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.
Apps are big business, and the biggest app business is games. In 2012, Flurry estimates revenue earned from apps will approach $10 billion, with games taking over 80% of the pie. The free-to-play business model (aka freemium), where consumers download and play the “core loop” of a game for free, but then pay for virtual goods and currency through micro-transactions, is the most prolific business model in the new era of digital distribution. When it comes to app consumption on iOS and Android smart devices, consumers spend over 40% of all their time using games.
The most successful companies in the new mobile economy, from Electronic Arts to Zynga and Mobage to Supercell, deeply understand consumer behavior differences by game genre. This level of understanding greatly informs a company’s app acquisition, retention and monetization strategies. In this report, Flurry examines the consumer behavior differences by app usage, retention and demographics for the top nine freemium game genres in mobile gaming. For this analysis, Flurry leveraged a sample of more than 300 million consumers using iOS and Android games each month. Please note that, for consistency, we include only free titles.
In the chart below, we lay out a “loyalty matrix” that plots the top nine freemium game categories by how often they’re used compared to how long consumers continue to use them over time. Specifically, we plot the 90-day retention rate of app categories on the x-axis against the frequency of use per week on the y-axis. We lay the “scatterplot” out in a Cartesian coordinate system with four quadrants.
Quadrant I represents a “sweet spot” for developers, whose games are used intensively by a set of highly retained users. Well-designed “appointment” mechanics drive frequency, as users are compelled to maintain and progress in their respective game. Social Turn-based games succeed in building an active, loyal user base by offering popular “evergreen” games played among friends. From a revenue perspective, while there exists significant potential to show advertising impressions to consumers who use so frequently, games in the Slots and Resource Management & Simulation (labeled as “Mgmt/Sim”) genres commonly monetize via in-app purchase. However, companies that maximize revenue in Quadrant I extract revenue from consumers willing to pay via in-app purchase, and then by showing ads to those who do not pay.
Quadrant II is characterized by the most intensive usage over a short customer lifecycle, and is occupied solely by the Strategy genre. This audience is demanding, game lifecycles are short and a game’s live services must be flawlessly executed. Successful Strategy game developers accelerate monetization by driving competition among players (“Player vs. Player”) and by encouraging fast game progress through premium currency spends. With frequency of use so high, users churn through content quickly. To maximize retention, developers must continuously release new content after the game’s initial launch.
Quadrant III also attracts a fickle gaming audience, but adds the challenge of having fewer opportunities per week to monetize the user. The well-documented success of the Card-Battle genre in Asia, and now Western markets, is even more impressive when considering the short time frame developers have to drive transactions. Targeted user acquisition is critical to avoid paying for large batches of users that will drop off quickly due to the “hardcore” nature of the content and game mechanics.
Quadrant IV features easy-to-play and highly repeatable games that can remain on a user’s “play list” for years. These evergreen titles may lack the depth required to generate sizeable in-app purchases, but do generate substantial advertising impressions over time. In addition to driving strong ad revenue, the large audience size of these games can be used to cross-promote a developer’s more narrowly focused, but better monetizing titles.
As the mobile app economy grows, the sophistication of its related advertising services will reach those found on the Internet today. Leveraging big data, the ability to target users based on demographics and personas, and then track the effectiveness of such targeting is just starting to take hold (Flurry has invested in this direction with its own services like Flurry AppCircle, an ad network, and Flurry Ad Analytics, an ad effectiveness solution). As developers and app marketing providers become more savvy, they can better acquire the kinds of users that will reliably play and pay in their apps. Below, using the same sample set of games, we look at the Age and Gender of users by genre.
A quick review shows that Quadrant I is largely comprised of middle-aged females that play games we know to have attractive retention and usage metrics.
Quadrant II shows that males are not extending into the same 40+ average age-range as female players. Casino / Poker games tend to attract older males the best.
Quadrant III is undoubtedly the hottest sector of the mobile gaming market, with young, male “core” gamers pausing their console gameplay sessions to increasingly play mobile games. These young men are difficult to corral, but can monetize at a rate that justifies the cost and effort of acquisition.
Quadrant IV shows younger females adopting games that feature more involved gameplay than those played by the middle-aged female crowd. While the youngest users enjoy the quick solo experience of the Endless genre, the late twenties / early thirties crowd are diving deeper into game mechanics and making it a social experience.
