Using Machine Learning to Enhance the Customer Experience

By Terry Myers, HPC Global Market Manager, Hewlett Packard Enterprise

May 16, 2016

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.

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.

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.

Machine learning technologies have a strong foothold in the future of customer interactions in the Digital Age. According to research from IDC, applications incorporating advanced and predictive analytics, including machine learning, will grow 65% faster than apps without predictive functionality. The same report estimated that by 2018 half of all consumers will interact with services based on cognitive computing on a regular basis.

The undeniable incentives for using Big Data insights to improve the customer experience don’t mean there aren’t also significant challenges. As with so many other issues surrounding Big Data, the sheer volume of customer information collected on a daily basis can be daunting, and it all must be mined and analyzed quickly in order to extract useful insight. Additionally, customer data from multiple structured and unstructured sources must be integrated in order to provide a full view of the customer, including data from web analytics, CRM systems, customer feedback channels, and social media platforms.

However, solving these challenges means businesses across a wide range of industries can leverage machine learning techniques to provide exceptional customer experiences. Here are just a few examples of innovative machine learning applications in use today:

  • Tracking and maintaining customer profile data helps organizations like banks and investment firms offer financial products or services that might be of interest to the customer based on recent life events.
  • Media and entertainment sites such as Netflix use sophisticated algorithms to analyze viewing history and present personalized content recommendations.
  • Hospitals use machine learning models which incorporate factors like staffing levels, patient data, department charts, and ER layout to predict emergency room wait times.
  • Contact centers improve customer interactions by using machine learning techniques to route incoming calls to the right representative more quickly, helping to reduce call durations and increase the incidence of first-call resolutions.

Once viewed as high-level, complicated data science, machine learning platforms are now widely available which provide proven tools to help the mainstream developer community build data-rich applications. The proliferation of these tools means businesses in all industries can transform to more customer-centric and personalized models, and enrich the customer experience like never before.

Machine learning is an exciting prospect for businesses given its potential for improving customer satisfaction, streamlining processes, and driving business growth. And to think, we’ve only begun to scratch the surface.

To learn more about the advantages of machine learning, I invite you to follow me on Twitter at @TMyers_HPE.

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