| | December 20179CIOReviewSocial media is a great place to identify local events that have received sudden spikes of attention, and the events themselves may mean a lot to the businessforefront. Back in 2012, a few food production companies saw a lot of posts, comments, and views directed toward going `back to the basics'--a rising interest toward all-natural food. They made deliberate moves to hedge up against that kind of a swell in demand. As AI/ML advances, a good neural net, reverse imaging classification algorithm, the next `hot' diet or the next popular food can be identified based on what people are clicking pictures of, liking and posting on Instagram.It's amazing how far we've gotten in terms of intellectual curiosity. Nevertheless, the scenario where the output of intelligent systems can be translated directly to an operational input is still evolving. A few years back, during my time at Sears Holdings, I worked with KickFactory in helping to identify and engage potential appliance customers on Twitter. In our test phase one of its detected tweets read: "Need a new refrigerator. Uncle Jeb just died! #redneckfuneral." The AI was ready to respond to what was obviously a joke. The platform was technically not wrong in detecting the tweet, but it didn't understand the humor either! KickFactory utilizes a hybrid approach because of this, where the machine is taught certain contextual and textual nuances by humans until a time where it can `think' in a humanized way.Surveys are showing a growing willingness by consumers to engage with AI and Machine Learning platforms, but if you're not delivering value with them, they're just toys. Passing the Turing Test is not enough anymore: just like when interacting with an in store associate, a personalized, empathetic interaction that delivers a value, monetary or not, is what consumers are looking for. Consumers are even willing to allow companies more discrete access to their private data that only a few years ago no one would've imagined them willing to disclose. Look at the adoption of smart home devices with microphones, fitness trackers, location data, etc... all being shared either socially or with companies because they bring value. Combining this, while of course adhering to any 3rd party platforms policies and government regulations, companies have a great opportunity to not only detect but influence demand signals as they emerge. Prepping for the FutureCompanies need to remain flexible, not only do the social media platforms de jure change, platforms relevant to one company's customers may be different than another's. Reading and influencing demand will continue to evolve, and it is an exciting space, but there's opportunity for companies internally as well. As average employee tenure decreases and the workforce evolves, knowledge of a specific category or market segment becomes less enduring, but this presents an opportunity thru good master data combined with its history for AI and Machine Learning to deliver the insights that used to take years of experience to gain and play a role in influencing strategic decisions. What are the important holidays, product colors, geographic idiosyncrasies, etc... These are questions that AI and Machine Learning can answer and deliver to buying and planning teams, whether they're in their first week or have been in the business for 20 years. My background in virtue epistemology (a branch of philosophy) has taught me that humans are creatures of habit, and retail has taught me, so are consumers. While philosophy has taught me to play `Sherlock' around the most significant questions in life, at Claire's Inc., I play Sherlock around the ever-evolving habits and demands of the consumer. My job is knowing my consumer--a young girl or woman, who may not always be the one with the wallet, but is potentially relying on her parent or friend to get her around or make purchases. When assisted with the growth and developments in technology and social media, it is undeniably a quickly growing world of possibilities and we're still part of the wave of first explorers.
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