among the top 50 dating websites from Compete.com, comScore and Alexa.com. For mobile application usage, we used Flurry Analytics data, which now tracks over 90,000 mobile applications. With respect to dating, Flurry tracks a large set of dating apps with more than 2 million total users.
Let’s start with total time spent on eDating in mobile apps versus on the web. Note that for this report, we use the term “eDating” to encompass online and mobile app dating.
As you can see, mobile dating apps now command more time compared to online dating sites: 8.4 minutes vs. 8.3 minutes. A year ago, people spent more than twice as much time on the Internet for dating as they now do in mobile apps. However, mobile app usage has increased dramatically over the last year, from 3.7 minutes in June 2010 to 8.4 minutes in June 2011, overtaking online dating time spent. These findings parallel Flurry’s recent report that showed, in total, mobile app usage has overtaken Internet usage.
In terms of engagement, frequency of use is driving growth in time spent per day in mobile dating apps. Last year, the average user opened his dating app 2 times per day, a little under 2 minutes each time. Now he opens his app over 5 times a day, but for shorter periods of time, about 1.5 minutes per session.
Next, let’s look at the proportion of people who use the Internet vs. mobile apps for eDating.
The chart above shows that dating apps are more popular on smartphones than online dating sites are on the Internet. We measured this by looking at the proportion of unique users of dating services versus the total, per platform. For the Internet, we compared unique visitors of online dating sites versus the total number of people using the Internet, which totaled 12% in June 2010 and 13% in June 2011. For mobile apps, we compared unique users of mobile dating apps versus all apps, which yielded 15% in June 2010 and 17% in June 2011.
We also found that the number of people using dating apps is growing faster than the number using all apps. In short, dating is a growth category. Overall, the number of unique users of all applications increased 125%, year-over-year, while the number of unique users using mobile dating apps increased by 150% over the same period. Comparing Internet dating to mobile app dating directly, unique users in mobile dating apps now account for about one third compared to the number of Internet dating users, which has doubled over the last year.
In an age where Facebook allows consumers to display their relationship status and easily connect to friends of friends, we speculate why mobile dating apps are gaining unprecedented traction on iOS and Android. The first reason, we believe, is that dating itself is inherently local and better served by mobile. Now, unplanned meetings of two nearby matches is more of a possibility. Secondly, it seems that mobile apps facilitate better engagement throughout the day. Today’s eDater need not be in front of her computer to view potential matches, or to receive or send messages. Her phone is always by her side. Our engagement numbers regarding frequency and session length, described above, support this trend.
iOS and Android devices are versatile multi-purpose machines that have already significantly impacted the business models of music, games and other Media & Entertainment industry categories. And now, within the nexus of mobile-social-local, mobile dating apps appear to be looking for love in all the right places.
Although the Internet entered the mainstream a mere 15 years ago, life without it today is nearly incomprehensible. And our use of the web has rapidly changed as well. In simple terms, it has evolved from online directories (Yahoo!) to search engines (Google) and now to social media (Facebook). Built on the desktop and notebook PC platform, the web’s popularity is significant.
Today, however, a new platform shift is taking place. In 2011, for the first time, smartphone and tablet shipments exceed those of desktop and notebook shipments (source: Mary Meeker, KPCB, see slide 7). This move means a new generation of consumers expects their smartphones and tablets to come with instant broadband connectively so they, too, can connect to the Internet.
In this report, Flurry compares how daily interactive consumption has changed over the last 12 months between the web (both desktop and mobile web) and mobile native apps. For Internet consumption, we built a model using publicly available data from comScore and Alexa. For mobile application usage, we used Flurry Analytics data, now exceeding 500 million aggregated, anonymous use sessions per day across more than 85,000 applications. We estimate this accounts for approximately one third of all mobile application activity, which we scaled-up accordingly for this analysis.
Our analysis shows that, for the first time ever, daily time spent in mobile apps surpasses desktop and mobile web consumption. This stat is even more remarkable if you consider that it took less than three years for native mobile apps to achieve this level of usage, driven primarily by the popularity of iOS and Android platforms. Let’s take a look at the numbers.
