[Support] Artificial Intelligence and the Future of Customer Engagement in 2018

3 minute read

January 12, 2018

[Support] Artificial Intelligence and the Future of Customer Engagement in 2018

  • In B2C environments, 56% of customers expect a business to already know who they are when they call for support. 58% want their products to self-diagnose and repair. 51% think a company should anticipate their needs and offer solutions before they contact support.
  • In B2B environments, these numbers increase significantly. 79% of customers want to be known, 73% expect self-diagnosis and 75% demand an eminently proactive service approach.

In essence, as our ability to deliver a fantastic CX grows, so will customer expectations. And as their expectations grow, so does our need to identify and apply the latest in AI to satisfy their demands. We’re in a race to the top with the finish line nowhere in sight.

Here are 5 promising ways AI technologies can be deployed to enhance customer engagement in 2018:

1. Dynamically Personalized Web UX

No two web visitors are alike, so why treat every Tom, Dick and Harry who lights upon your website exactly the same way?

Decision-making APIs like LiftIgniter are using machine learning to craft highly personalized web experiences for each user. LI alone has been able to increase click-through rates by 240%, conversion by 105% and time-on-site by 159%.

2. Individually Tailored Offers

Every marketer knows the benefit of utilizing valuable offers to drive action. Still, there are vexing questions to be asked: what do I offer, how much and when?

The folks at Optimove are helping to take the guesswork out of that process. Using machine learning, OM analyzes loads of customer data to ensure every offer is perfectly calibrated to appeal to each recipient.

3. Real-time Buyer Personas

A buyer persona is only valuable insofar as it captures the true-to-life behaviors of your target customer. The problem with current tools and methods for creating buyer personas is that they’re static—they fail to catch how customers behave in real time.

Tanjo combines machine learning with smart automation to dynamically render each buyer persona. For the marketer, dynamic personas offer a far more accurate picture of customer behavior coupled with a profound well of targeting insight.

4. Dynamic Pricing Driven by Predictive Analytics

Dynamic pricing has long benefited savvy airline ticketpricers. More recently, Amazon and Uber have caught on to the economic wisdom of dynamically adjusting pricing to meet current levels of supply and demand.

PerfectPrice uses machine learning to analyze market dynamics, anticipate customer behavior and offer actionable pricing insights, allowing marketers to deliver the right price to the right customer… every time.

5. Conversational Automated Messaging

Facebook Messenger and similar chatbot technologies have been attracting attention lately as incredibly useful tools for reaching customers. That’s great, but automated approaches to messaging often miss the boat when the bots fail to approximate real human behavior adequately.

Services like Automat claim to be reversing that trend. Using natural language processing and deep learning, they’ve created bots capable of conducting highly personalized one-on-one conversations with potential customers.

These are just a few of the companies utilizing artificial intelligence to reshape the way companies approach customer engagement. As 2018 develops, I anticipate each one to not only grow as a viable means of differentiation but to shape customer expectations even further in the direction of highly-personalized, AI-drive self-service solutions.


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Kenny S.

Written by Kenny S.

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