This article originally appeared in the Dec. 2012 issue of Next Gen Mobility Magazine.
The notion of personalization is hardly a new concept. Originally a core attribute of the big Internet, it embodied the use of context, for the purpose of tailoring content to individuals. Conduct a web search on a new guitar, see online advertisements for guitars on subsequent searches, as one of dozens of examples.
But the big Internet is no longer confined to fixed networks, and innovation around personalization is as or more pervasive as in wireless networks. Personalization is evolving to mean the blending of context with location, so as to tailor content to specific individuals.
We call this mobile personalization phenomenon data in motion, meaning information that’s intrinsic and exclusive to mobile service providers. It may consider device type, user, current location (to within a foot), signal type, signal strength.
In most cases, mobile data is constantly variable, because it’s as on-the-move as the mobile device it characterizes. And the more on-the-move that data is, the more likely it is that it falls within the exclusive domain of the mobile service provider. If not abused or done in a creepy way – which is critical – does Guitar Center benefit by knowing you just walked in the door? Yes. Do you? Almost certainly.
Call it mobile analytics, call it monetization, and call it the next flavor of big data – mobile personalization is fast becoming the new normal.
The New Normal
As mobile service providers race to keep network capacity ahead of surging demand for devices, apps, and ultimately bandwidth, they’re simultaneously pressured to find new ways to monetize the expansion.
Submitting a capital budget for gear needed to keep up with 40-50 percent compound annual growth in usage, without revenue to offset it, makes for a bad day at the office.
That’s where the unique nature of data in motion comes into play.
What the Network Knows
Not long ago, a service provider executive asked me to pinpoint how much latent value is riding on his network. It gave me pause. The notion of big data is not new, as a way to perform analytics that monetize various business situations – who’s watching what, so as to attract advertisers; who’s searching for what, so as to link them to what they seek.
This is where the notion of the data in motion emerges, in a big way. It’s about tapping into the intelligence that is both latent and legion, inside the network. Today’s big data analytics players predominantly act on static information, present in data warehouses and data centers. Predictions, based on that static data, become the currency of offers and advertisements.
That is fine, but data in motion can do this faster, and better. The notion of dynamic or near-real-time analytics is what’s different, faster, and better than static analytics, as a way to map to contextually-relevant awareness, in real time.
So the answer to the question of latent value riding on mobile networks starts with knowing what you know, which breaks down into explicit and implicit categories.
In a mobile sense, then, service providers explicitly know the following things: identity (who a person is); location, often within a foot of actual location; what kind of network people are on (Wi-Fi, 3G, 4G); what kind of bandwidth they have; and whether they’re indoors or outdoors.
Implicitly, the network knows context – recent searches, recent maps. All of this data is held anonymously in the network. No other entity in the mobile ecosystem is poised to know as much, or as quickly. This is important to potential service discovery, and monetization.
Use cases abound. We’ll highlight three here: courtesy bandwidth, hyper-localized couponing, and machine-to-machine brokering.
If it’s a given that service providers will ultimately shift to usage-based pricing, so as to deal with the fact that mobile devices now contain video cameras and Internet connections, then it’s also a given that mobile consumers will begin paying more attention to usage.
Consider the case of Mike, who’s on the road with his tablet. He wants to watch Spiderman. Behind the scenes, his mobile service provider senses this and sets up a priority quality of service treatment on its 4G network. As the movie starts to play, he’s alerted: “Mike, the bandwidth for this viewing comes to you courtesy of Acme Video,” or another advertiser/sponsor.
Maybe Mike’s hotel offers Wi-Fi for $14.95 a day. He’s resentful of the fee, but is facing a night on the laptop, creating and moving big files. Within the available SSIDs on his laptop: Small-cell access to an alternate Wi-Fi provider, which charges less – or better yet, a toll-free offer, courtesy of – again, pick an advertiser, pick a sponsor.
Call it courtesy bandwidth, call it 1800-data, call it zero rating – one way to sidestep data overages is to extract usage behaviors, such that consumers don’t go over usage caps, because other interested businesses are subsidizing them.
Another example is the collective work to date on HotSpot 2.0, which in essence enables automatic roaming across data networks: Making login credentials transfer automatically, across service provider boundaries, so that people and their devices can move without having to receive a refreshed IP address, request for profile information, or login multiple times, as they move.
HotSpot 2.0 works in the background, transferring user credentials as needed between service provider participants.
As our colleagues at Shaw Communications (News - Alert) put it, when they embarked on HotSpot 2.0 – it’s how they’d build for mobile broadband, if they could wave a wand and fix all the things that were and are clumsy on existing Wi-Fi hotspots.
It’s a fact that most smartphones contain or will contain silicon that can pinpoint their own exact location, to within a foot. That brings us back to the web search for the guitar – implicit data, in personalization terms. Upon entering the guitar store, Mike checks his phone for any in-store offers.
Obviously, it’s of value to any retailer to know that a serious buyer is in the store, right now. How this information is handled will be a make-or-break endeavor. Done incorrectly (too obviously; too pushy), hyperlocalization is surely a non-starter. Done correctly, though, it’s a plausible example of business-to-business monetization that benefits all parties – the consumer, the mobile provider, and the retailer.
Only the network knows that Mike just walked into the store (explicit info); only the network knows that Mike recently searched for guitars (implicit info). With proper attention to privacy, this mix of explicit and implicit information is enormously useful to retailers (Mike needs a new guitar and we have plenty), and to Mike (I want the best possible deal).
Mobility, network intelligence and a solid packet core open up new ways to drive loyalty, promotions, and foot traffic at destination locations – meaning wherever people are, with their mobile Internet connections.
Monetizing M2M and the Internet of Things
A third example of data in motion as a monetization engine involves the burgeoning field of machine-to-machine computing, as a way to keep the Internet of things connected and maintained. This involves small sensors, outfitted with IP connections, which can be polled and acted upon, as needed.
Health care is a plausible beneficiary (among many) of mobile personalization. Already, prescription bottles are in the works that contain M2M sensors within the lid. When a life-critical medication gets down to a five-day supply, the sensor alerts the pharmacy to refill the prescription, and notify the consumer.
Right now, the M2M marketplace is still fairly nascent – utility companies, large shipping companies, and other organizations resourced to handle the large volumes of sensors that define M2M computing. But with scale economics and the right cost structure, contextual mapping of M2M, combined with location data, stands as a plausible monetization example for service providers.
Personalization Is (Very) Good for Service Providers
Personalization, and the potential monetization of contextual awareness, is wonderfully disruptive. There’s the disruption in the access network, around the consumer experience relative to how to address bottlenecks, with small cells and seamless handoffs and how to enable courtesy bandwidth, which benefits consumers and advertisers/sponsors.
And, there’s disruption in the data in motion domain, and how the mobile Internet will create value with real-time, context-aware computing that better targets and optimizes content, around consumer behavior: hyperlocalization; M2M computing.
This double disruption is great for service providers, because only they know this level of explicit and implicit data. It’s a growth engine, because it solves the riddle of how best to service consumers, without reaching into their wallets (again).
And this is just the beginning. Personalization is essentially in its infancy, particularly on mobile networks. It’s just beginning to unfold. It will create value, and it will increase consumer loyalty to their mobile providers. As mobile network people, this is ours to win.
Murali Nemani is senior director or mobility services marketing at Cisco (News - Alert) (www.cisco.com).
Edited by Brooke Neuman