The preceding chart compares the average number of minutes consumers spend per day in mobile native apps vs. the web. For mobile apps, Flurry tracks iOS, Android, BlackBerry, Windows Phone and J2ME. And for the web, our figures include the open web, Facebook and the mobile web.
Flurry found that the average user now spends 9% more time using mobile apps than the Internet. This was not the case just 12 months ago. Last year, the average user spent just under 43 minutes a day using mobile applications versus an average 64 minutes using the Internet. Growing at 91% over the last year, users now spend over 81 minutes on mobile applications per day. This growth has come primarily from more sessions per user, per day rather than a large growth in average session lengths. Time spent on the Internet has grown at a much slower rate, 16% over the last year, with users now spending 74 minutes on the Internet a day.
As a note of interest, Facebook has increasingly taken its share of time spent on the Internet, now making up 14 of the 74 minutes spent per day by consumers, or about one sixth of all Internet minutes. Considering Facebook’s recent leak regarding Project Spartan, an effort to run apps within its service on top of the mobile Safari browser, thus disintermediating Apple, it appears Facebook seeks to counter both Apple and Google’s increasing control over consumers as mobile app usage proliferates.
Games & Social Networking Dominate Mobile App Usage
With mobile app usage soaring, Flurry additionally studied which categories most occupy consumers’ time. For this snapshot, Flurry captured time spent per category from May 2011 across all apps it tracks, now totaling more than 85,000. The results are shown in the pie chart below.
The chart clearly shows that Games and Social Networking categories capture the significant majority of consumers’ time. Consumers spend nearly half their time using Games, and a third in Social Networking apps. Combined, these two categories control a whopping 79% of consumers’ total app time. Further, as we drill down into the data, consumers use these two categories more frequently, and for longer average session lengths, compared to other categories. Any way we slice it, Games and Social Networking apps deliver the most engaging experience on mobile today.
With a better understanding of how consumers spend their time across app categories, Facebook’s Project Spartan makes even more sense. As a category, social networking – which is Facebook’s core competency – commands the second largest allocation of consumers’ time. Games, which typify the most popular kind of app played on the Facebook platform itself, are also the top categories on both Android and iOS platforms. As interactive media usage continues to shift from the web to mobile apps, one thing is certain: Facebook, Apple and Google will all expend significant resources to ensure that no one company dominates owning the direct relationship with the consumer.
In 2006, European mobile analysts dubbed mobile the “seventh mass media channel” following print, recordings (e.g., albums, cassettes, DVDs, etc.), cinema, radio, television and the web. However, mobile failed to fulfill its promise. For mobile to have reached its true potential as a mass media channel, it needed to overcome slow and expensive carrier data networks, poorly managed carrier decks, and a heavily fragmented handset base which featured a myriad of small screens, weak processors, confusing user interfaces and clumsy WAP browsers. With so much friction in the channel, content creators were stymied in their ability to deliver compelling experiences to consumers, making mobile look far more like a niche than mass media channel.
Then, in 2007, the iPhone changed everything. In addition to unleashing a prolific media device, Apple wrested control of the storefront from carriers, convinced carriers to offer flat-rate data plans to consumers, tapped into blazing Wi-Fi as a pipe and shipped a useful mobile browser. Most importantly, they built a low-friction, robust channel through which content creators could distribute smartphone apps to consumers: the App Store.
In a few short years, with Apple as a game-changing catalyst, applications have already been downloaded tens of billions of times. Research firm, In-Stat, forecasts there will be 48 billion app downloads in 2015. With their success, apps already challenge the television in terms of reach and the Internet in terms of engagement.
For this report, Flurry used data from over 45,000 companies across their more than 85,000 applications. Flurry Analytics tracks over 15B user sessions per month across iOS, Android, BlackBerry, Windows Phone and J2ME.
