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Death, Data and the Digital Hereafter

13 Feb

The digital afterlife: thinking about what happens to our online life when we die. Image  credit: Richard Parker/

The digital afterlife: thinking about what happens to our online life when we die. Image credit: Richard Parker/

A soon-to-be-released science fiction movie, Transcendence, features Johnny Depp as a scientist who becomes immortalised as a digital entity – an event that is referred to by many as theSingularity. This is still rather far from reality, of course, but it did get me thinking about death and what happens to ‘our’ data – all those Facebook chats, Instagram photos and so on. I’m talking about the digital hereafter.

Your digital persona

It was around the turn of the millennium when I first started using the internet seriously (by which I mean how much time and energy I spent on the internet, not what I used it for). Back then, I spent my time online divided between MySpace, and plenty of forums. I certainly wasn’t thinking about a data backlog, or what would happen when I die. But as more and more of my life moved online, this has come to my attention as something not too many people think about. I don’t actually know, but I would guess that I have a profile at well over 200 websites, including social media sites, forums, retail and financial services, and any number of arbitrary web-apps that required me to sign up to use them just once.

My point is, as the internet has grown we have strewn our personal data far and wide across numerous websites, with little further thought for that data, sequestered in servers across the world. And in so doing, we have created a kind of avatar – a nebulous collection of data points in the cloud, that together makes up an online persona.

Your data after you die

Google, Facebook, and Twitter all have strategies to deal with accounts of the deceased –Facebook will ‘memorialise’ a profile if a family member can confirm the death of that person. This turns the profile of the deceased into a public memorial page, which won’t show status updates but still allows loved ones to post messages. Twitter just locks your information down, while Google has what they call the Inactive Account Manager – after a defined period of inactivity, Google will  transfer your data to a trusted contact and/or shut down your account. In general, it seems that the data will be made available to loved ones (or the courts) if absolutely necessary. Several companies have positioned themselves as managers of you digital legacy – covered in this blogpost. For a more in-depth discussion of digital estate planning, see this NY Times articlepublished last year.

Now for some more outlandish options for the digital afterlife. Several companies have caught on to this opportunity, and are offering to immortalise your digital persona for posterity. Eterni.mepromises to create a digital version of the deceased, which will continue to post status updates and send messages. The company will parse your data to create an virtual ‘you’ based on your likes, browsing history and previous social media messages. LivesOn is another such project, which promises to keep tweeting for you after you die. With taglines like ‘When your heart stops beating, you’ll keep tweeting. Welcome to your social afterlife.’ (LivesOn) or the frankly misleading ‘Simply Become Immortal’ (, these services are not for everybody. Personally, I find the idea of a dead loved one tweeting something inane rather distasteful, and I would be downright upset if a digital ghost started messaging me about the good times we had back when they were alive.

Corporates aren’t the only ones thinking quite seriously about this stuff – there is a website, The Digital Beyond, which has been started to discuss and document these issues. The owners of the site have also written a book discussing one’s options for curating the digital remains of a loved one. Academia is getting in on the act, too: researchers in the UK are studying how Western public mourning practices are changing. They document massive growth in online mourning rituals, such as the aforementioned memorial pages on Facebook, blogs dedicated to the memory of loved ones, and so on.

Another way of dealing with digital remains

I would like to consider another aspect of this discussion, one which I have not seen discussed much: the value of that data as a public resource. Data has become the unofficial second currency of business in the 21st century – just look at mobile developers. They run at a loss for years, until someone will buy their captive audience from them as data for the great online advertising machine. As it stands, the digital remnants of a life belong to the company that owned that data to begin with. But I have a alternative suggestion, which would be massively useful if implemented correctly. What if, after a reasonable mourning period (call it five years to be safe), all of that data was parsed, anonymised, and made publicly available, for free? Think of the wealth of data that would represent, over the next few decades, or even centuries. Big Data is an overhyped topic right now, but we are already seeing it’s mark across the world. Think of the complex modelling and forecasting that would be possible. Think of the boost to academia, industry, commerce, financial services and even sport. And applied to humanitarian work in health or the environment, it would quite literally change the world.



