In May of 2013, KPCB’s Partner and world-renowned analyst Mary Meeker shared her latest Internet Trends Report. In that report, Ms. Meeker shared an interesting stat: “The average mobile consumer checks their device 150 times a day”. That number raised a few eyebrows and led many analysts to question the difference between existing smartphones and highly anticipated “Wearables”. In this report, we have used data from Flurry Analytics to analyze the behavior of consumers that heavily use their smartphones or tablets, a segment we refer to as the “Mobile Addict”.
We have defined a “Mobile Addict” as a consumer that launches apps more than 60 times per day. Looking at data Flurry sees from 500,000 apps across 1.3B devices as of March 2014, we know that on average, a consumer launches apps 10 times per day. So we have defined a “Mobile Addict” as someone who launches apps 6 times more per day than the average.
Mobile Addicts Are Multiplying
The chart below shows the year-over-year growth in usage, across all segments of mobile app users. The Mobile Addict segment is growing the fastest, posting 123% growth between 2013 and 2014. In March of 2014, there were 176 million Mobile Addicts, up from 79 million in March of 2013. That is astonishing growth in a single year. This compares to 55% growth for a category we’re calling Super Users and 23% for Regular Users, who launch apps 16 times or less per day.
Most Addicted? Teens, College Students and Middle-Age Parents
We dug deeper into the Mobile Addicts segment to better understand that audience. Mobile Addicts were 52% female and 48% male, compared to 48% female and 52% male for an average mobile users. That means females over-index 8% compared to the average mobile user. The 8% number appears small, but it is significant: In the total Mobile Addict population of 176 million, it means that there are 15 million more female Mobile Addicts than male Mobile Addicts.
Now looking at age, the Mobile Addict segment over indexed on the 13-17 (Teens), 18-24 (College Students) and 35-54 (Middle Aged) age segments. In fact, Middle Aged consumers constituted 28% of Mobile Addicts, but only constituted 20% of the average mobile consumer. The Addict segment under indexed on 25-34 (adults) and 55+ (seniors).
The analysis gets even more interesting when you dive into the differences among Flurry Personas. On the female side, the following Personas over-indexed as Mobile Addicts: Moms, Parenting & Education, Gamers and Sports Fans, in that order. For Males, the following Personas over-indexed as Mobile Addicts: Auto Enthusiasts, Parenting and Education, Gamers and Catalogue Shoppers.
The “Over-Index” is shown in the chart below. It refers to the division of the percentage reach of that Persona in the Mobile Addict segment compared to the percentage reach of that Persona for the average mobile consumer. For example, in the male Mobile Addict segment, Auto Enthusiasts are 26% of the total, while for the average male mobile consumer Auto Enthusiasts are just 3% of total. In other words, male Mobile Addicts are much more likely to be Auto Enthusiasts than non-Addicts.
Looking at the three charts above, we are starting to form a relatively clear picture of a Mobile Addict. Teens, College Students (skewing females) and Middle Age Parents. We were not surprised by teens being part of the group. Their youth coincided with the mobile revolution – they are not just accustomed to mobile, they expect their mobile device to handle nearly every type of task and communication. The same is true for college students who are noticeably avid users of messaging and gaming apps. We were also comfortable with young adults under-indexing. They have just entered the workforce, are predominantly single and are likely out and about more often than older and younger segments.
What surprised us most was the over-indexing of the middle-age segment and by a margin that beats that of teens. But when we inspected the Personas of that segment and their app usage, we came to the conclusion that these middle-aged consumers are probably part of a family and their devices are likely shared among multiple family members, including their children. Males and females in the Middle Age segment both over-indexed on parenting and education. Males over indexed as Catalogue Shoppers and females over indexed on Sports. The picture we formed is a family of four, with two phones, one tablet, and all three devices shared by the family for education, entertainment and more utilitarian functions as well.