As mobile gaming rapidly matures, it is becoming increasingly difficult for new and small developers to succeed. The game quality bar has risen dramatically, user acquisition costs continue to climb and organic installs via app store discovery and featuring are harder to come by. One great equalizer for developers is the ability to collect and harness the power of data. In fact, game developers tend to be the “power users” of analytics, using sophisticated metrics to track user progress, tune gameplay and maximize monetization (a large part of Flurry Analytics' use base is game developers). In an industry that has historically been considered more artistic and subjective, connected devices and the ability to rapidly iterate on already shipped titles has ushered in an age of science and measurement. In short, data has enabled the “gamification” of the mobile industry.
This month, the world’s two largest mobile app platform providers, Apple and Google, enter what is arguably the most critical month of the year for each company, when each hosts their annual developer conference, the Apple Worldwide Developer Conference (WWDC) and Google I/O. While engaged in a multi-year platform war, their success largely depends on innovation provided for their platforms by the third party developer community. If the developer community embraces one platform over the other, developers will build the software that infinitely extends the value of the consumer experience, giving a platform a meaningful edge. The perceived availability of a large, steady stream of high quality apps is a key reason for consumers to initially choose an Android or iOS device, and then to remain loyal. Moreover, given that the mobile industry is among the leading sectors in the worldwide economy, the outcome of these two conferences can largely impact the fate of some of the most prolific, innovative forces in the world’s economy today. Combined, Apple and Google have a market cap of approximately three quarters of a trillion dollars.
This report compares developer support for iOS versus Android and explores the underlying factors that could explain varying levels of developer loyalty. We use the data set collected by Flurry Analytics, now powering consumer insights for more than 70,000 companies across more than 185,000 mobile apps. Each day, Flurry tracks more than 1.2 billion anonymous, aggregated end user sessions across more than 100 million unique devices. Each month, Flurry tracks over 36 billion end user sessions across more than a 500 million devices, a number that is more than 60% of Facebook’s monthly active user base.
Oh Captain, My Captain
At Flurry, we track developer support across the platforms that compete for their commitment. When companies create new projects in Flurry Analytics, they download platform-specific SDKs for their apps. Since resources are limited, choices developers make to support a specific platform signal confidence, as they invest their R&D budget where they expect the greatest return. Further, because developers set up analytics several weeks before shipping their final apps, Flurry has a glimpse into the bets developers are making ahead of the market.
The chart above shows that Apple continues to garner more support from developers. For every 10 apps that developers build, roughly 7 are for iOS. While Google made some gains in Q1 2012, edging up to over 30% for the first time in a year, we believe this is largely due to seasonality, as Apple traditionally experiences a spike in developer support leading up to the holiday season. Apple’s business has more observable seasonality.
The Apple 2-for-1 Proposition
Among the reasons iOS appears more attractive to developers is the dominance by Apple in the tablet category. Not only does Apple offer a large, homogenous smartphone base for which to build software, but also when developers build for smartphones, their apps run on Apple’s iPad tablets as well. That's like getting two platforms for the price of one. Apple offers the most compelling ‘build once, run anywhere’ value proposition in the market today, delivering maximum consumer reach to developers for minimal cost.
The pie chart above demonstrates just how much Apple dominates the tablet category. The Galaxy Tab and Amazon Kindle Fire hold very distant second and third places in terms of consumer usage. To build the chart, Flurry aggregated total worldwide user sessions across the first five months of the year, January through May.
Android Fragmentation Pain
Opposite to the efficiency Apple offers developers through their homogenous device base, Android fragmentation appears to be increasing, driving up complexity and cost for developers. Further, this fragmentation is concentrated primarily in just smartphones, as there is no serious Android tablet contender to the iPad. For Android, Flurry observes fragmentation along two significant vectors, devices and firmware. Let's look at device fragmentation first.
The chart above shows the number of consumer application sessions across the top 20 Android devices in May 2012. Four major OEMs – Samsung, Motorola, HTC and Amazon – have Android devices in the top 20. 17 of the top 20 hold a share of 6% or fewer, among the top 20, meaning that each additional device a developer supports will deliver only a small increase in distribution coverage. However, on Android, both devices and firmware contribute to fragmentation, so let’s look at firmware fragmentation next.
