Driving Better Business Decisions with Social Media Research and the Internet of Things
Editor’s Note: The Internet of Things is an ever growing reality that is poised to transform the world, especially as it relates to data analytics. The increasing flows of information available from virtually every device humans use for work or leisure is fueling the “who, what, where, when & how” of data analysis and the advent of Big Data as a true solution to harness it all. My belief is that the future of MR will be focused on the “why” to provide context and insights into these unimaginably vast streams of data flowing in the world. For more on my take of how this will impact our industry check out a presentation I recently did for the Mid-Atlantic MRA:
Today’s post by Costis Kompis of DigitalMR follows similar themes, but Costis takes a more in-depth view and approaches the topic from a technologist’s perspective. It’s a great think piece that everyone involved with data-driven insights should pay attention to.
By Costis Kompis
A few weeks ago, I had the fortune to participate in the Inaugural ‘Internet of Things World Forum’ that took place in Barcelona and attended by more than 800 delegates.
The Internet of Things (IoT) entails a world where physical objects such as machines, devices or sensors behind cars, trains, utility meters, home appliances or medical devices, are seamlessly integrated into IP networks and where they can connect and communicate with users, social and environmental contexts and thus become active participants in business processes.
Having been involved in this area for almost a decade, I have to say that this forum was quite remarkable for a couple of reasons. While previously, the topic tended to attract mostly academic delegates, they only represented a tiny minority there; instead, the audience comprised predominantly of business executives from every major industry sector including manufacturing, retail, energy, transport, construction and financial services. Undoubtedly, the technology is maturing to such a level that big corporations feel that substantial revenues can be achieved from it and in the process redesign entirely new Internet services. Naturally, vendors and systems integrators are keen to provide the bits and bolts for the enabling infrastructure. Cisco Systems, who are a strategic player in the Internet of Things World Forum, expect that by 2020 there will be 50 billion connected devices; this is far bigger than what even the largest corporations can handle alone, so the importance of ecosystems should be exceedingly recognized.
Among those devices, the portion of smartphones, tablets, and PCs will continue to shrink. Wearables – the electronic systems located on the body that mediate their user and their environment – spanning from activity trackers like FitBit, Nike+ FuelBand and Jawbone Up to more advanced information devices like Google Glass and Samsung Smartgear represent a new and fast-growing form-factor for mobile devices. The first generation of connected IoT devices already influence people’s behavior and can be used to gain new insights. Clearly, the business value of the IoT is not in the hardware but the services that can be underpinned by data streams continually generated by objects and users; it is not just extra streams of data, but often entirely new ones. This data can be coupled with aggregation, processing, decision-making and information dissemination mechanisms to help businesses identify emerging developments.
Imagine the seismic shift this would have in the business world when combining it with the power of social media, which is about human connections, interactions, and stories that add valuable insights. The IoT together with social media research can provide, for example, fast-moving consumer goods companies with a precise, factual understanding of how clients behave in virtual or physical stores and then correlate their behavior with what they say online, most often by using their smartphones. At DigitalMR, we are particularly active in social media listening at the cross-section of data mining and social media. Considering that social media has no geographic boundaries, people are posting comments everywhere in a wide variety of languages; we serve corporations operating in many different countries who are therefore interested to know the sentiment of their customers’ opinions about their own brands and those of competitors.
Analyzing big data efficiently requires a coordinated approach. DigitalMR recommends combining data from different sources such as behavioral (coming from connected devices or loyalty cards), unsolicited perceptions on the web and asking questions using surveys and focus groups. Still, the IoT has the potential to open entirely new possibilities for the market research sector. Unlike conventional approaches that ask specific, highly practical questions, IoT makes it possible to understand people’s requirements by observing behavioral patterns in an indirect way. This observational method can enlighten us about the context in which customers would use a new product or a service and the meaning that these might hold in their lives. It is inevitable that privacy issues will arise, but if corporations are genuinely focused on trying to create a relationship with their customers, and the customers become or are already fans/advocates, they will then be willing to participate as a means to shape the products and services they ultimately receive.
DigitalMR have devised a software platform that supports data-intensive applications, able to handle structured as well as unstructured data. Using state of the art cloud computing, we combine the value of deterministic models with machine learning so as to automatically classify previously unseen data. This enables the discovery of true brand insights, engagement and advocacy today, with algorithms that do not have a fear of big data; on the contrary the bigger the data, the better!
The advent of the IoT is creating new ways of looking at old Market Research problems. Forward-looking businesses have the opportunity to use the resulting intelligence to make better decisions so as to optimize dynamic messaging, pricing, stock levels, store layouts, staffing and service delivery and in the process drive economic growth and improve quality of life.