A Sneak-Peek into the Wearable Early-Adopter
Mobile Addicts launch apps over 60 times per day, making them consumers that are effectively wearing their devices. This analysis of the Mobile Addict should give us a sneak preview into the make-up of early-adopters of Wearables, and what types of apps and experiences will resonate with them. To date, many applications for Wearables have focused on fitness and health, but thinking about what’s next, developers should think about the other experiences that will delight the people who need to be connected all the time. This includes Teens, College Students and Middle-Aged parents who are interested gaming, autos, sports and shopping, and who may have a constant need to entertain or educate their children. After all, the people who we consider “Mobile Addicts” are already essentially wearing their devices 24/7/365.
According to the U.S. Census Bureau, more than 12% of people in the U.S. speak Spanish at home, and nearly fifty million Americans are of Hispanic origin. The collective purchasing power of Hispanics is expected to reach 1.5 trillion dollars by 2015. Brands are clearly aware of the importance of this demographic group, and there are advertising agencies dedicated toward helping brands communicate with Hispanic consumers. Nonetheless results of some recent research suggest that brands are not doing enough to create positive app experiences for Spanish speaking consumers in spite of the fact that Hispanics in general are enthusiastic users of smartphones.
Last week’s Advertising Research Foundation forum on the intersection between mobile and culture inspired us to investigate what the overall U.S. appscape looks like from the perspective of Spanish-speaking device users. Flurry is able to do that because we can detect what language a user’s device is set to each time they start an app session, and we record data from over a billion app sessions each day in the U.S.
Defining Spanish Interest Apps
We started by defining Spanish Interest apps as those for which there is at least one U.S.-based user with their device’s language set to Spanish for every twenty set to English. We used this as an indication that a non-trivial proportion of the app’s users speak Spanish, indicating some level of interest in the app among Spanish speakers. As shown below, 15% of apps with fifty or more daily users in the U.S. were in this category.
Android Speaks Spanish
The overall percentage of Spanish Interest apps is in line with what you might expect given the prevalence of Spanish speakers in the U.S., but what’s surprising is how those apps are distributed across mobile operating systems. As shown below, nearly half of Android apps are Spanish Interest apps compared to less than 5% of iOS apps. In other words, 47% of Android apps have one or more user with their device set to Spanish for every twenty who have it set to English. That is only true of 4% of iOS apps.
It’s important to note that this may not be so much a reflection of app availability as it is a reflection of device ownership patterns since the apps a user can run are determined by their device’s operating system.
Spanish Speaking Android Users Love Games Even More Than Everyone Else Does
The apps that have the greatest number of U.S. users with devices set to Spanish as compared to English are mainly Spanish language apps (some originating from the U.S. and some from countries for which Spanish is the dominant language). Other than that, Spanish Interest apps span the full range of app categories but are disproportionately likely to be in the Game, Live Wallpaper, Personalization, and Photography categories in Google Play. As shown below, Spanish Interest apps are also over-represented in some iOS categories, but because the base rate on iOS is so low (4%) the absolute percentage of Spanish Interest apps is still relatively low even in categories in which they are over-represented.
Fans Of Pets, Sports, And Bargains
By definition, the audience for Spanish Interest apps includes Spanish speakers, but we wanted to find out what else we could learn about the audience for those apps. We did that by identifying which Flurry Personas (psychographic segments) are over- and under-represented in Spanish Interest apps. We found that Pet Owners, Sports Fans, and Value Shoppers are among the over-represented Personas and Auto Enthusiasts, Home and Garden Pros, and Real Estate Followers are among the under-represented. A more complete list is provided below.
Brands Don’t Speak Android
Many brands have taken a while to embrace mobile at all, and to the extent that they have they have tended to start with iOS. Some haven’t ventured any further. In some cases that is due to concerns about fragmentation or for brand safety in the more open Android ecosystem, but it is also due to the demographics of the user bases for iOS and Android. A considerable body of evidence suggests that, on average, iOS users are more affluent than Android users and they tend to spend more money in a variety of product categories.
