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.
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.
On October 5, 2009, CBS canceled "Guiding Light," the longest running television drama in history, which began in 1952. Last month, CBS aired the last episode of "As the World Turns," the Proctor & Gamble production that has been running for more than 50 years. Ad dollars allocated to soaps fell nearly 30 percent from 2005 to 2009, and then fell another 20 percent in the first half of 2010.
Since the 90s, the television industry has been reeling from the disruptive forces of the Internet and DVRs. No longer could the industry depend on a captive audience to which it had grown so accustomed. While the industry has adapted its programming with a glut of cheaper, but profitable competition reality shows and edgier dramas to reclaim a loyal audience, a new entertainment force is once again driving disruption: the iPhone. The chart below illustrates how iOS social games, a popular form of gaming mixed with social networking, stack up against primetime TV viewership.
Social games on iPhone, iPad and iPod touch devices are competing for television viewers. In fact, these apps, tracked on the Flurry network alone, comprise of a daily audience of more than 19 million who spend over 22 minutes per day using these apps. Treated as a consumer audience, its size and reach rank somewhere between NBC’s Sunday Night Football and ABC’s Dancing with the Stars, and only 4 million viewers shy from beating the number one prime-time show on television, FOX’s American Idol.
However, Flurry is only seeing part of the picture. With Flurry integrated into more than 50,000 apps, out of Apple’s stated total of 250,000 apps, Flurry has about 20% penetration. Additionally, since this analysis focuses on only two categories of applications, social games and social networking apps, it’s clear that iOS devices are already ahead of prime time television’s hottest shows.
Given that the app store only launched in July 2008, these figures are staggering. Mass consumption of applications on mobile devices has exploded in record time. Also noteworthy is that the enormous audience these applications reach takes place every day, 365 days a year. Compared to a top television series, which airs 22 episodes a season, advertisers can reach a larger consumer audience through applications 15 times more frequently.
There are a lot of conclusions that can be drawn from this phenomenal shift in audience behavior. The most obvious is the impact on the advertisement industry, which has relied on the reach generated by its prime time television slot for years. This season, while Americon Idol is busy shuffling judges, the people have voted: iOS social games are as prime time as prime time television. Enjoy the show!