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.
Many consumer surveys point to an obvious conclusion: most people hate seeing ads on smartphones and tablets. But the truth is, contrary to the desire for an ad-free experience, when faced with the choice between free apps with ads, or paying even $.99 for apps without ads, consumers overwhelmingly choose the free apps and tolerate the ads.
In this post we explore that revealed preference for free content over content free of ads by examining four years worth of pricing information for the nearly 350,000 apps that use Flurry Analytics.
Our Apps Tell A Story
Each time we download an app, we reveal a little bit about ourselves. A glance at the apps on your phone can indicate whether you are a fan of sports, gaming, or public radio, and whether you love to hike or cook or travel. But our choices of apps also reveal our individual tolerance for advertising, and how we feel about the trade-off between paying for content directly, or paying indirectly by (implicitly) agreeing to view ads.
In many cases, apps are available in two forms: free (with ads) and paid (no ads). If you truly can’t stand to see ads in apps, you can usually pay $.99 or $1.99 to eliminate the ads and possibly get some additional functionality too. Even when a specific app does not come in paid and free versions, there are often other apps to choose from, free and paid, that perform very similar tasks like calling a taxi or looking up recipes.
So what are consumers choosing? Let’s start by considering iOS apps since they have been available for longer than Android apps. Note that all of our measurements in this post are weighted by user numbers so the apps with more users contribute more to the total trend.
People Want Content To Be Free
The chart below shows how the proportion of free versus paid apps has changed over the years in the App Store. Between 2010 and 2012 the percentage of apps using Flurry Analytics that were free varied between 80% and 84%, but by 2013, 90% of apps in use were free.
Some might argue that this supports the idea that “content wants to be free”. We don’t see it quite that way. Instead, we simply see this as the outcome of consumer choice: people want free content more than they want to avoid ads or to have the absolute highest quality content possible. This is a collective choice that could have played out differently and could still in particular contexts (e.g., enterprise apps or highly specialized apps such as those tracking medical or financial information).
Android Users Are Even Less Willing to Pay For Apps
Up until now, we have focused on iOS apps because they have been around longer, but what about Android? Conventional wisdom (backed by a variety of non-Flurry surveys) is that Android users tend to be less affluent and less willing to pay for things than iOS users. Does the app pricing data support that theory? Resoundingly.
As of April 2013, the average price paid for Android apps (including those where the price was free) was significantly less than for iPhone and iPad apps as shown below. This suggests that Android owners want app content to be free even more than iOS device users, implying that Android users are more tolerant of in-app advertising to subsidize the cost of developing apps.
These results also support another belief derived from surveys and some transaction data: iPad users tend to be bigger spenders than owners of other devices, including iPhone. On average, the price of iPad apps in use in April of this year was more than 2.5 times that of iPhone apps and more than 8 times that of Android apps. This is likely to be at least partly attributable to the fact that on average iPad owners have higher incomes than owners of other devices.
Developers’ Pricing Decisions Were Data-Driven
On the surface, the rise of free apps could be seen as herding behavior: maybe app developers saw how much free competition there was and decided to make their apps free too. It’s certainly possible that may have happened in some instances, but by digging deeper into app pricing patterns over time, we were able to see that many developers took a much more thoughtful approach to pricing.
We looked at historical iOS app data (again because iOS apps have a longer history) to identify apps that have been the subjects of pricing experiments. That typically took the form of A/B testing, where an app was one price for a period of time then the price was raised or lowered for a period of time, then raised or lowered again. This lets developers assess users’ willingness to pay (i.e., price elasticity of demand) based on the number of downloads at different price points.
The chart below shows the percentage of tested and untested apps that were free (again, weighted by user numbers). The vast majority of untested apps in green were free all along, so it’s most interesting to look at the trend among apps that were subject to pricing experiments, in blue. As shown, there was an upward trend in the proportion of price-tested apps that went from paid to free. This implies that many of the developers who ran pricing experiments concluded that charging even $.99 significantly reduced demand for their apps.
The People Have Spoken; It’s Time To Change The Conversation.