Combine that with the tendency of Spanish Speakers to use Android devices, and it’s easy to understand why few brands have created Spanish language apps. The fact that some of the Personas most coveted by advertisers are under-represented in the apps in which Spanish speakers are most over-represented reinforces this point.
Given the size of the Spanish speaking population, the shift of consumer attention toward mobile, and the advertising budgets following them, this situation needs to change. Our results show that if marketers want to reach Spanish speakers on mobile they are going to need to do so using Android. That creates an opportunity – or really a necessity -- for Hispanic-focused advertising agencies to lead in creating high-quality brand promotion on Android. While Android users in the U.S. may be less affluent than iOS users, collectively they still have massive purchasing power, and world-wide, Android is even more dominant than it is in the U.S. Given the size of the Android audience world-wide, teaching brands to speak Android could pay big dividends well beyond those that can be generated from U.S. Spanish speakers.
Many of us at Flurry love Mad Men, but we believe that Don Draper’s advertising industry is ancient history. Don would probably mistake smartphones for cigarette cases and tablets for coasters. More importantly, sophisticated buyers and sellers in today’s advertising market are making decisions in real time based on masses of data rather than months in advance based on charm and corporate hospitality. Advertising buying is being disrupted by efficiency gains from real time bidding (RTB) and effectiveness improvements achieved by using big data to inform mobile advertising transactions.
Data-Driven RTB In The Mobile Space
Recently Flurry launched an RTB Marketplace that enables advertisers to bid for the attention of smartphone and tablet users one at a time. We are betting big on the trend toward programmatic buying for two reasons. First, it enables precision targeting that was unimaginable in the pre-digital age and is still uncommon. Buying ad exposures one at a time enables advertisers to reach precisely-defined audiences wherever they are and whenever they use their devices. That level of precision would always have been useful, but it is especially important now that consumer interests, preferences, and lifestyles have become so varied.
Second, RTB brings a new level of efficiency to ad buying. The whole nature of an auction means that an advertiser who is willing to pay the most to reach a certain type of person will earn the opportunity to do so. The price advertisers are willing to pay provides a clear signal of the relative value they place on a customer or potential customer.
In this post we share initial results from our Marketplace to illustrate the power of combining the price signals provided through RTB auctions with the individualized targeting capabilities made possible by big data.
Building A Mobile Audience One Person(a) At A Time
The chart below illustrates three important results related to the value advertisers place on different types of mobile users and the available supply of those people’s in-app attention. The items being plotted are Flurry Personas. These are groups of devices whose owners access particular types of apps more frequently than people using other devices do.
The size of the bubble associated with each Persona represents supply, or the relative number of auctions for the right to serve an impression to a device in the Persona. Of the Personas shown here the greatest number of available impressions were for Casual and Social Gamers and the least were for Fashionistas and Food and Dining enthusiasts.
The x-axis, clearance rate, shows the percentage of auctions that had a winning bid, resulting in an advertiser displaying an ad on a device. As can be seen by looking at the right bound of the x-axis, less than half of the auctions had a winning bidder. This is a normal and expected result in RTB auctions. Reasons for auctions not clearing include price floors being set too high, bidding technologies used by advertisers’ representatives responding too slowly, some publishers being able to sell their ad inventory for higher prices elsewhere, and advertisers being uninterested in the inventory some publishers offer.
The y-axis shows the average effective cost per thousand impressions (eCPM). Even though these impressions are sold on an individual basis that is still the common pricing metric.
Fashionistas And Foodies Command A Premium, But Hipsters And Music Lovers Are Cheap
Examining supply, price, and clearance rate together reveals a lot about the state of play in the mobile advertising market. First, the fact that Fashionistas and Food and Dining Lovers are in the upper right corner implies that those Personas are of greatest interest to advertisers. It seems logical that those would be desirable psychographics, but the limited supply of ad inventory for those Personas also helps explain why prices and clearance rates are high. It means there are opportunities to generate mobile advertising revenue by publishing apps and content that attract Fashionistas and Food and Dining Lovers.
