Recently, I was reading a conclusions paper created from an American Marketing Association webinar about mobile marketing featuring Brian Vellmure of Innovantage and John Balla of SAS. As I was reading, one line stuck out to me on the first page of the paper: “The key to making sense of mobile is analytics.” I thought that was a very simple, bold statement that was very much to the point.
That statement led to the next logical question, which is, “How?” How are mobile analytics being handled today in organizations? What are their maturity levels and opinions on mobile analytics? Vellmure and Balla answer that question and even provide analytical- and optimization-based suggestions for solving mobile analytics challenges.
Their starting point is to describe the current mobile environment, beginning with mobile in the workplace indicators. Did you know that 37% of corporate employees in a recent study are using mobile for more than 60 minutes a day? Similarly, 70% of respondents to an in-webinar survey claimed mobile is either “Very Important” or “Important” to their organization.
These stats illustrate the fact that humans, whether in a personal or professional setting, are device dependent. This should come as no surprise, but Vellmure goes on to summarize the main uses of mobile in a few key phrases that I really liked. First, he noted that mobile is now our “primary gateway to communication, commerce, and sharing.” Secondly, he compared mobile to a “human sensor,” telling those with access to our data “who we are, what we’re doing, and where we’re going.”
Later, we learn a bit about how users engage with mobile devices, including the concept of “no-mo-phobia,” or the anxiety and withdrawal that one experiences when not having their device at hand. The struggle is quite real, since I've personally sensed anxiety over the misplacement of my device. This anxiety is likely due to the fact that we as consumers know that our devices now encompass so many interaction channels and provide the “digital interface” to our lives. Whether you use it for the Web, social media, text messages, or simply to make phone calls, the mobile device today is a prime facilitator of interactions between consumers and brands.
Take, for instance, the product purchase process. Transactions can now be done completely from the mobile device. With the exception of the occasional “showroomer,” the process of researching, price comparing, and purchasing is all being done online, accounting for billions of dollars of spend annually.
As time progresses, organizations will need to become more and more adept at handling the consumer entirely from a digital perspective – potentially never having a person-to-person interaction. Organizations are certainly aware of the importance of having a presence across digital channels, as we have seen mobile advertising spend continually increase year over year – one projection forecast U.S. mobile ad spending at over $11 billion in 2014 alone. But how do brands continually improve when and where they are advertising, to whom and across what combination of digital media? How do they deliver a consistent message as consumers move seamlessly between digital marketing channels? How do brands use responses from customer interactions to refine their digital marketing messages over time?
The key to making sense of mobile is analytics.
Let’s consider the concept of “showrooming” - a real problem today for brick-and-mortar retailers. When showrooming, a consumer goes into their local big box store, tries a product, price compares (sometimes while in the store), and makes the purchase online for a better price. How could a brand overcome this issue?
Well, what if the store put a GPS based “geo-fence” around its store, allowing them to know exactly when a mobile-enabled consumer entered the confines of the store? What if, using advertising technologies, a mobile offer could be sent to the device when inside of the store for the exact product that is being “showroomed?” What if, when a consumer accepts or declines this offer, a subsequent action could be taken, such as sending a more appealing offer – all delivered at the individual consumer level? And what if all of this could be optimized, as to ensure that the consumer never receives a repetitive offer and always receives the offer at the optimal time, place in the store, and channel (perhaps they prefer an offer in the store’s mobile app versus over a social network)?
With technologies from SAS, all of this can be done. It’s not as far off as it seems, as SAS is already working with organizations, many well-known, to put this exact use case into action. If you and your organization want to enable better interactions over the mobile channel with your consumers, take a look at what SAS can provide today.
Start by downloading the paper, Leveraging Analytics for Mobile Marketing. After reading the paper, take a look at our Customer Intelligence web pages and then contact us. I promise we can help you make sense of mobile.