While consumers may not like in-app advertising, their behavior makes it clear that they are willing to accept it in exchange for free content, just as we have in radio, TV and online for decades. In light of that, it seems that the conversation about whether apps should have ads is largely over. Developers of some specialized apps may be able to monetize through paid downloads, and game apps sometimes generate significant revenue through in-app purchases, but since consumers are unwilling to pay for most apps, and most app developers need to make money somehow, it seems clear that ads in apps are a sure thing for the foreseeable future. Given that, we believe it’s time to shift the conversation away from whether there should be ads in apps at all, and instead determine how to make ads in apps as interesting and relevant as possible for consumers, and as efficient and effective as possible for advertisers and developers.
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.
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.
The Super Bowl is one of the world’s top media events. This year’s contest, Super Bowl XLVII, was hosted in New Orleans and drew an average of 108.4 million viewers, the third largest audience in U.S. television history. According to Nielsen, previous Super Bowls captured the top two U.S. TV audiences, with last year’s event drawing 111.3 million viewers and the previous year’s attracting 110.0 million.
While the contest on the field pitted the San Francisco 49ers against the Baltimore Ravens, an equally fierce battle for consumer engagement was waged across multiple screens. As the world’s top brands paid up to $4 million to air 30 second television spots, consumers were more distracted than ever, accessing mobile apps and social media in droves. Twitter reported 24.1 million Super Bowl-related tweets, the most popular of which focused on Beyoncé, Destiny’s Child, the Superdome power outage and key game moments. Facebook reported similar increases in conversations around these topics.
Mobile Apps Make TV the Second Screen
In this report, Flurry finds that mobile appears to have become the first screen. The implication is that, from this day forward, as marketers advertise on television, they must ensure that the content is sufficiently compelling to pull the consumer away from her smartphone or tablet. While TV may continue to be widely regarded as the first screen, Flurry believes that brands need to reverse that logic in order to reach and engage their consumers.
For this study, Flurry measured U.S. app session starts, per second, over the course of this year’s Super Bowl, last year’s Super Bowl, and the equivalent time period on the Sunday before this year’s Super Bowl (to establish a baseline for an average Sunday) from 3 PM PST to 8 PM PST. Flurry Analytics is used by 275,000 apps, including many of the most-used apps, with aggregate daily usage sessions of 2.4 billion.
For this analysis, we estimated U.S. app session starts occurring on Super Bowl Sunday by sampling from our own data and extrapolating based on the proportion of the market that Flurry "sees." To be able to compare across last year's to this year's Super Bowl, we created an index where “100” represents a baseline for app usage. Let’s start by looking at how this year’s Super Bowl app activity compared to that of last year’s.
The chart above shows this year’s Super Bowl in blue compared to last year’s Super Bowl in grey. The spark lines show application session starts in the U.S. sampled from Flurry’s system, per second. The way to interpret the chart is that if the line is moving up, consumers are picking up their phones (or tablets). And if the line is moving down, consumers are putting down their phones (or tablets). In other words, when something on the TV cannot sufficiently hold the consumer’s attention, she often reaches for her connected device. The advantage for using mobile app usage as a signal is that we can accurately measure when consumers are interacting with the mobile apps. In this way, we can distinguish between active (consumer is using the "app") and passive use (app is just "on"). Using mobile app usage as a signal, the events to which consumers paid the most attention were the National Anthems, Halftime shows and close finishes.
A few structural differences to the length, shape and height of the curves are worth noting. First, last year’s Super Bowl was faster up through the first half, as we see that Madonna’s half time show started earlier compared to Beyoncé’s. Additionally, this year’s Super Bowl was further extended due to the 34-minute power outage in the Superdome just after the beginning of the 3rd quarter. Relative to last year’s Super Bowl, consumers began picking up their phones and tablets en masse during this period. Next, this year’s Super Bowl curve (blue) sits higher than last year’s curve (grey), which indicates that there was more relative app usage in the U.S. this year versus last year. Specifically, we measure a 19% increase in app usage between last year’s Super Bowl versus this year’s.