At the other extreme, Music Lovers and Hipsters have relatively low clearance rates and relatively low average eCPMs. While the supply of impressions for these groups within our Marketplace is not particularly large (as shown by the medium-sized bubbles), we hypothesize that people in these Personas are fairly easy to reach outside of our Marketplace because music fans spend a lot of time in music apps and many apps attract mobile-savvy Hipsters. It also makes sense that advertisers compete less aggressively for Music Lovers considering how inexpensive music is now compared to the pre-Napster era.
The overall diagonal pattern formed by the personas shows that the market is working efficiently, as expected. How do we know that? If a Persona had a high clearance rate but a low average eCPM we would expect advertisers to bid up the price to secure inventory. The fact that there are no Personas in the lower right corner shows that is exactly what has happened.
A position in the upper left corner of the chart means that auctions to advertise to that Persona have a high average eCPM given their rate of clearance. Here, we would expect publishers to drop their floor prices to achieve higher clearance rates. The fact that there are no Personas in the extreme upper left corner suggests that is also happening. There are some Personas with positions approaching that upper left corner: News and Magazine Readers are the most extreme example. We see two possible explanations for why those publishers didn’t drop their floors in search of higher clearance rates. One is that some of those publishers are able to sell impressions that don’t sell through our Marketplace direct or to use them themselves (i.e., to promote their own properties). The other is a policy of keeping prices above a certain level to maintain a premium image even if it means sacrificing short-term revenue opportunities.
Power Lunches Are Losing Out To The Power Of Data
RTB moves at lightning speed. A publisher can shop a single impression in the nanosecond before the winning ad appears. Compare that to the speculative, mass-market approach of the Upfronts, and it’s easy to see that advertising buying is likely to be completely disrupted by RTB.
The Persona-based targeting described in this post demonstrates the power of data to inform each bid. Advertisers no longer need to make buying decisions based on stereotypes about which types of people are interested in what type of products or content. They can define their target audience precisely, and aggregate that exact audience efficiently impression by impression. Mobile also contributes to this type of precision targeting since smartphones are highly personal devices loaded with apps that reveal much more about the person looking at the screen than standard demographics ever did. The long held promise of digital advertising is finally being realized on mobile.
All of this leads us to believe that advertisers or publishers who want to do things in the old way may be better off kicking back, pouring themselves a drink, and watching an episode of Mad Men instead of entering the fray in the mobile advertising space where data-fueled RTB is sure to win.
Android has been a hot topic lately, with some arguing that it may become a unilateral smartphone superpower and others arguing that it has already peaked in the US market. A lot of this conversation seems to assume that Android’s (and by extension, Google’s) gain is Apple’s loss and vice-versa. We believe that the situation is more complex than that.
Two facts about Android are now well established: 1) Android smartphones now dominate many markets in terms of device shipments, but 2) The market for Android devices is famously fragmented. What’s less well-established is how and when all of those Android devices are being used and the implications of that for participants in the Android ecosystem and beyond. Those are the topics that we tackle in this post with a particular focus on Samsung devices and how their owners compare to users of other Android devices.
Smartphones Dominate On Android
This posts builds on a previous one we did exploring how people use iOS smartphones and tablets. As we will show, there are many similarities in usage patterns across the two operating systems, but one big difference is the overall breakdown between smartphones and tablets. In this May sample of 45,340 Android devices (of the 576 million Flurry measures), 88% were phones and 12% were tablets. The share of devices represented by smartphones is significantly greater than in our iOS sample, in which 72% of devices were phones. The emphasis on phones over tablets was even greater among Samsung devices in our sample: 91% were smartphones and 9% were tablets.
As in our previous post, we started our analysis by considering how the smartphone versus tablet distribution varies by psychographic segment. These are Personas, developed by Flurry, in which device users are assigned to segments based on their app usage. An individual person may be in more than one Persona because they over-index on a variety of types of apps. Those who own more than one device may not be assigned to the same Personas on all of their devices because their app usage patterns may not be the same across devices.