Facebook’s Future Plans for Data Collection

6 Dec

Facebook’s dark plans for the future are given away in its patent applications.
On November 12 Facebook, Inc. filed its 178th patent application for a consumer profiling technique the company calls “inferring household income for users of a social networking system.”

“The amount of information gathered from users,” explain Facebook programmers Justin Voskuhl and Ramesh Vyaghrapuri in their patent application, “is staggering — information describing recent moves to a new city, graduations, births, engagements, marriages, and the like.” Facebook and other so-called tech companies have been warehousing all of this information since their respective inceptions. In Facebook’s case, its data vault includes information posted as early as 2004, when the site first went live. Now in a single month the amount of information forever recorded by Facebook —dinner plans, vacation destinations, emotional states, sexual activity, political views, etc.— far surpasses what was recorded during the company’s first several years of operation. And while no one outside of the company knows for certain, it is believed that Facebook has amassed one of the widest and deepest databases in history. Facebook has over 1,189,000,000 “monthly active users” around the world as of October 2013, providing considerable width of data. And Facebook has stored away trillions and trillions of missives and images, and logged other data about the lives of this billion plus statistical sample of humanity. Adjusting for bogus or duplicate accounts it all adds up to about 1/7th of humanity from which some kind of data has been recorded.

According to Facebook’s programmers like Voskuhl and Vyaghrapuri, of all the clever uses they have already applied this pile of data toward, Facebook has so far “lacked tools to synthesize this information about users for targeting advertisements based on their perceived income.” Now they have such a tool thanks to the retention and analysis of variable the company’s positivist specialists believe are correlated with income levels.

They’ll have many more tools within the next year to run similar predictions. Indeed, Facebook, Google, Yahoo, Twitter, and the hundreds of smaller tech lesser-known tech firms that now control the main portals of social, economic, and political life on the web (which is now to say everywhere as all economic and much social activity is made cyber) are only getting started. The Big Data analytics revolutions has barely begun, and these firms are just beginning to tinker with rational-instrumental methods of predicting and manipulating human behavior.

There are few, if any, government regulations restricting their imaginations at this point. Indeed, the U.S. President himself is a true believer in Big Data; the brain of Obama’s election team was a now famous “cave” filled with young Ivy League men (and a few women) sucking up electioneering information and crunching demographic and consumer data to target individual voters with appeals timed to maximize the probability of a vote for the new Big Blue, not IBM, but the Democratic Party’s candidate of “Hope” and “Change.” The halls of power are enraptured by the potential of rational-instrumental methods paired with unprecedented access to data that describes the social lives of hundreds of millions.

Facebook’s intellectual property portfolio reads like cliff notes summarizing the aspirations of all corporations in capitalist modernity; to optimize efficiency in order to maximize profits and reduce or externalize risk. Unlike most other corporations, and unlike previous phases in the development of rational bureaucracies, Facebook and its tech peers have accumulated never before seen quantities of information about individuals and groups. Recent breakthroughs in networked computing make analysis of these gigantic data sets fast and cheap. Facebook’s patent holdings are just a taste of what’s arriving here and now.

The way you type, the rate, common mistakes, intervals between certain characters, is all unique, like your fingerprint, and there are already cyber robots that can identify you as you peck away at keys. Facebook has even patented methods of individual identification with obviously cybernetic overtones, where the machine becomes an appendage of the person. U.S. Patents 8,306,256, 8,472,662, and 8,503,718, all filed within the last year, allow Facebook’s web robots to identify a user based on the unique pixelation and other characteristics of their smartphone’s camera. Identification of the subject is the first step toward building a useful data set to file among the billion or so other user logs. Then comes analysis, then prediction, then efforts to influence a parting of money.

Many Facebook patents pertain to advertising techniques that are designed and targeted, and continuously redesigned with ever-finer calibrations by robot programs, to be absorbed by the gazes of individuals as they scroll and swipe across their Facebook feeds, or on third party web sites.

