The Effectiveness and Future of Mobile Analytics
How does one measure the effectiveness of an advertising strategy that has no fixed location, but that relies primarily on the response of individual targets? Mobile marketing, a strategy which allows advertisers to send out text messages or alternatively develop applications for use on mobile devices, is measured by what is known as mobile analytics. According to studies conducted over the last ten years, mobile marketing can dramatically increase the impact of any given ad campaign in terms of what is known as ‘user engagement.’ Specifically, applications, or ‘apps’ as they are known, attract users who are interested in a particular product or service, and keep them engaged by periodically offering them relevant updates or information. But what is the future of mobile marketing? Has it already hit its prime, or is there room for development that will come to redefine the relationship between ‘customers’ and ‘businesses’?
Effectiveness
A recent news event confirms the effectiveness of mobile marketing. The event involves Nokia, a once-powerful telecommunications company that has been struggling to regain market share against its competitors the iPhone and the Android. Nokia announced that is purchasing the Mobile Analytics company Motally, which has spent years developing highly refined techniques of tracking customer interaction and response to mobile apps. Motally’s data takes into consideration the device that the user has to access the data, the content the user accesses, the location from which they access it, and the total amount of time they spend accessing it. This type of information, coupled with demographic data that is publicly available on such applications as Facebook, provides companies with a wealth of detailed information about their visitors, including age, work history, and social connections. Nokia’s decision to purchase the company when Nokia itself is struggling indicates that the company believes that Motally’s technology will allow Nokia to aggressively re-enter the mobile device market.
Motally’s mobile analytics has an added degree of sophistication, primarily in the rapid way it is able to sort all of this data and render it to Nokia. One of the unexpected difficulties of the 21st century has not been accessibility or availability of information, but rather the ability to sort through all of the available data to produce meaningful and useful results. Mobile analytics in of itself is incredibly valuable and useful primarily because it offers companies a pre-developed metric to sort through literally thousands of gigabytes of data in a timeframe that allows them to make commercial gains.
By comparing real-time user data with demographic information, a company can predict the interests of a particular user, and send them information about upcoming products or services that they will very likely be interested in either purchasing or using. Each time the user interacts with the information that has been sent to them, they add to a larger data stream of information about them, which allows companies to target them with ever increasing accuracy. In this sense, mobile analytics is the equivalent of a personalized commercial profile, a tool which gives companies and developers incredible power.
Case Studies
The burgeoning club scene in Los Angeles, New York, and Las Vegas has discovered something about its users: they move fast. In an era when the rapid-fire communication technology of social networking sites has bestowed upon email a certain stolid formality, marketing to people under the age of 30 requires a high-impact approach. Both PACHA in New York City and the nightclub TAO in Las Vegas discovered an enormous boost in attendance and follow-up participation once they switched from flyer and email marketing to an text messaging/app-based approach. This direct engagement, which could be instantly modified depending on user response, helped both clubs create instantaneous communities of dedicated club goers.
Of course, the success of mobile marketing is not limited to night clubs. Other businesses have benefited from being able to interact with their customers, including those companies who offer services online, such as the iTunes store, or developers who create apps. In each case, the success of the marketing strategy seems to hinge on the fact that the company begins to develop a slightly more ‘personal’ relationship with its customers. In the case of the Ran Pass Liquor store in Texas, customers were clued in to discounts ahead of the official announcements, creating customer loyalty and spawning other events, which in turn drew in more customers, who signed up for the individual messaging service.
Apps, meanwhile, compete with each other for market dominance primarily by being able to offer customers the most useful and efficient methods of parsing data. With its detailed roster of data, mobile analytics is vital to the success of a given app. If an app user knows that his or her core customers are spending most of their time on one particular feature, but neglecting others entirely, he or she is able to spend the appropriate amount of labor and time in re-engineering those portions that work, and those that do not.
Geolocation
So what is the future of mobile marketing and mobile analytics? With an increasing amount of personal information now available on the internet, is there a point where the most successful mobile analytics firms will develop a formula that emphasizes speed?
Not necessarily. While information parsing is of vital importance to the technology, the “type” of information may also impact mobile analytics, and subsequently alter business practices. Geolocation, which is the technology that allows a network to pinpoint the geographical location of an individual based on his or her access signal or IP address, may dramatically reconfigure business models, and play a substantial role in how mobile analytics is used.
Perhaps the easiest way to visualize how this could occur is to imagine the stages of evolution of the internet. In the 20th century, the internet was primarily an amorphous realm, without tangible connections to a physical locale. Gradually, as more and more users began to interact with the internet, the idea of a three dimensional physical location began to gain more importance. If someone wanted to order a pizza, for example, they would need to know who sold pizza within their geographical radius, not all the pizza makers on the planet.
With the increasing emphasis on commerce, physical locality again becomes of utmost importance. In order to compete in this new era, retailers will want to advertise directly to individuals who are within their vicinity, which makes the availability of geographical data a kind of insider edge. Additionally, as users continue to build up a commercial profile of themselves by virtue of not only of the purchases they make online, but how and when they make them, retailers will want to start competing for very specific individuals who have excellent shopping ‘profiles.’ Put another way, everyone will want to track down the big spenders. Undoubtedly, mobile analytics will make advertising rates to certain individuals far more expensive than to others whose commercial profiles are not as impressive.
This gradual narrowing of focus in advertising, with an emphasis on targeting a select group of coveted individuals, will have other effects. Individual users may in fact have their device subsidized if they spend more money. If Google and Verizon manage to enact a two-tier system, the public internet will require users to pay to get in, while those individuals who use their mobile devices to make purchases and thus create detailed histories about themselves will be able to use their devices for free.
Conclusion
Mobile marketing and mobile analytics are both useful tools that promise to alter how society interacts with the internet, and with each other. By increasing the amount of accurate information about individual consumer habits, mobile analytics changes how businesses interact with their customers. Those mobile analytics companies that can parse data in the fastest and most detailed fashion will become very wealthy indeed.
By Peter Marino, Senior Partner and CMO of reelWebDesign.com, a search and social media marketing company in New York City.