The Personas shown above the “Everyone” bar in the graph below skew more toward phones than the general population of Android device owners, while the Personas shown below the “Everyone” bar skew more toward tablets. (Android device ownership patterns for Personas not shown are not statistically different from those shown for “Everyone.”) In general, these follow a similar pattern to the one we saw for iOS. On-the-move type Personas, including Avid Runners, skew toward phones and more home-bound personas, such as Pet Owners, skew more toward tablets.
Within that broader pattern, there were differences based on the particular Android smartphone or tablet that a person owns. Samsung is the dominant manufacturer of Android devices. Its phones represented 59% of the phones in our overall sample of Android phones, and its tablets represented 42% of the tablets in our sample. Both its products and its promotion suggest that Samsung attempts to differentiate itself from other devices that share the Android operating system, and those differences were reflected in persona memberships.
Samsung Is Building A Unique and Attractive Audience
Owners of Samsung devices were disproportionately likely to be in many personas, including some of those most sought-after by advertisers (e.g., Business Travelers and Moms). Since Persona memberships are based on over-indexing for time spent in particular types of apps, this suggests that Samsung device owners are generally more enthusiastic app users than owners of other brands of Android smartphones and tablets.
Overall, owners of Android tablets spent 64% more time using apps than owners of Android smartphones. This ratio varied by category, as shown in the chart below. For example, owners of Android smartphones spent more than five times as much time, on average, in Business apps as owners of Android tablets. Sports and Photography were other categories that heavily favored phones. As with iOS, Education and Games skewed more toward tablets. (Average time spent using app categories not shown does not differ in a statistically significant way between Android smartphones and tablets.)
Once again there was variation by manufacturer. Overall, owners of Samsung phones spent 14% more time using apps than owners of other Android phones and owners of Samsung tablets spent 10% more time using apps than owners of other Android tablets. The particular categories of apps where time spent was greater for Samsung phones were News Magazines, Tools, Health and Fitness, Photography, and Education. Owners of Samsung tablets spent more time than owners of other Android tablets in Communication (e.g., voice over IP and texting) apps.
Android app use peaks between 8 and 11 pm. Comparing the two types of Android devices, a greater share of tablet use takes place from 3pm until 11 pm and a greater share of phone use takes place from 11 am to 3 pm and overnight. While the overall amount of time spent on Samsung devices is greater than for other Android smartphones and tablets, the overall time distribution throughout the day is similar.
Can Samsung Compete At Both Ends Of The Market?
As this and our previous post have shown, while smartphones capture more time in specific app categories, such as Navigation and Photography, those tend to be categories of apps used in short bursts. Tablets are favored for longer-duration app categories, such as Games and Education, and so, on average, tablet users spend more total time using apps than smartphone users. That makes tablets particularly interesting to content creators and to advertisers.
Samsung is the dominant manufacturer of Android devices. As shown in this post, it is attracting a unique audience relative to other Android devices. Owners of Samsung devices spend more time in apps than owners of other Android devices, and they are also disproportionately likely to be members of psychographic segments (Personas) that are attractive to advertisers. In those respects, they are more similar to owners of iOS devices than owners of other Android devices are.
But compared to iOS, a smaller share of Android devices are tablets, and that percentage is even smaller for Samsung devices than for Android as a whole. So the question is: will Samsung make as big of an impact in the tablet market as it has in the smartphone market?
In some ways, this comes down to a question of how it will balance its resources between two different types of markets: relatively more affluent countries that were early adopters of connected devices so new growth is now coming mainly from tablet adoption versus less affluent countries where smartphone penetration is still relatively low, but growing quickly.
A focus on tablets could enable Samsung to better develop more of a true ecosystem of its own (especially considering that they can include connected TVs as part of that) and the higher profits that go with that. Riding the wave of global smartphone growth is more of a high volume / low margin strategy. Of course, they could try to compete at both ends of the market, but each individually may require a lot of resources because of Apple’s (and to a lesser extent, Amazon’s) strength in the tablet market and the number of hungry competitors anxious to grow along with the Android smartphone market. If they can do both, they will rule the Android Kingdom, and Samsung, rather than Google, will pose the greater threat to Apple.