Speaking of feeds, U.S. Patent 8,352,859, Facebook’s system for “Dynamically providing a feed of stories about a user of a social networking system” is used by the company to organize the constantly updated posts and activities inputted by a user’s “friends.” Of course embedded in this system are means of inserting advertisements. According to Facebook’s programmers, a user’s feeds are frequently injected with “a depiction of a product, a depiction of a logo, a display of a trademark, an inducement to buy a product, an inducement to buy a service, an inducement to invest, an offer for sale, a product description, trade promotion, a survey, a political message, an opinion, a public service announcement, news, a religious message, educational information, a coupon, entertainment, a file of data, an article, a book, a picture, travel information, and the like.” That’s a long list for sure, but what gets injected is more often than not whatever will boost revenues for Facebook.

The advantage here, according to Facebook, is that “rather than having to initiate calls or emails to learn news of another user, a user of a social networking website may passively receive alerts to new postings by other users.” The web robot knows best. Sit back and relax and let sociality wash over you, passively. This is merely one of Facebook’s many “systems for tailoring connections between various users” so that these connections ripple with ads uncannily resonant with desires and needs revealed in the quietly observed flow of e-mails, texts, images, and clicks captured forever in dark inaccessible servers of Facebook, Google and the like. These communications services are free in order to control the freedom of data that might otherwise crash about randomly, generating few opportunities for sales.

Where this fails Facebook ratchets up the probability of influencing the user to behave as a predictable consumer. “Targeted advertisements often fail to earn a user’s trust in the advertised product,” explain Facebook’s programmers in U.S. Patent 8,527,344, filed in September of this year. “For example, the user may be skeptical of the claims made by the advertisement. Thus, targeted advertisements may not be very effective in selling an advertised product.” Facebook’s computer programmers who now profess mastery over sociological forces add that even celebrity endorsements are viewed with skepticism by the savvy citizen of the modulated Internet. They’re probably right.

Facebook’s solution is to mobilize its users as trusted advertisers in their own right. “Unlike advertisements, most users seek and read content generated by their friends within the social networking system; thus,” concludes Facebook’s mathematicians of human inducement, “advertisements generated by a friend of the user are more likely to catch the attention of the user, increasing the effectiveness of the advertisement.” That Facebook’s current So-And-So-likes-BrandX ads are often so clumsy and ineffective does not negate the qualitative shift in this model of advertising and the possibilities of un-freedom it evokes.

Forget iPhones and applications, the tech industry’s core consumer product is now advertising. Their essential practice is mass surveillance conducted in real time through continuous and multiple sensors that pass, for most people, entirely unnoticed. The autonomy and unpredictability of the individual —in Facebook’s language the individual is the “user”— is their fundamental business problem. Reducing autonomy via surveillance and predictive algorithms that can placate existing desires, and even stimulate and mold new desires is the tech industry’s reason for being. Selling their capacious surveillance and consumer stimulus capabilities to the highest bidder is the ultimate end.

Sounds too dystopian? Perhaps, and this is by no means the world we live in, not yet. It is, however, a tendency rooted in the tech economy. The advent of mobile, hand-held, wirelessly networked computers, called “smartphones,” is still so new that the technology, and its services feel like a parallel universe, a new layer of existence added upon our existing social relationships, business activities, and political affiliations. In many ways it feels liberating and often playful. Our devices can map geographic routes, identify places and things, provide information about almost anything in real time, respond to our voices, and replace our wallets. Who hasn’t consulted “Dr. Google” to answer a pressing question? Everyone and everything is seemingly within reach and there is a kind of freedom to this utility.

Most of Facebook’s “users” have only been registered on the web site since 2010, and so the quintessential social network feels new and fun, and although perhaps fraught with some privacy concerns, it does not altogether fell like a threat to the autonomy of the individual. To say it is, is a cliche sci-fi nightmare narrative of tech-bureaucracy, and we all tell one another that the reality is more complex.

Privacy continues, however, too be too narrowly conceptualized as a liberal right against incursions of government, and while the tech companies have certainly been involved in a good deal of old-fashioned mass surveillance for the sake of our federal Big Brother, there’s another means of dissolving privacy that is more fundamental to the goals of the tech companies and more threatening to social creativity and political freedom.