Unprecedented and Accelerating Reach
The chart above shows the number of people actively using apps on their smartphones in May 2011 across the top five European markets. Flurry calculates active smartphones by first measuring its own penetration across these devices via apps into which Flurry Analytics has been integrated. For example, Flurry detects roughly 85% of all iOS and Android devices worldwide. We then grossed this number up, by country, for our estimates.
Combined, the top five European markets – the UK, France, Germany, Italy and Spain – actively use apps on 46 million devices each month. With a combined population of just over 240 million, for ages 13 and over, the addressable market through smartphone apps averages approximately 20% of the largest, most affluent European countries. Additionally, with a month-over-month growth rate (Compounded Monthly Growth Rate, CMGR) of more than 10% over the last two years, we project the installed base of smartphones will more than double over the next 12 months alone.
In the chart below, we show the smartphone app audience as a percentage of each top European country’s population, again ages 13 and over. The UK leads in penetration with a whopping 33% of its population using apps on smartphones per month. France places second with a sizable 20%, next followed by Germany, Spain and Italy coming in with 14%, 9% and 10%, respectively.
After having established the percent of each country’s monthly population that can be reached through smartphone apps, we next look at the pace of smartphone adoption, by country.
The chart above shows just how quickly the base of devices running smartphone apps is growing by country. While the UK and France are the most penetrated to date, as a percentage of their countries' populations, the laggard countries are closing the gap in terms of growth. Spain leads in growth of its active smartphone user base with a monthly growth rate of 14%. Germany and Italy’s active smartphone bases are both growing at 11%. Additionally, France and the UK continue to grow, month-over-month, by 7% and 6.7%, respectively.
With growing adoption of iOS and Android-based smartphones, the imminent release of Nokia phones based on Windows Phone 7, and the fact that the majority of consumers actively use applications, we predict that the growth of this mass market media channel will continue to grow until near total smartphone market saturation. To underscore just how aggressively this channel is growing, if we assumed the growth of smartphone adoption continued at their current rates, all five countries would have full smartphone penetration in just over two years.
Games and Social Networking Rule
Flurry tracks the total number of application use sessions, from when consumers start app sessions to when they end them, and groups these sessions into categories such as games, news and travel. The top categories ranked by session usage worldwide are: Games, Social Networking, Sports & Entertainment and News.
The graph below shows how consumer usage varies by app category across the top five European markets.
With the exception of Italy, the games category is the most popular app category across all countries. In Italy, the one country where the games category does not lead, Social Networking is the top category, with 38% of Italians using Social Networking apps compared to other categories.
Comparing each country’s proportion of usage by category, more consumers play games in France than compared to other countries – a massive 45% of all French app sessions are Games. In Spain, a greater percentage of the Spanish population consumes news compared to other countries, and the UK leads in relative Sports & Entertainment app consumption. In all 5 countries, the 4 top categories make up 80% of all traffic.
Solid App Retention and Engagement
In May 2011, the average worldwide 6-month retention rate for all apps was 36%. In other words, of all consumers who downloaded an app over the last six months ago, 36% had used that same app within the last 7 days of May (Flurry looks at “last 7 days” for its retention metric).
Continuing to look at the top 5 European countries, all have posted 6-month retention rates of greater than 30%. The chart below breaks out each countries 6-month retention rate compared to the worldwide average.
Reviewing the chart, we note that the UK leads in retention with 38%, followed by France at 37%, Germany at 34% and then Spain and Italy at 32% and 31.5%, respectively. Generally, we see a correlation between the maturity of a given market and app retention. We observe that consumers typically try several apps before they settle into using a group of favorites, which they then use several times per week, even per day. In less developed countries, we often see much more app experimentation. The five countries we review for this report are clearly all highly developed economies.
As a mass market media channel, smartphone apps not only reach a sizable audience today, but also continue to grow at staggering rates. The channel is already formidable with no signs of slowing. Smartphone app consumers are highly engaged and consider their smartphone among their most important personal possessions; we believe the 8th mass market media channel has indeed arrived in Europe.