by Angela Guess
Grace Peters recently wrote in HPCwire, “Thanks to machine learning, the page you see when you log-on to Amazon.com is likely very different from the one I see. Advertising, product recommendations, and special deals are all tailored to our unique customer profiles based on historical browsing trends and buying behavior. Online retailers like Amazon were among the first users of customer data collection and analysis for improving services and personalizing the shopping experience, and they’ve become so skilled some sites might even be able to predict what we will purchase before we even know what we’re looking for.”
Peters goes on, “Advancements in digital technologies have driven a paradigm shift in the way businesses interact with their customers, with touchpoints increasingly moving to digital mediums. Because of the limited opportunities to satisfy customers on a person-to-person level, machine learning is now in widespread use by a variety of modern enterprises as a way to enrich customer experiences, create more personalized and customer-centric interactions, and offer seamless omnichannel communications.”
She continues, “Machine learning goes a step beyond Big Data analytics, where machines employ advanced algorithms to autonomously adapt and learn from previous experiences, and therefore emulate the thought process behind human decision-making. In the customer experience realm, machine learning allows new data-driven customer insights to be rapidly produced and continually improved upon as new data is added to the models, with the results being used by businesses to delight customers, anticipate needs/preferences, and achieve competitive advantage.”
Photo credit: Amazon