Georgetown University law professor Julie Cohen notes that pervasive surveillance is inimical to the spaces of privacy that are required for liberal democracy, but she adds importantly, that the surveillance and advertising strategies of the tech industry goes further.

“A society that permits the unchecked ascendancy of surveillance infrastructures, which dampen and modulate behavioral variability, cannot hope to maintain a vibrant tradition of cultural and technical innovation,” writes Cohen in a forthcoming Harvard Law Review article.

“Modulation” is Cohen’s term for the tech industry’s practice of using algorithms and other logical machine operations to mine an individual’s data so as to continuously personalize information streams. Facebook’s patents are largely techniques of modulation, as are Google’s and the rest of the industry leaders. Facebook conducts meticulous surveillance on users, collects their data, tracks their movements on the web, and feeds the individual specific content that is determined to best resonate with their desires, behaviors, and predicted future movements. The point is to perfect the form and function of the rational-instrumental bureaucracy as defined by Max Weber: to constantly ratchet up efficiency, calculability, predictability, and control. If they succeed in their own terms, the tech companies stand to create a feedback loop made perfectly to fit each an every one of us, an increasingly closed systems of personal development in which the great algorithms in the cloud endlessly tailor the psychological and social inputs of humans who lose the gift of randomness and irrationality.

“It is modulation, not privacy, that poses the greater threat to innovative practice,” explains Cohen. “Regimes of pervasively distributed surveillance and modulation seek to mold individual preferences and behavior in ways that reduce the serendipity and the freedom to tinker on which innovation thrives.” Cohen has pointed out the obvious irony here, not that it’s easy to miss; the tech industry is uncritically labeled America’s hothouse of innovation, but it may in fact be killing innovation by disenchanting the world and locking inspiration in an cage.

If there were limits to the reach of the tech industry’s surveillance and stimuli strategies it would indeed be less worrisome. Only parts of our lives would be subject to this modulation, and it could therefore benefit us. But the industry aspires to totalitarian visions in which universal data sets are constantly mobilized to transform an individual’s interface with society, family, the economy, and other institutions. The tech industry’s luminaries are clear in their desire to observe and log everything, and use every “data point” to establish optimum efficiency in life as the pursuit of consumer happiness. Consumer happiness is, in turn, a step toward the rational pursuit of maximum corporate profit. We are told that the “Internet of things” is arriving, that soon every object will have embedded within it a computer that is networked to the sublime cloud, and that the physical environment will be made “smart” through the same strategy of modulation so that we might be made free not just in cyberspace, but also in the meatspace.

Whereas the Internet of the late 1990s matured as an archipelago of innumerable disjointed and disconnected web sites and databases, today’s Internet is gripped by a handful of giant companies that observe much of the traffic and communications, and which deliver much of the information from an Android phone or laptop computer, to distant servers, and back. The future Internet being built by the tech giants —putting aside the Internet of things for the moment— is already well into its beta testing phase. It’s a seamlessly integrated quilt of web sites and apps that all absorb “user” data, everything from clicks and keywords to biometric voice identification and geolocation.

United States Patent 8,572,174, another of Facebook’s recent inventions, allows the company to personalize a web page outside of Facebook’s own system with content from Facebook’s databases. Facebook is selling what the company calls its “rich set of social information” to third party web sites in order to “provide personalized content for their users based on social information about those users that is maintained by, or otherwise accessible to, the social networking system.” Facebook’s users generated this rich social information, worth many billions of dollars as recent quarterly earnings of the company attest.

In this way the entire Internet becomes Facebook. The totalitarian ambition here is obvious, and it can be read in the securities filings, patent applications, and other non-sanitized business documents crafted by the tech industry for the financial analysts who supply the capital for further so-called innovation. Everywhere you go on the web, with your phone or tablet, you’re a “user,” and your social network data will be mined every second by every application, site, and service to “enhance your experience,” as Facebook and others say. The tech industry’s leaders aim to expand this into the physical world, creating modulated advertising and environmental experiences as cameras and sensors track our movements.