The above chart reveals that the majority of devices in the market run Gingerbread, which is only the third newest iteration of the Android OS. Honeycomb, more optimized for tablets, and Ice Cream Sandwich, which put a lot of effort into the user interface, have a combined 11% of penetration in the market. Froyo, which shipped before Honeycomb and Ice Cream Sandwich, alone has a higher share of firmware penetration than the two newer, more advance firmware versions combined. This means that the majority of consumers are running on an Android operating system that is three to four iterations old.
Running a comparison of revenue generated by top apps on both iOS and Android, Flurry calculates that the difference in revenue generated per active user is still 4 times greater on iOS than Android. For every $1.00 a developer earns on iOS, he can expect to earn about $0.24 on Android. These results mirror earlier findings from similar analysis Flurry conducted in Q4 of 2011 and Q1 of 2012.
At the end of the day, developers run businesses, and businesses seek out markets where revenue opportunities are highest and the cost of building and distributing is lowest. In short, Android delivers less gain and more pain than iOS, which we believe is the key reason 7 out of every 10 apps built in the new economy are for iOS instead of Android.
Over the next two weeks, the momentum of two of the world’s most innovative, influential and prolific technology companies will be impacted by the reaction of the development community to their conferences, Apple WWDC and Google I/O. And as developers watch Apple and Google, the world should watch developers.
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 iOS and Android app economy continues to grow, with freemium games leading all app revenue models, now accounting for more than 65% of app revenue.
In its most recent analysis on freemium games, Flurry revealed that the amount of time and money consumers spend varies significantly by age. Younger consumers spend a lot more time, but older consumers spend a lot more money. In this post, we shift our focus to understand how freemium consumer behavior varies between men and women. We’ll compare differences in time spent, money spent, transaction volume and average price per transaction.
And since the world of marketing and advertising traditionally looks at consumer behavior by “demo” (i.e., the market broken down by demographics of age and sex), we likewise present all of our findings by demo. By Flurry’s calculation, the freemium audience represents among the largest and most attractive concentrations of educated and affluent consumers in consumer technology today. From conversations Flurry is having with the industry, brands and advertising agencies continue to show increasing interest in accessing this audience.
This study uses data from a sample of iOS and Android freemium games with over 20 million users across more than 1.4 billion sessions gathered from Flurry Analytics, which tracks over 110,000 apps across the major smartphone platforms. The amount of money spent was tallied by summing the total transactions multiplied by their respective price points. Time spent was observed by tracking the total minutes spent playing these games. Let’s start by looking at time spent. Please note that figures presented in charts have been rounded up to nearest whole percentages.
The chart above shows a graphical cross-tabbed view of time spent by age versus sex. Adding up all the percentages across each column totals 100%. Blue columns represent males and pink columns represent females. The amount of time spent by males and females is broken down by age group, from youngest to oldest, left to right. The total split of time spent is presented in the legend, with men edging out women 53% to 47%.
What we take away from this chart is that time spent in freemium games on mobile is relatively evenly split among males and females, with 18 -34 males (coincidentally considered the best target for hardcore games) representing the largest group about a third of all players. 18 – 34 year old girls come in accounting for 27% of time spent. In total, freemium gamers tend to be younger, with 83% of them under 34 years old.
Switching our attention to money spent in freemium games, males lead in money spent by a greater degree, accounting for 58% of total money spent. Across each age group, men lead women in spending, with the greatest difference occurring in the 25 – 34 year old age group. For freemium games, spending is concentrated between the ages of 25 - 54, with men in this age range representing nearly half (45%) of spending and women representing another third (32%).
After finding that men and women spend similar amounts of time playing freemium games, but that men out-spend women 58% vs. 42%, we further drilled down to understanding this difference. Breaking out the number of transactions by demo, we see the similar clustering of transactions into the 25 – 54 year old span of users, but see that transactions are more evenly completed by both men and women. In this age range, men drive 40% of transactions and women drive 35%. This is quite a bit different than total money spent by this age group, which came in at 45% male versus 32% female.
Calculating and presenting the data by amount paid per transaction, we find our answer. Men spend an average of 31% more per transaction, or $15.60 versus $11.90. In fact, male spending dominates female spending across each age group by a relatively consistent margin. In the “sweet spot” of revenue generation, 25 – 34 year olds, representing a whopping 49% of total revenue, men out-spend women by 37% per transaction.