The chart above plots app usage during this year’s Super Bowl against the same time period from the Sunday before. This gives us a sense for how much application usage varies on a normal Sunday compared to Super Bowl Sunday. Overall, total app usage dropped in aggregate by only 5% from the Sunday before to Super Bowl Sunday, which suggests that the Super Bowl largely failed to curb consumer app usage when compared to normal behavior. The height and the shapes of the curves are very similar. More notable differences did appear from just before the Super Bowl started up until about half way into the second quarter of the game, where consumers appeared to be paying more attention to the Super Bowl (i.e., the blue line was modestly below the grey line for that period). We also note a spike in app usage during the Jeep halftime report during the sports analyst commentary, followed by a plummet in activity during Beyoncé’s performance. Next, during the outage, consumers began using their apps. After gameplay resumed, app usage was very similar to a normal Sunday except for the last minutes of this year’s close Super Bowl finish, as the 49ers mounted an exciting, narrowly-missed comeback.
Next we studied how app usage varied during different times during the Super Bowl: while the game was on, when ads were broadcasted, during halftime and during the power outage. We used app activity during the game as a baseline.
The overall finding was that app usage did not vary greatly between commercials and game play, with only a slight increase in app session starts during ads in this Super Bowl, and an even smaller decline in session starts during the last Super Bowl. In contrast, session starts dropped by nearly ten percent during this year’s halftime. That suggests that while Beyoncé was compelling enough to cause viewers to put down their phones, much of the game and many of the ads were not. The large increase in app session starts during the power outage provides additional evidence that TV cannot hold attention without compelling content. Consumers turned to their smaller screens in great numbers as soon as there was a lull in the action on TV.
Of course, there is variation within these averages. Groups particularly prone to starting app sessions during ads include: Photo & Video Enthusiasts, Real Estate followers, Small Business Owners, TV Lovers and Movie Lovers. For your convenience, you can find Flurry (psychographic) Personas listed here. Consumers less inclined to start app sessions during ads include iPad Users, Food Enthusiasts, Catalog Shoppers, Fashionistas and Home & Garden Enthusiasts. Those most inclined to take a break from their apps and watch the halftime show included Home & Garden Pros, Health & Fitness Enthusiasts, Fashionistas, Catalog Shoppers and Food Enthusiasts. Groups whose app use climbed most during the power outage – suggesting that they were paying closest attention to the game at other times – were Males, Seniors and Sports Fans.
Mobile Is Killing The TV Star
Ratings from Nielsen confirm that people continue to sit in front of TVs on Super Bowl Sunday. However, the fact that overall app usage declined by less than just 5% compared to same time period on the prior Sunday suggests that a large amount of consumers’ attention is spent in apps, even as they sit in front of the TV. This should cause advertisers to question the value of paying a premium for Super Bowl ads when the attention premium they command is eroding. That’s particularly true for some groups. For example, overall app usage by Moms, during the time the Super Bowl was on, dropped by less than two percent compared to the previous week. While Tide’s “Miracle Stain” ad was certainly entertaining, it appears that the “Mom” target market was not paying attention.
The price of a Super Bowl ad pays for a lot on mobile whether that’s in app advertising, sponsored content, in-app product placement or branded apps, and Flurry believes many marketers may benefit from reconsidering their media mixes in light of evidence in this report showing that unless exceptionally interesting things are happening on TV, a significant and increasing amount of consumer attention is spent using smartphones and tablets.
New Consumer Behavior. New Strategy.
Brands who continue to believe in the potential of TV during major events such as the Super Bowl must also now understand the multi-screening behavior of their target market, and take that into account in developing their campaigns. For example, marketers targeting Fashionistas would be well-served by scheduling ads to run during or near the half-time show, while running in-app ads during the game itself. The reverse strategy would apply to groups such as Sports Enthusiasts. These results also have implications for those who wish to run integrated campaigns across screens: those will only be effective if the TV portion is compelling enough to pull attention away from the screens in the hands of the audience.
With the holy grail of TV events disrupted, advertisers need to take note. The winner of the Screen Bowl is the smartphone. Mobile is here. Mobile is the new first screen.
The app revolution has changed the way software is distributed and used among consumers. With a perfect storm of digital distribution, free content and powerful touch screen devices, the success of mobile apps has disrupted industries from telecommunications and games to music and news. To date, no category of apps has been more successful than Games, directly disrupting the traditional gaming industry. Flurry recently wrote about the impact iOS and Android game popularity has had on Sony and Nintendo. And with low barriers to entry for armies of entrepreneurial developers, indie game developers continue to thrive on iOS and Android.