Facebook and the rest of the tech industry fear autonomy and unpredictability. The ultimate expression of these irrational variables that cannot be mined with algorithmic methods is absence from the networks of surveillance in which data is collected.

One of Facebook’s preventative measures is United States Patent 8,560,962, “promoting participation of low-activity users in social networking system.” This novel invention devised by programmers in Facebook’s Palo Alto and San Francisco offices involves a “process of inducing interactions,” that are meant to maximize the amount of “user-generated content” on Facebook by getting lapsed users to return, and stimulating all users to produce more and more data. User generated content is, after all, worth billions. Think twice before you hit “like” next time, or tap that conspicuously placed “share” button; a machine likely put that content and interaction before your eyes after a logical operation determined it to have the highest probability of tempting you to add to the data stream, thereby increasing corporate revenues.

Facebook’s patents on techniques of modulating “user” behavior are few compared to the real giants of the tech industry’s surveillance and influence agenda. Amazon, Microsoft, and of course Google hold some of the most fundamental patents using personal data to attempt to shape an individual’s behavior into predictable consumptive patterns. Smaller specialized firms like Choicestream and Gist Communications have filed dozens more applications for modulation techniques. The rate of this so-called innovation is rapidly telescoping.

Perhaps we do know who will live in the iron cage. It might very well be a cage made of our own user generated content, paradoxically ushering in a new era of possibilities in shopping convenience and the delivery of satisfactory experiences even while it eradicates many degrees of chance, and pain, and struggle (the motive forces of human progress) in a robot-powered quest to have us construct identities and relationships that yield to prediction and computer-generated suggestion. Defense of individual privacy and autonomy today is rightly motivated by the reach of an Orwellian security state (the NSA, FBI, CIA). This surveillance changes our behavior by chilling us, by telling us we are always being watched by authority. Authority thereby represses in us whatever might happen to be defined as “crime,” or any anti-social behavior at the moment. But what about the surveillance that does not seek to repress us, the watching computer eyes and ears that instead hope to stimulate a particular set of monetized behaviors in us with the intimate knowledge gained from our every online utterance, even our facial expressions and finger movements?


Evaluating ROI on Social Media for Telecom Service Providers

21 Nov

Which social media website to choose based on certain user specific criteria (Created using Gephi)

Which social media website should be chosen? What is the Return on Investment? (Picture Created using Gephi based on list of social media websites from wikipedia & calculating weighted mean)

Most telecom service providers use IT in key business processes like Marketing, Sales & Service. It would be worthwhile to integrate social media listening capabilities with the current systems so that the social media impact on the business can be measured. Below are a few metrics I could think of that can be used to understand if the social media strategy used is a successful one.

Customer Readiness for Social Media Influence – Marketing

Customer readiness to accept the influence of social media in their decisions to purchase products from the service providers can be understood with the following metrics. Based on the metrics given below, the social media campaign / channels can be decided upon.

  • During customer care / dealer / web portal interactions, are your customers ready to share their social media handles?

  • Which social media handle data are your customers more willing to give (like facebook, twitter, google+, linkedIn, etc.,) and our activity on the particular site.

  • What % of the entire customer base’s social media handles do you have?

  • What is the increase in the readiness of the customer to share their social media data?

  • How many customers interact with you on social media (like / favorite / comment / share)

 Branding – Marketing

Brand perception relies a lot on the products the service provider sells and hence it is important for the listening engine to understand what customers (prospective & current) think about:

  • the products released recently and the positives / negatives through sentiment analysis

  • the most popular products sold (according to the users)

  • the reasons associated with the segment-wise popularity of the product.

  • No. of times a product has been discussed on social media and its impact on sales.

  • Influence on branding by those who are not our customers or unidentified as customers.

 Campaign Management – Marketing / Sales

Nowadays we see a lot of campaigns being created exclusively for those on social media. It is important to keep track of

  • the number of campaigns that have been created based on the requests / interests identified through social media.

  • The number of campaigns created and the revenue out of these campaigns should give an idea of the returns on investment.

  • Map enterprise level data with the campaign data to understand the segment which likes the campaign.