Apps are telling – they signal our personal tastes and interests. There are probably nearly as many unique combinations of apps as there are devices, and the apps we use reveal a lot about us. Based on Personas that Flurry has developed for its advertising clients, we are beginning a series of blog posts to shed light on different groups of smartphone and tablet users and their app usage patterns. Moms -- who often control household budgets and expenditures -- are considered the prime audience for many brands. So we thought, where better to start our Personas series than by examining what moms are doing with apps?
Our analysis for this post relies on iPhone, iPad, and Android app usage during May of this year for a large sample (24,985) of American-owned smartphones and tablets. Discussion of app usage is based on time those devices spent in the 300,000+ apps that use Flurry Analytics.
What Apps Do Moms Use?
Moms, like most other groups, spend a lot of smartphone and tablet time playing games. In fact, on Android, more than half of the time American Moms spent in apps was spent playing games. Similarly, on iPad moms spent about half their time in games, but on iPhone, that percentage drops to a little less than a third of their time. On iPhone, lifestyle apps capture a larger proportion of Moms' attention (12%) than on iPad and Android devices.
As shown below, the second most popular category among moms on iPhone and Android devices is social networking. On iPad, newsstand (24%) was the second most popular category, demonstrating its strength as a screen for displaying magazine type content.
Where Do Moms Over-Index?
Most mobile consumers spend a large proportion of their app time in gaming and social networking apps, so what makes moms different from the other American owners of smartphones and tablets? Across iPhone, iPad, and Android, American Moms spend more time in education apps than the general population. Also, moms who own an iPhone or an Android device spend a greater share of their app time in health and fitness apps. Unsurprisingly, moms are also heavy shoppers. Android moms over-index for time spent in shopping apps, and iPhone moms over-index for time spent in catalog and lifestyle apps. (For this post, we have honored The App Store and Google Play’s systems for classifying apps. In iOS, shopping apps can fall into either the catalog or lifestyle category, whereas Android has a dedicated “shopping” category.)
Moms Own More Tablets And Gravitate Toward iOS
Compared to other American device owners, moms are enthusiastic users of tablets. As shown below, among the general population 25% of connected mobile devices were tablets, but for moms that percentage is 35%. This could be driven by the fact that many parents use tablets for sharing games and stories with their children.
60% of the smartphones and tablets we looked at were iOS devices. (Note that this number is a function of the installed base of active devices, so does not reflect market shares from sales in recent quarters.) For American Moms, the numbers lean even further toward iOS devices. A whopping 77% of moms own iOS devices while just 23% own Android. There are at least two factors that may explain this. First, it could be a function of Moms’ greater tablet ownership since iPad dominates the tablet market. Second, surveys show that women in general skew toward iOS devices. The key takeaway is that moms are much more likely to be found using iOS devices than Android devices.
For Moms, Connected Devices Are More For Escape Than Utility
So what can we infer about American Moms based on their app usage? For one thing, it appears that they use smartphones and tablets as a refuge from their busy lives. On average, half or more of the time they spend in apps is spent on social networking and game apps. In this sense, they are not that different from other Americans, but it does show that even busy moms need to escape and socialize, and mobile devices provide a way to do that.
Apps where American Moms spend a disproportionate share of time relative to other Americans also tell us something about their more serious side. Those apps tend to be improvement-oriented: education and health and fitness, for example. Moms are using their devices to help them achieve personal goals and possibly to educate their children.
We hope this post gives brands and developers a better idea of where the coveted American Mom is most likely to be during mobile time, and what is capturing their attention. App developers can tap into this valuable group by building experiences that give moms an escape from their hectic day-to-day routine, keep them socially connected, and help them improve different aspects of their lives. Media planners who want to reach American Moms should continue to buy ad inventory in gaming, news / magazine, and social networking apps, and to weight their budgets toward iOS apps.
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!