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February 05, 2014

IBM's Interactive Experience Predicts Life Events for Better Marketing Initiatives

The desire to collect information for marketing purposes is not a new concept. Businesses thrive on this to ensure they are selling the right products at the right time to their customers. The science of the intersection of data and human behavior has certainly come a long way, thanks to technology, and IBM’s next big thing is to help companies harness this power and predict life-events, thanks to information supplied by your social media profiles like Twitter.

This new consulting practice called IBM Interactive Experience comes from its legendary research labs to inform design, customer interaction, and business decisions. It will use emerging techniques from the labs designed to help them personalize offers to their customers, including life event detection, behavioral pricing, and psycholinguistic analytics, which combines the psychology of language with social media data to understand inherent personality traits of individuals and identify their preferences.

"Our clients understand that the experience any individual has with their brands, products, services or strategy is the new point of entry to sustainable business relationships," said Bridget van Kralingen, Senior Vice President of IBM Global Business Services, in a keynote speech to leading technology and business executives. "That experience will generate the most valuable information any enterprise can ever possess -- information on individual preferences. So as our clients' front-office agendas drive the next era of business transformation, we're going to see traditional distinctions between strategy, analytic applications, and the design of the individual experience, disappear."

The tools are reminiscent of similar computer research from IBM we know as Watson. Watson is a computer that understands human language, and by simply looking at the language used when posting on social media sites, it can understand your personality and even predict major events likely to happen in your life.

As Fast Co. Design's John Brownlee writes: "It can even predict major life-events: if you changed your Facebook status to "Married" a year ago, for example, a company might infer that it was about time to start approaching you about products and services for your first child."

Of course, on the business side of things, this can be good news, as the practice will help clients create the essential front-end, individual engagement, assimilate massive volumes of data, then convert that insight into high-value outcomes ranging from personalization to business model redesign.

For the consumer end of it, it could be construed as encroaching a bit too much on personal digital life.

It reminds me of the time when, after almost a year after my second child’s birth, how Pampers sent me an e-mail with a checklist to help me prepare for “the big event.” I’m not sure how Pampers missed the mark entirely, as I had already brought two wonderful babies into this world and was already in the thick of toddlerhood. Perhaps its analytics weren’t able to properly track my spending habits, or perhaps it had been sometime since I had downloaded its app on fetal development. The flaws were likely inherent on both sides, but admittedly, it was a little creepy, not to mention that ship had already sailed. It would have been better had Pampers prepared me for the next big event known as potty training, and sent me some coupons for the training pants to get us through the experience.

But IBM’s initiatives show promise for those who will implement it, and maybe its left event detection technology will yield better results. The only downside to these technologies is, say you have a married couple trying for a family but are having issues doing so, to have a company send out baby marketing and trying-to-conceive product coupons might send customers in the wrong direction.

If it can successfully help companies send out coupons for things customer want before they even know they want them, then more power to them.

Edited by Ryan Sartor

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