  • How successful are the campaigns through Social Media? Revenue vs cost from these campaigns?

 Generating leads – Sales

While it is good to interact with customers and enhance brand awareness and influence, if the goal of the service provider is to actually find leads and convert them into business, the following are very important:

  • How many people have you converted into leads through Social Media?

  • the % of leads that could be contacted through Social media / outside of Social media.

  • How much % of these leads have been converted into actual customers by selling your products / subscriptions?

 Client specific goals & parameters – Service

The listening engine should take into consideration that each service provider / client base is unique and include the client specific goals into consideration before posting content across the social media. A few examples are given below:

  1. For example, if a telecom service provider wants to increase the usage of self-service portals thereby reducing the customer service requests through customer care channel, the company needs to devise logic to convert the goals to measurable ones & spread awareness through social media

  2. How much time can the service provider afford to spend on social media.

  3. If the customer base is multilingual, are their messages routed to the right support agents? Or is there an internal re-assignment?

Complaint Handling – Service

The number of issues / complaints identified gives a sense of the effectiveness of the listening engine. All identified issues / complaints could be saved as service requests / trouble tickets based on the nature of the issue. It is important to understand how many service requests raised are actually solved so that it can be compared to the traditional way of raising service requests. The Service Requests raised through the listening engine are initially not tagged to any of the accounts (remember “eventual consistency” in previous article?). The approximate account – subscription details to be tagged to this request is maintained in other fields and the customer care agent manually accepts or changes the account tagged. If the information cannot be tagged to any of the accounts, a personal message is sent to the user for the details and responded to their post on the same channel.

  • Number of service requests / trouble tickets have been identified through social media

  • % of service requests / trouble tickets solved

  • % of solved issues required a follow up customer care call VS how many were solved using information in social media itself

  • % of anonymous Service Requests that are later tagged to accounts & channels used as mentioned above

Churn reduction % – Service

Churn is the amount of customers moving from our network to other networks. Social media can help the service provider in understanding the ported out customers by listening to them on social media. The impact of social media on churn reduction can be found by looking at the following metrics:

  • The churn ratio among those people engaged on social media to people not engaged on social media. Higher the ratio, lower is the impact of social media influence on churn reduction

  • the number of Number Portability Requests due to social media. (This could happen due to competitors or due to influencers on social media who influence our customers to move out to another network)

  • Approx. number of customers where social media interactions were helpful to prevent churn beforehand

  • Positive / negative of feedback of customers who have ported our from a network on social media

 Competitor Analysis – Marketing

Most metrics defined here need to be monitored for our competitors as well. This gives a better perspective of the strengths and weaknesses of competitors, as perceived by the direct customers. As we monitor, we could scale up our strengths and also grow in areas considered popular by the end users. The perception & changing perception of our own strengths and weaknesses as perceived by people can be monitored on a regular basis and checked if we are moving in the right direction. The number of customers identified because we are monitoring our competitors can also be noted on a continuous basis.

One more important metric is the number of voices of those who popularize our competitors and their influence rate. These will help us understand the kind of people our customers listen to, in addition to us and our competitors.

Big Data is not about others success stories, but ours!


Mobile Ads Are the Future. They’re Also Lousy

6 Nov
Companies across the Internet continually proclaim mobile ads as the next great frontier. Pandora Media (P), Twitter, and other big names often derive the majority of their revenue from them. On Oct. 23, Facebook’s (FB)stock leapt more than 10 percent on news that the social network earned 14 percent of its third-quarter revenue from mobile ads, up from almost nothing in the first quarter. That mobile advertising should be an enormous business makes sense. After all, our smartphones are always with us, know where we are, and collect far more data about us than a desktop PC. So if mobile has such potential, why are the ads so mediocre?

“Most mobile advertising is done as an afterthought,” says Eric Picard, chief executive officer of Rare Crowds, an ad technology company. “Immature designers have just sort of slapped banner ads in there.” Working with a tiny canvas—a smartphone display—most ads take one of two forms, each with obvious shortcomings. There is the tiny banner ad Picard refers to, which has little room to say anything more than “Click here for something!” and the interstitial, the screen that pops up and interrupts you while you’re trying to read something else.

