Facebook now has 819 million mobile monthly active users. That’s a huge audience. That’s actually 71% of total active users.
Yesterday, Facebook reported they generated 41% of total ad revenues via mobile. That’s pretty impressive considering they generated nearly 0% end 2011 when they had already 432 million mobile monthly users. Since the launch of mobile ads in 2012, Facebook steadily increased the share of mobile in total ad revenues: it was 23% end 2012 and 30% in Q1 2013.
There is still a monetization gap in comparison to the share of their mobile audience, but that’s definitely impressive for a new product.
There are a couple of reasons for this sharp increase. Time spent on Facebook is meaningful. Facebook’s mobile ads integrate well in the natural flow of Facebook’s news feeds. They are quite visible and are increasingly successful at driving mobile app installs. According to our European Technographics Consumer Technology Online Survey, Q4 2012, 16% of online adult smartphone owners (ages 16-plus) who use apps report that they first learned about an app via social networking websites such as Facebook. No wonder why the likes of Fiksu and other app boosters spent a lot of money on Facebook mobile ads. Cost per click increased despite a lot more clicks and ads shown.
For this approach to be successful in the longer term, there are a couple of key questions to be answered:
Last month I published new research on the Database of Affinity — a catalogue of people’s tastes and preferences collected by observing their social behaviors on sites like Facebook and Twitter — and how that database will change marketing. And I'm pleased to say I've gotten a lot of great feedback on that research. So I'm excited to be presenting the idea on stage at our Marketing Leadership Forum in London later this month.
What is the database of affinity?
I hope you'll be able to join us in London on May 21 and 22.
Recently we described an idea called the database of affinity: A catalogue of people’s tastes and preferences collected by observing their social behaviors on sites like Facebook and Twitter. Why are we so excited about this idea? Because if Facebook or Twitter or some other company can effectively harness the data from all the likes and shares and votes and reviews they record, they could bring untold rigor, discipline, and success to brand advertising.
But exploiting the database of affinity won’t be easy. Any company hoping to turn affinity data into something marketers can use will need three things:
Lots of affinity data from lots of sources. The raw data required to build a functional database of affinity doesn’t live in just one place. Facebook controls the most "like" data, recording more than 80 billion per month at last check. But Twitter records more "talking" than anyone else (1.5 billion tweets per month); Amazon collects the most reviews (well over 6 million per month); and Google’s YouTube and Google Display Network have data on how a billion people prefer to spend their time.
The ability to bring meaning to that data. It’s easy to draw simple conclusions from affinity data: If you ‘like’ snowboarding you might like to see an ad for energy drinks. But the real value in affinity data won’t be unlocked until we can find hidden combinations of affinity that work for marketing. That’ll require technologies and teams that can do some serious data analysis — as well as a real-time feedback loop to determine whether people really are interested in the ads targeted to them based on such complex assumptions.
For years, brand marketers have guessed at people’s affinities from the barest of demographic, geographic, and contextual clues. We deduce that Midwestern men prefer pickup trucks and that people watching extreme sports like energy drinks, and then we spend billions advertising to these inferred affinities.
But today, we no longer have to guess. Every day huge numbers of people online tell us what they like. They do this by clicking a ‘like’ button, of course — but there are many other ways people express affinity: talking about things on Twitter and in blogs; reviewing things on Amazon and Yelp; spending time with content on YouTube (and telling us where they’re spending their offline time on Foursquare); and sharing things through both public and private social channels.
People’s rush to post their affinities online recalls another flood of data that began a decade ago: the explosion in online searches. John Battelle once described the data created by search as the “database of intentions,” which I’d define as “a catalogue of people’s needs and desires collected by observing their search behaviors.” In the same way, the result of all these online expressions of “liking” has created the “database of affinity,” which Forrester defines as:
A catalogue of people’s tastes and preferences collected by observing their social behaviors.
Facebook made headlines last Friday with its announcement that it had been the victim of a sophisticated security attack. All major news publications picked up the story, citing widespread concern about the implications of the breach.
The breach itself, however, was largely a nonevent from a security standpoint.
Facebook identified the security breach before it infiltrated too deeply into company systems, remediated all compromised machines, informed law enforcement, and reported the Java exploit to its parent owner Oracle – acting quickly and appropriately. Most importantly, Facebook made it clear that the breach did not expose any of its users’ data.