Something Disruptive This Way Comes
Consider for a moment Facebook’s speedy billion-dollar acquisition of Instagram, a service that succeeds by delivering Facebook’s core value proposition of photo sharing, but only on mobile. When one understands that consumers now spend more time in mobile apps than they do online, Instagram’s value begins to make sense. With over 500 million iOS and Android devices in the market, mobile apps are the new battleground for consumer engagement. If Facebook feels compelled to snap up Instagram in this way, perhaps this is an indication of how relevant social networking has become in mobile apps, or simply how relevant mobile has become overall. In this report, Flurry focuses on the rise of the Social Networking category in mobile apps. Let’s start by looking at where consumers spend their time by application category.
In the chart above, Flurry compares the time consumers spend across different application categories when using smartphones. Starting on the left, we look at the average number of minutes a consumer spent each day, over the course of Q1 2011, across different app categories. For this period, we calculated that consumers spent 25 minutes (37%) of their app-using time in Games. They additionally spent 15 minutes (22%) of their time in Social Networking apps. News and Entertainment were the next most popular categories, garnering an average of 11 (16%) and 10 (15%) minutes per day, respectively. All other categories combined made up the final 7 minutes (10%) of time. During Q1 2011, Flurry tracked approximately 30 billion application sessions worldwide.
On the right, we conduct the same analysis for Q1 2012. Compared to the same quarter in 2011, time spent per consumer each day increased from 68 to 77 minutes. Additionally, the distribution of time spent per category shifted. Games usage dropped by 4% down to 24 minutes per day, while Social Networking increased by 60% up to 24 minutes per day. Games and Social Networking categories each controlled 31% of consumers’ time. News, Entertainment and Other categories commanded 12 (15%), 10 (13%) and 7 (9%) minutes, respectively. Flurry tracked approximately 110 billion application sessions during Q1 2012.
The most significant trend is that, for the first time in the history of applications (Flurry began tracking application usage in 2008), another app category is rivaling Games. We take the rise in Social Networking apps as a signal of maturation for the platform. As game demand may be hitting its saturation point, consumers are also discovering other apps, namely Social Networking. The year-over-year growth in Social Networking has been staggering. Not only has time spent increased by 60%, but also within a growing amount of total time spent in smartphone apps among consumers, from 68 to 77 minutes, or a growth rate of 13%.
Money Pools Where Audiences Aggregate
Through its mobile app traffic acquisition network, Flurry AppCircle, the company can also see how apps with growing audiences earn revenue through advertising. When app developers amass larger audiences, among the chief ways to monetize their businesses is by showing ads to their consumers. In the chart below, we show revenue earned by publishers in the Flurry AppCircle ad network for each of the last three months. Flurry AppCircle reaches over 300 million unique devices per month, making it one of the industry’s largest ad networks by reach. The columns in the chart grow from month-to-month at the same proportion as AppCircle publisher revenue growth. From just February to April of this year, Flurry AppCircle publisher revenue has grown by 23%. Please note that we forecast the remaining few days of April for the chart below.
From inspection, ad revenue in apps is driven primarily by Games and Social Networking categories. In other words, audiences using these apps a combination of the largest and most receptive to ads. For February, March and April, Games apps earned 35%, 35% and 36% of total ad revenue in the AppCircle network. Over the same three months, Social Networking climbed from 24% in February to 25% in March, and then to 37% in April. This is the first time in Flurry’s history that any category has surpassed Games in ad revenue generated (Flurry launched AppCircle summer 2010).
SoLoMo Not So Loco?
Over the last couple of years, the term “SoLoMo” was coined to describe the convergence of social experiences on mobile devices that leverage some element of proximity (i.e., location) to the experience. While a Silicon Valley term in origin, it speaks to the new consumer experiences possible when dreaming up any combination of these three factors. Phones are powerful, connected and always with consumers. And they are considered personal devices that easily enable sharing of personal content and information through apps. Build a clever app that leverages these aspects in a compelling way, and you could have the next Pinterest or Instagram.