These two simple forms have their roots in other media—only in other media they make a lot more sense. A print advertisement or, for that matter, a Web ad on a computer’s large display, is based on the concept of adjacency: We tolerate it because it’s next to content we want to consume. Television ads work the same way (at least for people without DVRs), but with the added dimension of time. Modern Family will be interrupted, sure, but the show’s story structure is designed for that, and we’ll sit through some commercials because we want to see what’s going to happen with Phil Dunphy’s next crazy scheme to surprise Claire.

When we encounter a mobile ad, it’s disruptive, and not in the positive way that business gurus breathlessly use the word. “When I see an ad pop up on my phone, I get scared,” says Al Rotches, a Web ad designer who has worked on Internet campaigns for Barack Obama, Honda Motor (HMC), and Trojan Brand Condoms (CHD). “When I’m on my phone, this is my thing,” he adds. “I don’t want to be tracked, I don’t want to be interrupted.”

Worldwide mobile-ad spending will reach $6.4 billion this year and more than $23.6 billion by 2016, according to researcher EMarketer. Google (GOOG) is the biggest beneficiary, but even it realizes that banner ads and interstitials aren’t going to work on a smartphone. The company has been developing enhanced ad services like click-to-call buttons, which allow people to contact an advertiser directly about an offer using the phone in their hand. Its Android devices also can use Google Now, a virtual personal assistant that keeps track of your frequently visited locations and repeating calendar entries and then tries to provide relevant information, such as a traffic report minutes before you head to work. The company hasn’t sent out any advertising through this service, but many in the industry expect it will: Besides the traffic, wouldn’t you be interested in a coupon for a new breakfast sandwich at that coffee place on your way to the office?

The company’s mobile-payment system, Google Wallet, is another way it’s moving beyond the standard model. Storing a user’s credit-card information does two things: It makes mobile purchases easier, since a person doesn’t have to enter payment information on a small device, and it provides a way to follow the money. Without a payment platform, Google and other ad networks have no way to determine whether an ad persuades a user to make an offline purchase. But if you use Google Wallet to pay a florist after Google sent you an ad from that florist, Google can make some conclusions about that ad’s efficacy and adjust prices accordingly.

Facebook’s rapid mobile-ad expansion has been possible because more than 60 percent of its users access the social networking site on a mobile device. The company attributes its recent growth in mobile ads to what is known in the digital-ad world as “native advertising,” or advertising that’s integrated with a site’s regular content. In Facebook’s case, that means ads that appear in a user’s news feed, which the company calls a “sponsored story.”

“We want to make the ads on Facebook part of the user experience in a seamless way,” says Gokul Rajaram, Facebook’s product director for advertising. That not only means incorporating ad content into news feeds, but also storing users’ credit-card information so they can make purchases with a single click. “On mobile, the need to reduce friction in any transaction is exponentially greater,” says Rajaram.

On Facebook, each user can be turned into an ad network. Sponsored stories are first distributed to users who have chosen to be fans of an advertiser’s Facebook page. If a fan then likes the ad (often consisting of a coupon or other discount) in a sponsored story, it’s distributed to that fan’s network of friends, whether they liked the advertiser’s page or not. “We’re finding that more than 50 percent of all claims of offers come from friends of fans, not fans,” says Rajaram, adding that Facebook’s research showed people recalled an ad referred by a friend 10 times more often than a typical display ad.

Twitter is also pursuing a native-advertising strategy, in the form of promoted tweets, but custom formats for Facebook and Twitter will not work for the larger world of the Web, meaning that the magic formula for mobile advertising remains elusive—especially for sites that have fewer visitors. “Digital advertising is about getting my message in front of a lot of people at a low cost,” says Rare Crowds’ Picard. “The more we carve up that inventory, the harder it is to get that message out.” Facebook can do sponsored stories, he says, because it has such a large audience. “But not everybody’s Facebook.”

The bottom line: Traditional advertising doesn’t translate to mobile devices, and companies are still struggling to come up with effective strategies.


