Marketing & Technology

Widespread consumer adoption of mobile and social media innovations is an exciting development in 21st century marketing. Myriad new communication and transaction vehicles, capabilities, and app features, layered on top of an already fast-growing internet, have made the role of the marketer much more interesting than ever. At the same time, they’ve made the job substantially more complex. Consider these fun facts: 90% of the world’s data was created in the last two years; 80% of the world’s data today is unstructured; and 1 trillion connected devices generate 2.5 quintillion bytes of data per day. A substantial portion of these data is generated by consumers themselves, providing a honey hole for marketers to explore and surface new insights for capturing growth in sales, market share and ROI.

Two types of data are especially interesting to marketers because of their power and scale: unstructured data and sensor data. Unstructured data is just as it sounds—these data do not automatically fit neatly into data tables marketers can query the way they do with a typical customer master data file. And there is typically a lot of noise in the data that needs to be culled out. Examples of unstructured data include speech, such as that recorded from call center conversations, text captured from product reviews, tweets, blogs, and social media posts, and video or images from sources like YouTube, Instagram and Pinterest. These data contain a wealth of insights, but the pressure is on marketers to tease out the information that matters most and then act on it in a profitable manner.

Sensor data are also interesting. Mobile devices and internet usage make it easy for customers to check- in or be tracked (primarily when they opt in to apps with location tracking functionality). This opens up a new world of geospatial and temporal data that marketers can harness to formulate an understanding of an individual customer’s context at a point in time—such as by day of week and even hour of day at a specific location, right down to a specific fixture inside a particular store on a rainy day. These data become understood by applying contextual analytics methods which, in turn, pave the way for marketers to deliver true personalization of the type that engenders customer loyalty, trust, and lifetime value. Once context is understood, marketers can interact with their customers in new and innovative ways using more relevant messages and offers to drive improved response, conversion and value.

The sheer volume of data and the struggle to organize it underscores the need for new technologies and analytical approaches, along with new analytical skills for marketers and data scientists. At IBM, we are developing new technologies and advanced analytics that help marketing scientists, and all marketers for that matter, analyze and use these varied sources of data. We are focused on helping marketers gain improved understanding of their customers in context, advance their ability to explore and continually learn more about their customers, predict and model potential outcomes and optimize investments. And we are partnered with The Ohio State University’s Fisher School of Business to help build a new curriculum for the study of advanced analytics. With the access to technology, tools and training, today’s marketers are in a better position than ever to understand their customers and unlock and capture new business opportunities.

Kim Hendrix

Innovation Strategist, Retail Analytics | IBM Research

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