As business ventures, the ability for Social Networking apps to engage consumers in a meaningful way is driving a wave of investment and bullish valuations. Social networks like Pinterest, Path and Skout are raising major venture capital rounds. This month, Andreessen Horowitz invested $22 million into Skout, and Greylock and Redpoint helped plow $30 million into Path. Pinterest, which has a strong mobile component, has become the third most popular social network behind Facebook and Twitter, and ahead of LinkedIn, Tagged and Google+. With so much innovation, coupled with high engagement among consumers, this appears to be only the beginning.
Games Don’t “Like” Social Networking Apps
The rise of Social Networking apps also signals the end of the era of gaming dominance within mobile apps. While the free-to-play business model performs extremely well, enabled by in-app-purchases, it does so primarily for simulation games, a sub-genre of the total games category. As long as the total iOS and Android installed base grows, all categories will continue to grow naturally. However, as we reach saturation for mobile gaming on a per user basis (one consumer can play only so many free-to-play games), the Games category could start behaving more like a “zero sum game” from here on out, meaning that game companies would have to fight over a finite group of consumers in order to grow their businesses. For one app to grow, it would have to take from its competitors. Even with an influx of new consumers into the market, the expected would-be casual gamers will be increasingly wooed away from games by compelling Social Networking and other apps. Going forward, the Games category will have to look to innovate on mobile to maintain its dominance and growth.
A Note about Methodology
For the comparison of minutes spent in this blog post, it’s important to clarify that these figures exclude tablet usage, and focus on smartphones only. While Flurry calculates that consumers spend an average of 94 minutes per day using mobile apps, that figure is a reflection of total usage spread over both smartphones and tablets. When we isolate just smartphone usage, as we’ve done in this analysis, the number of minutes spent on apps is lower.
Smartphones and tablets continue to break new consumer technology adoption records. From earlier research, Flurry found that iOS and Android smart devices have experienced twice the uptake rate compared to that of Internet adoption, and four times the rate compared to that of PC adoption. Following this unprecedented adoption, advertising dollars are beginning to flow into mobile. A recent IAB study reported that 63% of top brand marketers have increased their mobile advertising spending over the last two years, and that 72% plan to increase advertising spending over the next two years.
Focused on mobile advertising, this report has two parts. First, Flurry compares the allocation of advertising spending across various media versus the actual time consumers spend across those same media. Next, through detailed demographic breakdowns, we share which audience segments are best responding to mobile advertising. Let’s start by understanding trends in media usage versus ad budget allocation.
The Great Mobile Ad Spending Gap
In the above chart, Flurry aggregated publicly available data from VSS and Mary Meeker (KPCB), then layered in its own analysis to reflect the growth in app usage we observe. With our adjustment, we resized the totals for U.S. advertising spending by media and consumer time spent using each media. From left to right, represented by the green columns, is the proportion of advertising spending across each major media. TV and Print command the greatest advertising spends in the U.S. with 43% and 29% of the total, respectively. Web, Radio and Mobile channels round out the balance of media spending with 16%, 11% and 1%, respectively. Adjacent to the ad spending columns is the amount of time consumers spend by media type, represented by blue columns. TV leads consumption with 40%, followed by Mobile and the Web with 23% and 22%, respectively. Radio and Print complete the picture with 9% and 6% of usage, respectively.
Comparing where usage and spending vary most, one notes severe over-spending in print advertising and even more severe under-spending in mobile. Web usage also shows sizable under-investment, relative to platform usage, though not as dramatically as seen on mobile. In short, despite the fact that mobile advertising is growing, the platform is far from getting rational levels of spending compared to other media.
We believe the main reason for this disparity is that the mobile app platform has emerged so rapidly over such a short period of time. With the iOS and Android app economy only three-and-half years old, Madison Avenue and brands have yet to adjust to an unprecedented adoption of apps by consumers. Further, the mobile advertising ecosystem remains nascent, without sophisticated platform tools. Concepts of audience measurement and segmentation on mobile are still forming, and mobile lacks the kinds of systems that agencies take for granted on the web. For instance, mobile inventory is difficult to buy in volume, ad networks have yet to be integrated into Demand-Side Platforms (DSPs) and common standards for ad serving, tracking and settlement are yet to be defined. Just consider that large publisher properties like Facebook have yet to monetize their mobile properties, with many still needing to hire media sales organizations to position themselves to do so. As the mobile platform matures, and these problems are addressed, mobile advertising is poised to take off in earnest.