Global Social Media Usage

5 Nov
Though the social media revolution has seemingly conquered the world, there is a broad range of global usage from country to country and channels used.
Global Social Media Usage


SMS Boom Days Are Over

1 Aug

SMS, perhaps one of the most profitable legal products ever, looks to be going the way of traditional voice, international direct dial (IDD) and other great telecom earners.

For most of the past decade the service has delivered margins of 90 percent or more for mobile operators.

Now, inevitably, it is just one more telecom service that’s being disrupted.

According to research firm Ovum Ltd. , worldwide SMS revenue grew 12 percent in 2010 and 7 percent in 2011, but predicts that growth rate will shrink to 4 percent this year and 3 percent in 2013.

Other statistics suggest the decline may be even sharper.

According to regulator Office of the Telecommunications Authority (OFTA) , the number of text messages sent in Hong Kong on Chinese New Year’s Day, usually the busiest day of the year, fell by 16 percent year-on-year to 24.5 million, the first ever decline. On Chinese New Year’s Day in 2011 the year-on-year volume increased by 3 percent and in 2010 it grew 17 percent.

Singapore Telecommunications Ltd. (SingTel) (OTC: SGTJY), the biggest Singapore operator, gave up on what used to be a revenue windfall over that holiday period and actually offered free texts.

But it’s not only Asia/Pacific that’s noticing the shift. Europeans sent fewer traditional text messages during the Christmas 2011 holidays. Finnish SMS traffic dropped 22 percent, according to statistics sourced from TeliaSonera AB (Nasdaq: TLSN) and cited by Citigroup in a report that suggests prepaid operators in Spain and Italy are especially at risk from a dip in text-related revenues during the next 12 months.

All of these trends are worrying for operators that are already having to plan for the inevitable further decline in traditional voice revenues. Text messaging is a GSM network feature that was initially overlooked by operators but has become the industry’s biggest non-voice revenue stream during the past decade.

It still accounts for the biggest share of data revenue, but that too is changing fast. The difference, of course, is mobile broadband, which is enabling alternative methods of near real-time communication via Facebook, Twitter and the use of downloadable messaging apps such as WhatsApp.

Smartphones are also eating away at SMS. Research In Motion Ltd. (RIM) (Nasdaq: RIMM; Toronto: RIM)’s free BlackBerry Messenger app has been one of its main attractions for teenagers, while Apple Inc. (Nasdaq: AAPL)’s recent launch of iMessaging may well accentuate the trend.

Clinging on to SMS
Operators contacted by Light Reading were wary about sharing either specific data or their views on the fate of the messaging market.

SingTel, a major shareholder in India’s biggest mobile operator Bharti Airtel Ltd. (Mumbai: BHARTIARTL) and a brace of other operators in south-east Asia, said SMS usage across its business was “steady.” A spokesperson acknowledged that consumers now have more messaging options, but said SMS remains popular because it is “more reliable and faster” than alternatives.

Australia’s Telstra Corp. Ltd. (ASX: TLS; NZK: TLS) said it didn’t expect the popularity of operator texting to change “in the near future.”

The fact is, almost every operator is now offering very large packages or bundles of all-you-can-eat SMS. And at the same time mobile operators need to deal with a more complex messaging environment, involving social features and multimedia.

New opportunities
One emerging opportunity, according to Ovum, is the combination of SMS and new applications. Apps such as group messaging have created a service with an IP-based interface but which “still depend on the reliable channel of SMS.”

And there’s a sweet spot for the future of SMS to be exploited, too — application-to-person (A2P). This includes information-based content such as news and sports results, along with advertising and vertical content. It currently accounts for around 16 percent of SMS traffic and is set to grow to more than 20 percent in the next two years, Ovum predicts.

But in the long term, the decline of SMS is part of the trend towards communications services becoming free bundled apps. Industry analyst Paul Budde says voice and (increasingly) SMS are being used to attract people to certain apps, “and it is within these apps that future revenues will be generated — the comms will be given free of charge as an incentive.”

Source: – Robert Clark, February 24, 2012

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