How AI and machine learning will impact the future of customer experience
Fri 16 Mar 2018 | Ronald van Loon
Ronald van Loon, ahead of his keynote presentation at Big Data World 2018, writes on why CX leaders are turning to new developments in AI and machine learning as opportunities to advance their customer strategies
Automated intelligent technologies like AI and machine earning are enabling businesses to deliver more relevant, personalized customer experiences through responsive technologies, like chatbots, and recommendations and services that streamline purchasing. Businesses can also deploy machine learning to tailor the marketing experience per user.
Natural Language Recognition is also helping businesses better understand the needs of their clients and automates processes for customers who call in for service or support.
These technologies are supporting and improving vital business functions that put customer experience at the forefront of business concerns, and enhance the ability to provide customized recommendations through insights into customer behaviors, preferences, and activities.
Improving engagement and experience
Businesses are able to become customer-centric by exploiting intelligent apps and utilizing Big Data and Analytics tools to refine products and services and improve customer interactions and personalization.
For example, machine learning can perform tasks that we’re unable to do, such as searching through millions of databases quickly, or analyzing huge amounts of data within text, audio, and images.
Businesses are also able to assess risks and opportunities and forecast potential outcomes and evaluate the likelihood of future events.
AI and machine learning automate repetitive tasks, and enhance human capabilities, increase productivity and efficiency, and create more immersive, interactive experiences between technology and humans.
Deploying a combination of automated intelligence through AI, machine learning, and IoT can really change behaviors
In some cases AI applications are unique, such as DataRPM, which utilizes machine learning for cognitive anomaly detection per type of asset and machine in IIoT. Other forms of AI, like speech recognition, have broader applications across diverse areas but still need to be trained in specific domains.
For example, speech recognition is used in the travel and hotel services industry to automate customer service for guests, and in self-monitored security systems to assess potential break-ins or emergencies. Ultimately, each solution is tailored for a business case for best outcomes.
Starting the journey into AI
Organizations need to start with a data and analytics infrastructure that supports automated technologies. This includes a solid data management foundation with the right data collection, governance, quality, and security so that insights can be shared across teams and departments. Then businesses can move step by step in data and analytics maturity towards predicting and prescribing.
Deploying a combination of automated intelligence through AI, machine learning, and IoT can really change behaviors and enable businesses to benefit from a live digital environment that’s enhanced by automation.
Innovations across all industries and sectors, such as Smart Cities, Smart Homes, Smart Agriculture, and Predictive Maintenance in Industrial and Manufacturing, are driving businesses to deploy sophisticated intelligent technologies to transform every facet of our daily lives.
These technologies will improve efficiency and increase the value of customer-based products and services. It also provides the capabilities for organizations to tap into the massive quantities of streaming data from so many different sources and devices.
Ronald van Loon will be speaking at the forthcoming Big Data World London, which takes place on 21st and 22nd March 2018 at London’s ExCeL Centre. To hear from Ronald and other Big Data experts from around the world, register today for your FREE ticket.
Tags:AI Big Data feature machine learning
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