Mobile Advertising Audience Sweet Spot
For the second part of our analysis, we measure which audience segments respond best to mobile advertising, leveraging data from our own ad network, AppCircle, as well as publicly available data. Taking a sample of 60,000 daily active users on iOS, from among a total group of 6 million for whom we have demographic data, we calculated the effective cost per mille (“thousand” in Latin), or eCPM, earned by publishers. Using eCPM allows us to consider both branding (e.g., CPM) and performance (e.g., CPC and CPA) advertising campaigns in our calculations to get an accurate read on which mobile audiences monetize best. In the following charts, we display eCPMs by age and gender, household income and educational level attained. The higher the eCPM earned by audience attribute, the more valuable the audience is to both advertisers, who pay top dollar to reach this audience, and publishers, who earn the most revenue for selling access to this audience. Let’s start with audience breakdown by age and gender.
The chart above shows the value of mobile application segments by age and gender. Males are shown in green and females are shown in blue. The value above each respective column is the eCPM earned by that segment. For example, 25 – 34 year old females fetch the highest eCPMs at around $13, driven by underlying high click-through and conversions rates. In fact, females are the more desirable target audience across most age breaks, tied with men in the 18 – 24 year old age range, and exceeding them at 25 and older.
Breaking out eCPMs by household income shows that income ranges from $60,000 to $100,000 are the most valuable, with $100,000 to $150,000 also performing very well. For mobile advertising, there appears a strong correlation between affluence and eCPMs. This squares with earlier analysis from Flurry that found households with iOS and Android smartphones are, on average, 50% more affluent ($44,000 average U.S. household income vs. $66,000 average U.S. smartphone household income). Smart device owners are, on average, more affluent and more educated.
Similar to household income, we find that those who attained higher levels of education are more valuable segments in terms of eCPM generation. Those with a bachelor degree fetch the highest eCPMs, close to $8.00. The second most valuable segment are those even more educated, having earned a master degree or higher.
The Cream-Skimmed Smartphone Upper Middle Class
As a total snapshot, our analysis shows that females and males, between the ages of 25 and 34 years old, who have higher levels of disposable income and a bachelors degree or higher, more strongly interact with mobile ads. Leading sociologists William Thompson and Joseph Hickey define this class as “the rich” or “upper middle class,” comprised of highly educated salaried professionals whose work is largely self-directed. Typical professions for this class include lawyers, physicians, dentists, engineers, accountants, professors, architects, economists and political scientists.
What bodes best for the outlook of mobile advertising is the quality and quantity of the audience that not only uses smartphones and tablets, but also interacts with ads on these devices. Based on our analysis, revealing that the most sought after segments already interact most with mobile ads, a key ingredient required to realize the promise of mobile advertising is the introduction of mobile ad platforms that can segment publisher audiences and enable targeting by advertisers to reach segments of their choice. Like online, which is infinitely more measurable than Print, Radio and TV, mobile advertising is poised to grow radically with the introduction of scalable, data-driven solutions that put advertisers and publishers in control of their own destiny. Actionable data and well-built platforms are the keys to unlocking Madison Avenue spending.
The Super Bowl is an American phenomenon, now largely considered a de facto American holiday. As a premier media event, it regularly attracts record-breaking audiences. This year, Super Bowl XLVI became the most watched television program in history, drawing an audience of 111 million viewers according to The Nielsen Company. Prior to this, the record was held by last year’s Super Bowl, which itself had overtaken the number one spot held for twenty-eight years by the final episode of M*A*S*H.
The Second Screen
Also breaking new ground this year was the concept of the "second screen," which illustrates that while watching TV (the first screen), people often interact with second screens such as smartphones and tablets. To keep viewers focused on the first screen, marketers increasingly are exploring ways to complement the first screen experience with the addition of hash tags, QR codes, voting and more. Among the most ambitious is Shazam, a music and media discovery service, which worked with ad partners such as Toyota, Best Buy, Pepsi, Bud Light and Fed Ex to drive additional second screen interactions related to advertising via the Shazam mobile app. During the halftime show, for example, viewers could get the setlist, buy music and download mobile apps from the artists. Shazam reported millions of audio tags as a result.
