Mobile Data: What’s Real, what’s Myth and what’s total BS? — A (discussion-oriented) Tutorial
Unlike any consumer accoutrement in history, the mobile smart-device continuously emits data about its user, offering the tantalizing possibility of using that data to affect and measure the outcomes of marketing and advertising campaigns. Every mobile marketing technology vendor, including ad networks, DSPs and SSPs, claims to have created “artifacts” based on this data and uses these artifacts as the major differentiator of its offering with respect to competitors. Without doubt, the use of “data” has been a key, perhaps the most important motivator, of the rapid rise of the mobile marketing channel.
Yet, the “data artifacts” that are so touted by so many, lie behind the well-known (and much opaque) vendor-shroud. In virtually every marketing channel, the existence of independent data and analytics providers is the norm. For instance, in traditional digital, (e.g., email or desktop) marketing, independent data vendors (such as Oracle/BlueKai, Acxiom, Neustar, Comscore) are important players in the ecosystem, offering audience segments and online-offline matching services to marketers — 95% of desktop marketers are plugged into the Bluekai audience marketplace for instance.
In mobile, the situation is much different. Data is behind 1st party vendor-shroud (which makes this data suspect) and little to no independent data exists. As an example consider the following dichotomy: Bluekai, the world’s largest digital audience platform, makes nearly every desktop in North America addressable through its marketplace, but has virtually zero addressability into mobile devices (anywhere in the globe). Whatever little audience they offer in mobile (and they offer none in Asia) are based on their desktop taxonomy and are based on statistical IDs, which tend to be precision-challenged. In-spite of the much touted value of mobile data, there is effectively almost no availability of data and analytics for general purpose use in mobile marketing, at scale, globally in general, and for sure in Asia in particular.
And there is good reason for this — it turns out that while there is (perhaps too much) availability of raw signals from mobile devices, the scale and noise in these signals makes it VERY hard to produce anything practically useful from it.
In this context, this (discussion driven) tutorial will address the following issues:
1. What is mobile data? What are the common signals that can be captured and analyzed? Why is it so hard to produce meaningful artifacts from these?
2. What are the most common uses of digital data? Turns out there are two canonical uses — audience segmentation and “online-offline” matching to address problems like Showrooming and Webrooming — how do these apply to mobile?
3. What is the “real” start of the art on mobile data availability?
4. What can marketers do, particularly in Asia, to ascertain what really is available behind the “vendor-shrouds” and to access real 3rd party data?
The discussion leader, Anindya Datta, is an ex-faculty at Georgia Tech and the National University of Singapore. His academic research, and subsequently the manifestation of this work in his multiple commercial ventures (now resident in Cisco and other large acquirers), make core contributions to the state of the art in large scale data management. He looks forward to sharing his learning in the space, and in turn, learn, from the audience.