Flurry believes that, aside from the raw appeal of a game, the ability to measure and act on this kind of data will make the biggest difference to the success or failure of freemium game companies. Zynga, who is poised to have one of the most successful IPO’s in history, recently described itself as “an analytics company masquerading as a games company.” Segmenting and targeting an app audience will reveal where to spend precious company resources to attract, retain and monetize the most valuable consumers.
In turn, advertising agencies and brands increasingly want to reach this new mass-market audience, who now spends more time in apps than browsing the web, and is primarily concentrated in freemium games. The ability to describe this audience by demo will make the difference between whether or not Madison Avenue can work with game developers. And since only 3% of consumers spend on freemium games, companies that monetize the other 97% of the audience, non-payers, will additionally succeed.
Flurry believes that the industry is at an exciting juncture, in terms of mass-market viability, real consumer spending and the ability to segment and target audiences. We know one thing for certain: companies follow consumers because consumers have money. And consumers are now in mobile apps, especially freemium games.
Mass market consumer adoption of Apple iOS and Google Android mobile devices has attracted an unprecedented volume of content, delivered through applications. Because the majority of these applications downloaded are also free, many ecosystem players have assumed that advertising revenue models will dominate how these apps are monetized.
However, new analysis by Flurry reveals that the sale of virtual goods is overtaking advertising in top categories on the iOS platform. Note that because Google’s Android Market does not yet support in-app purchases (micro-transactions), this model is not yet viable for Android apps. This study was conducted using data collected from a sample of leading iOS social networking and social gaming applications, with a combined reach of 2.2 million daily active users.
Reviewing the chart above, the majority of revenue generated from advertising occurs during the 2009 holiday period. During 2010, however, revenue increasingly shifts from advertising to virtual goods sales until reaching a proportion of more than 80% from virtual goods. Admittedly, the idea that consumers acquiring virtual swords, gold coins and respect points can outperform advertising seems counter-intuitive; however, this phenomenon is neither new nor unique to the iOS platform.
In fact, virtual goods sales already represent the primary source of revenue for social gaming on Facebook. Michael Pachter, Wedbush Morgan Securities video game analyst, reports that social gaming has grown from approximately $600 million in 2008 to $1 billion in 2009. Further, he forecasts that social gaming will generate nearly $1.6 billion this year, and grow to more than $4 billion by 2013.
One factor responsible for low advertising levels may be advertising agencies’ slow acceptance of mobile as a media platform, with skepticism about the viability of social games and social mobile media as a channel for advertisement. With these agencies representing and guiding the biggest brands, they appear to be missing a meaningful opportunity to reach a mass market of consumers who have adopted new platforms and forms of content.
As social games continue to expand their consumer reach, demonstrating their ability to attract an audience beyond teenagers using iPod touches, their relevance will increase. In fact, with mobile social game critical mass now rivaling TV prime time viewership, Flurry anticipates a stronger ad revenue generation through mobile social networking and games in 2011. Over the next 18 to 24 months, Flurry predicts strong revenue growth from both virtual goods and advertising revenue from social gaming. We say play on!
The ability for developers to offer in-app-purchases within paid iPhone apps, as part of iPhone OS 3.0, creates exciting new revenue opportunities. At the same time, the option to sell virtual goods, additional game levels, subscriptions and other forms of micro-transactions, creates more complexity around how to best monetize a given application. Developers who can quickly and effectively measure and optimize the impact of these new pricing options will emerge as winners in the next phase of the iPhone economy.
To date, selling an iPhone application required a few simple decisions: developers could either give an app away for free or charge for it. The two most common business models to emerge were free-to-paid and ad-supported, with some companies opting to ship only paid version of their applications. The decision to offer a free version seems correlated to whether a developer has recognizable brands. For example, EA Mobile, which boasts The Sims 3, Tetris and Scrabble tends to release more paid-only versions. By contrast, companies with more original, less-recognizable titles like Digital Chocolate, which makes Crazy Penguin Catapult, Brick Breaker Revolution and Tower Bloxx frequently go to market with free trials of their games to entice consumers to try-and-buy. Overall, much of the learning in the market has centered on what price to charge, when to drop price and whether ad-supported apps earn more revenue than paid apps.
