Data Monetisation – A Poisoned Chalice For Carriers?


The idea that the data flowing across a communication service providers (CSP) network could hold intrinsic value is nothing new. The principles of infonomics, that information should be accounted for with the same formality as traditional assets was first proposed in the late 90’s by Doug Laney, vice president and distinguished analyst at Gartner.

Traditionally CSPs made their money by providing a service; voice, SMS and some VAS. The actual content or context of the service didn’t matter, it was the provision of the service that was the focus. Since 2007 and the launch of the first iPhone this focus has been shifting. The veritable deluge of data flooding mobile networks globally following the move to 3G and the launch of the iPhone has meant that the content and context of the service is potentially much more value than the service itself.

This realisation has had CSPs globally literally salivating at the untapped information asset at their finger tips and the potential external data market speculatively worth billions of dollars a year just at a time when traditional CSP revenues were in decline.

The state will eventually have total control over you without you even knowing it…

The early forays into data monetisation in 2012-2013 were led by the large carriers in the US. AT&T, Sprint and Verizon all invested heavily in data monetisation plays with AT&T launching AdWorks, Sprint, Insight Media+ and Verizon, Precision Market Insights. In Europe, Telefonica also introduced Dynamic Insights in 2012.

These early monetisation attempts, monetisation 1.0 if you will, started with much fanfare and promise only to see those hopes dashed in 2013 with the first revelations from Edward Snowden. The public became all too aware of not only the governments snooping but also the collusion of the technology and communications companies with the government providing unfettered access to our personal and daily digital lives.

…if you are really worried about being tracked, don’t use a phone at all…

Following the Snowden revelations, AT&T and Verizon were hit with consumer outrage over their ‘cookies’ and the fact that consumers were unable to opt-out of their tracking programs. Verizon and AT&T after some false starts both had to allow consumers the choice of opting out with the FCC investigating Verizon over a potential breach of consumer privacy laws.

These stumbling blocks, along with increasingly complex privacy legislation in Europe led to a number of carriers pulling back from direct monetisation. AT&T shuttered the mobile division of AdWorks for example while Verizon and Sprint both started concentrating on getting their subscribers to opt-in through rewards programs and VAS offerings.

The difficulty in identifying a quid pro quo that successfully incentivises a subscriber to share information about their likes, interests, location and behaviours has led to what I like to call monetisation 2.0, the anonymised, aggregated demographic systems we’ve seen from the likes of Telefonica, Teralytics, DataSpark and SAP.

My data (and that of everyone else) is my property and making profit from it should be illegal without my express permission.

What could a consumer possibly have against being included in an anonymised, aggregated data set one could ask? There’s no way, or no easy way at least, to identify individuals from aggregate data sets, no personal information is shared, no DPI recording your web browsing habits. Only aggregated demographic and location data used to identify travel patterns, how far people travel to get to a certain location, popular times of day, traffic congestion etc.

The unfortunate fact is that consumers don’t like to be tracked at all. In a recent 2015 survey 82% of consumers siao they didn’t want to share any location information with brands. The Symantec State of Privacy report last year found that 70% of consumers believed their data was already being sold to third parties and a whooping 74% felt that it is unfair that companies are making money from their personal data.

The recent news that Everything Everywhere in the UK had partnered with Royal Parks to track visitors to Hyde Park is a great example. The aggregate, anonymised and four-week delayed data was used to inform Royal Parks about visitor numbers displayed on a heat map and the percentage to have visited from different boroughs, towns and cities. Certainly a worthy cause but a look through the comments section should be enough to give any CSP considering this pause for thought. The ‘easy money’ promised by data monetisation is in reality an incredibly complex and delicate balancing act.

If a company wants to watch and monetize that watching, they should pay the person they are watching after getting permission to do so.

“using my data without paying me and without asking my permission, anonymous or not”, “you pay to use their service, they are paid for the data you create”, “My data (and that of everyone else) is my property and making profit from it should be illegal without my express permission” are just some of the 600+ comments this story generated.

Aside from the privacy concerns which might be alleviated through consumer education there is a consistent thread highlighting the perceived unfairness of the deal. The quid pro quo is seen as being heavily weighted against the consumer. It’s too early to see exactly how privacy concerns might impact a carriers bottom line through churn or fines for privacy breaches but the potential damage to the brand should be carefully weighed before any monetisation project is undertaken.

Rewarding consumers for giving away their privacy certainly isn’t a new idea and we’ve seen with variable success this tried with many carriers. From AT&T’s $29 privacy “tax” on their fiber, $139 or $110 if you allow them to snoop on your surfing, to Verizon’s Smart Rewards but perhaps the future lies in allowing consumers to choose when and where and what they want to share and to reward them accordingly.

Until then navigating the mine field of data monetisation will remain a tricky balancing act where building a solution that lives up the hype is increasingly difficult.

About This Author

Big Data and Python geek. Writes an eclectic mix of news from the world of Big Data and Telecommunications interspersed with articles on Python, Hadoop, E-Commerce and my continual attempts to learn Russian!

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