Aside from a handful of innovators like Shazam, Flurry believes that the second screen is still largely more disruptive than complementary to first screen viewing. If a consumer is not paying attention to the television program in front of her, she is likely using an application to post social updates or play games. For example, if a Super Bowl ad isn’t holding a viewer’s interest, playing another round of Words with Friends is a likely activity. Monitoring app usage provides Flurry the ability to understand this tightly-coupled relationship between the first and second screen.
Massive Second Screen App Audience
For this report, Flurry tracked U.S. app usage, per second, over the course of Super Bowl XLVI, mapping application session starts to each television spot aired, game time segment, the halftime show, and more. We further studied behavioral differences between males versus females. With Flurry Analytics in over 160,000 applications, the company detects app usage on more than 90% of all iOS and Android devices per day. Let’s start by comparing how many people used apps during the Super Bowl to the number who watched the Super Bowl.
The left-hand column shows the number of users Flurry estimates launched applications in the United States between the hours of 3:15 and 7:15 PM PST on Sunday, February 5. During this four-hour window, in which the Super Bowl was played, Flurry estimates that nearly one-third of the U.S. population used an application. Compared to Nielsen’s estimate that 111 million people watched the Super Bowl this year, the two audiences are similar in size.
The chart above shows estimated app session starts in the U.S. per second. Studying overall trends reveals a highly correlated, inverse relationship between app usage and game, halftime and commercial events. Generally, app usage increased steadily over the first three quarters of the game, showing the challenge in holding peoples’ attention over several hours. However, because this year’s game was close throughout, including an exciting fourth quarter finish, app usage remained relatively checked. Noticeably, app usage declined significantly during the last part of the fourth quarter. The most clearly visible change in app usage occurred during Madonna’s half time show, where app usage remained consistently low for the longest, sustained period of time. From this, we conclude that Madonna strongly held viewers’ attention on the first screen and was a major draw for the Super Bowl this year.
Looking more closely at the details, we see that key moments like the coin toss and kick off were paired with decreases in app usage. Additionally, we found that advertisement popularity could be inferred from rises or declines in app usage. For example, if app usage increases during an ad, we conclude that it did not hold the consumer’s attention. While there is the possibility that certain advertisements encouraged the use of an app, this was not the norm. Studying male versus female usage differences, we found that 62% of overall app usage during the game was driven by females. Flurry also found that women, on average, paid more attention to advertisements, and drove spikes in app usage upon return to the game after commercial breaks.
In this chart, we isolate app usage during broadcast game time only. All breaks for advertising have been excluded. This chart displays a clear pattern of usage by quarter. To create the chart, we took an average for app usage across the entire game, and then for each quarter. Starting on the left-hand side, app usage was lowest during the first quarter. The second and third quarters show increases in app usage, as we assume peoples' attentions waned over the long course of the game. The fourth quarter, however, shows a decline in usage due to the game’s close finish, which drew attention back to the first screen.
In this chart, we isolate app usage to only those times when advertisements were aired. Again, consumer fatigue played a role in attention paid to the first versus second screen. Even with a close Super Bowl game, viewers paid far less attention to ads during the second half. This would suggest that when buying ad times, advertisers should focus on Q1 and Q2 ad slots. Not shown on the chart, pre-game ads, as early as 20 minutes before game time, also held consumer attention well. Half-time, outside of Madonna’s half time show fared worst for holding consumer attention. We speculate that people were either taking a bathroom break or looking for information and/or content on their phones related to Madonna or other artists that appeared in the show.
Flurry Super Bowl Ad Rankings
Finally, Flurry ranks ad Super Bowl ad performance. During the times app usage spikes, we assume ad fail to appeal to the viewer. Conversely, if app usage declines during a TV spot, we assume that the first screen is where the consumer is focused. For each ad, Flurry counted the number of app sessions starts. We then divided that number by the number of seconds in the ad, to get an average number of session starts per second. This gives an apples-to-apples comparison for comparing varying ad lengths. Below, we share rankings for Overall, Male and Female user groups. By our count there were over 100 ads from pre-game through post-game.
The relationship between advertisers and consumers continues to change, with apps playing a key role. In a year when the industry is anticipating major moves from companies like Apple and Google around interactive television, app makers and marketers will need to learn and adapt. In the meantime, we know that Madonna still has the power to make you put your phone down, at least for a while.