Already, there are several iPhone apps well suited to micro-transactions. To stay relevant, well ranked, and retain consumers, developers have been adding extra content and features via updates. Pocket God by Bolt Creative* is an example of an app that has strong micro-transaction potential. They have already successfully trained users to expect regularly released content updates that keep the gaming experience fresh (personally, I like the spear used to fight off the Tyrannosaurus Rex). As a result, Pocket God has been ranked among the top paid apps for several weeks. However, they have been collecting a mere $0.99 for the initial download of the app and then giving away a steady stream of additional content after the sale. While their current strategy has earned them users, they should weigh this approach against maximizing revenue through micro-transactions. A risk to keep in mind is that users who have been receiving content updates for free may resent paying for updates going forward. This could be mitigated with a combination of free updates and optional in-app purchases.
To further this example, listed below are some ways Bolt Creative could consider applying micro-transactions:
- Content Packs: Charge $0.49 (UPDATE: $0.99 is currently the lowest price that Apple will allow for any transaction in the App Store) for each content update going forward. Over time, measuring the micro-transaction conversion will allow Bolt to tune the amount of content, how often they offer new content and types of content. These could be new maps complete with common-themed sets of items. Imagine a moon map with all sci-fi items, for example.
- Individual Items: Bolt could test whether selling individual items for $0.25 (UPDATE: $0.99 until Apple allows lower price points) such as ant spray, shark repellent, blueprints to build a shelter, etc. yields higher total revenue per user.
- New features: Offer new features like sending a post card to a friend and challenging them to play a turn-based version of the game, charging $0.99 for these as in-app purchases.
- Subscription: Convert to a subscription billing model, charging $0.99 per month going forward. It goes without saying that the amount of regularly offered content needs to satisfy subscribers to keep them engaged and paying.
Of course with each of these pricing changes, Bolt could lose users. However, if they can find the right model and sweet spot of monetizing the new content they are currently giving away, they could stand to increase revenue significantly. It's really about finding that balance to increase revenues, even if it's with a smaller user base. Either way, it will be key to measure how changing their pricing model affects new user adoption, retention and monetization. All of this can be measured with a robust analytics package like Flurry.
Experienced publishers and developers will tell you that testing and measuring is the best way to focus on the right parts of your business, especially when it comes to your product and how you price it. As it relates to micro-transactions in the App Store, think about the content you are offering and whether it's well suited to micro-transactions. Then test launch different kinds and amounts of content, at different price points, from within different points of your app and at different intervals. Compare how these perform using your analytics service of choice and tweak your approach. With this kind of testing, learning and tuning, you'll be reaping the rewards in the next era of the impressive iPhone economy.
* Bolt Creative is not a Flurry customer and the business model options explored in this blog post are for illustrative purposes only.
An age-old question in any demo or trial program is how much of the product to give away in order to maximize sales. With Free and Paid sections, Apple has designed the iPhone App Store to easily facilitate this classic go-to-market strategy, and we've found that iPhone App free trial strategies are effective.
In the world of mobile applications, the question of how much to give away is actually a relatively new challenge since carriers, for the most part, did not support free trials on their decks. Previously, mobile developers dealt with the occasional issue of defining trial length only when they won a coveted embed (aka pre-load) deal on an OEM's handset. With so many new developers throwing their hat into the iPhone App Store ring, there is little collective experience around this topic. Additionally, mobile application analytics solutions, like Flurry Analytics, did not exist. With Flurry Analytics, the guess work can be completely removed and developers can measure with precision the optimal up-sell point in their trial application.
Before we review mobile developers' choices around "free" iPhone App store offerings, we want to point out that Apple requires the amount of a free game or app to be a full, stand-alone experience. For example, developers cannot "gray out" menu items that would appear in the paid application if the consumer were to purchase it. Additionally, since it's well documented that few ad supported applications generate meaningful revenue, exceptions notwithstanding, we'll suspend this topic for this blog post.
The decision of how much of a free game or application experience to give away begins with understanding the mechanics of the basic equation: Revenue = (Number of Free Players) x (Free to Paid Conversion %) x (Price per Unit). If a developer gives away too much of an experience, it inadvertently satisfies the consumer so that upgrading to the paid version does not seem necessary. However, by giving away a lot of value, the application may become more popular as a result, garnering strong community review scores and increasing the free version installed base. Having a large installed base means that a smaller percentage conversion is needed to make good money. Generally, we recommend a balance with a focus on optimizing conversion.
In other words, we recommend giving enough of the game or application away so the consumer understands the value, but still understands that if they buy the full version, there is a lot more value to be had. Overall, don't be afraid to cut off a consumer if he isn't willing to pay. We subscribe to the philosophy that developers should be focused on finding consumers who are willing to pay, not trying to completely satisfy free-rider consumers.