Today’s announcements at the Open Compute Project (OCP) 2013 Summit could be considered as tangible markers for the OCP crossing the line into real relevance as an important influence on emerging hyper-scale and cloud computing as well as having a potential bleed-through into the world of enterprise data centers and computing. This is obviously a subjective viewpoint – there is no objective standard for relevance, only post-facto recognition that something was important or not. But in this case I’m going to stick my neck out and predict that OCP will have some influence and will be a sticky presence in the industry for many years.
Even if their specs (which look generally quite good) do not get picked up verbatim, they will act as an influence on major vendors who will, much like the auto industry in the 1970s, get the message that there is a market for economical “low-frills” alternatives.
Major OCP Initiatives
To date, OCP has announced a number of useful hardware specifications, including:
Windows 8 is a make or break product launch for Microsoft. Windows will endure a slow start as traditional PC users delay upgrades, while those eager for Windows tablets jump in. After a slow start in 2013, Windows 8 will take hold in 2014, keeping Microsoft relevant and the master of the PC market, but simply a contender in tablets, and a distant third in smartphones.
Microsoft has long dominated PC units, with something more than 95% sales. The incremental gains of Apple’s Mac products over the last five years haven’t really changed that reality. But the tremendous growth of smartphones, and then tablets, has. If you combine all the unit sales of personal devices, Microsoft’s share of units has shrunk drastically to about 30% in 2012.
It’s hard to absorb the reality of the shift without a picture, so in the report “Windows: The Next Five Years,” we estimated and forecast the unit sales of PCs, smartphones, and tablets from 2008 to 2016 to create a visual. As you can see below in the chart of unit sales, Microsoft has and will continue to grow unit sales of Windows and Windows Phone. But the mobile market grew very fast in the last five years, while Microsoft had tiny share in smartphones and no share in tablets.
If you look at the results by share of all personal devices, below, you can see how big a shift happened over the last five years as smartphone units exploded and the iPad took hold.
Microsoft Windows will power just one-third of personal computing devices sold during 2012. Say what? Over the past five years, the transition to mobile devices has transformed Microsoft’s position from desktop dominance to one of several players vying for share in a new competitive landscape.
And so Microsoft is making some very bold moves to transform Windows: creating a singular touch-native UX for a seamless experience across PCs and mobile devices, building an app store distribution model, and engaging its vast user base to develop core personal cloud services.
You’ll learn about the trends and behaviors shaping a painful, but ultimately successful, five-year migration for the Windows franchise. We will size and forecast the future of Windows’ presence in a device landscape where market share is measured across all computing devices, not just PCs. And we will outline the new personal computing success metrics for OS providers and ecosystems, which look beyond device market share to customer engagement across multiple formats, online services, and content delivery.
Creators sit at the top of Forrester’s Social Technographics® ladder: They are the consumers who write blogs and articles, upload self-created video and music, post photos, and maintain their own web pages. More than any other group, Creators are shaping the face of consumer content online. We recently published a report called “Exploring The Social Technographics® Ladder: Creators.” It shows that Creators are great advocates for the brands they like, and that they have, on average, many more friends and followers to share their opinions with than any other group.
However, what was really intriguing is how much they value feedback from companies and brands. Even more importantly, more Creators expect companies to respond to positive posts about products/services than to negative ones.
This is contrary to popular belief. In fact, there’s plenty of advice out there on what you should do in a crisis or how to respond to someone who’s posted a complaint. There’s not much advice on how to handle positive feedback, but in fact, it’s one of the best ways to trigger (and motivate) your brand advocates.
In our research on eBusiness and channel strategy, we often come across clusters of innovation where innovation by one company in a sector causes its competitors not only to match it, but to try to leapfrog it -- resulting in a rapid cycles of innovation. Among the examples of these clusters are insurance companies in the US (Progressive, Geico and a growing number of others) and banks in Spain (Bankinter, La Caixa, BBVA and Banco Sabadell).
Another of those clusters is the retail banking market in Turkey. Last week I was in Istanbul and was able to see some of the innovations in person and meet a number of heads of eBusiness at Turkey's big banks. Turkey's banks have been quick to adopt digital technologies and achieved some world firsts for the banking industry. Here are a few examples you might like:
Ziraat Bank has deployed a network of unstaffed video kiosks (see picture, right), which it calls video teller machines, that use video-conferencing to connect customers with agents in the bank’s contact centre. Customers can use the kiosks to deposit and withdraw money, buy and sell foreign exchange, pay bills, transfer money and buy bonds. The kiosks let the bank expand its network much more quickly than building conventional branches would do.