Below is an example of how one game developer tracked user progression in its free trial game. While this free version shipped with ten levels, analytics showed that most users failed to progress beyond level five of the free game. With the up-sell message shown at the end of the demo, describing additional features the consumer would get when purchasing the full version, many consumers did not see this. By cutting the free version in half, holding the same conversion rate, we estimate this developer could increase its sales by approximately 40%.
Traditionally, the process of deciding how much of a game or application to give away has been more art than science. While the length of a demo experience should vary from app to app, leveraging analytics data allows developers to test, track and tune their free trial strategy to drive maximum conversion rates and revenue.
Among your strongest marketing plays in the App Store is to offer a free trial of your game or application. Not only is the App Store designed for this, but also it's the best way to reduce consumer risk in trying your application, with the goal of eventually getting that user to purchase the full version. Think: money. And from our data, it's among the most effective moves you can make. Here's a motivational example using customer data collected using Flurry's mobile app analytics service in their iPhone apps.
In particular this strategy can favor non-branded applications. For example, instead of simply purchasing a familiar and "safe" game like Tetris, Bejeweled or Pac-Man, a consumer can explore and try your innovative, unknown game for free to decide whether or not to purchase. Simply put, free trial has leveled the playing field for independent developers who previously struggled to get consumers to even give them a try. Additionally, it rewards more established companies who innovate and leverage capabilities of the iPhone hardware to wow consumers - things like touch, the accelerometer, contact list integration for invites, and more.
To further motivate you to seriously consider a comprehensive free trial strategy, we took a look beyond the very hot and sexy iPhone App Store, observing that all major new mobile store entrants will also offer a Free Apps section. Check out a very good side-by-side app store comparison courtesy of Gizmodo that compares the iPhone App Store, Android Market, BlackBerry App World, Windows Mobile Marketplace, Palm App Catalog and Nokia Ovi Store. What this tells us is that a free trial strategy is a must-have going forward in all viable launch strategies. One could argue that uber-brands are an exception to this rule since their consumers are probably willing to buy an application or game without first trying it. However, even if you're the proud steward of such an uber-brand, remember that free trials drive discovery your title, helping increase the adoption of your paid version and ranking in the Paid App category. And don't forget that all the previously disadvantaged Indies now have a shot to take away you consumer with their free trial.
In an upcoming blog entry, I'll touch on how to track and tune your free-to-paid program from a product experience standpoint to maximize your conversion, and therefore revenue generated. Also, there are some Apple policy issues you need to be aware of when designing your free experience - nothing too crazy, but that can result in failing the Apple approval process. Stay tuned.
The glut of applications in the App Store has made application discovery a top concern among companies releasing iPhone games and apps. Last week, 148 Apps reported that more 30,000 games and applications are available in the store, already 5,000 more than the 25,000 announced by Apple when it previewed its iPhone OS 3.0 software on March 17.
With rampant competition, companies must leverage every customer contact point to increase sales. This is where cross-selling can help. Cross-selling targets a company's existing consumers to sell them additional products. On the iPhone, the best opportunity is from within a downloaded application, usually with a link to other games or applications included on the menu screen.
While cross-selling theoretically has been around since the beginning of business, it has become far more effective since the advent of e-commerce on the Internet. In addition to allowing a consumer to quickly and easily complete a follow-on purchase, it can be tracked, measured and tuned for maximum impact.
Since cross-selling is such a classic marketing tool, not to mention easy to execute on the iPhone, we were surprised to observe several developers either not doing so, or treating it as a rushed after thought. So we took a look into our data set to ask: how well does cross-selling work on the iPhone?
The short answer is that it can be highly effective, and the following example demonstrates just how effective. After three weeks of strong sales in the App Store, sales began to decline for Company X's first application. When the second application was released, it included a strong call-to-action to purchase the first application. As the graph below shows, strong sales of the second application, along with solid cross-sell conversion, reversed declining sales of the first application.
It is worth noting that these two applications benefitted from sharing a similar target audience to which both products appealed, and that the efficacy of cross-selling efforts can vary. However, whether your application can achieve a similar lift from cross-selling is something you won't know until you test and measure it for yourself. As all markets mature - and the iPhone App Store has matured in record time - it is important to think strategically about growing your business by maximizing every precious consumer point of contact. Cross-selling remains among the most effective marketing tools.