Customer Experience Predictions 2019: Part 3

[24]7.ai | January 21, 2019

Think about the last time you Googled something, and Google wasn’t able to successfully autocomplete what you were searching – did you feel a little annoyed you actually had to type out your entire query?

If you did, you’re not alone. Technology has definitely made life easier for us, but in the process, it’s made us all a little more impatient. We have much higher expectations when interacting with technology today than we did a few years ago, and are easily annoyed when things don’t work the way we expect them to. 

These expectations have trickled into our online interactions with businesses and have created new challenges for companies who are struggling to understand who their customers are and what they want, so they can deliver the perfect experience in the moment it matters. 

What many companies don’t know is the secret to success is simple: by embracing the right technology, you can learn a lot about your customers, and deliver personalized, predictive experiences that will keep them happy – and coming back. Wondering what you need to get started? 

This brings us to our next customer experience prediction for 2019.

CX Prediction Part 3: Predictive Analytics in Customer Experiences 

In the past, customer experiences have typically been reactive. Companies would respond to customers after an incident or problem occurred and attempt to resolve things or undo any damage that was done. In 2019, we’re going to start seeing AI-driven insights and predictive analytics being used to help companies turn things around and proactively act on interactions, rather than being reactive. Click to Tweet

86% of buyers will pay more for a better brand experience, but only 1% feel that vendors consistently meet expectations
— Oracle

How Can Technology Help?

Companies already have vast amounts of customer data, most just don’t know what to do with it. 
Using AI and predictive analytics, you can compile hundreds of thousands of your customer data points, analyze, and act on them in milliseconds. 

From the moment a customer gets on your website, you’ll know: 

  • Who they are (age, gender, education)
  • What pages they’ve visited before
  • What products they’re most likely interested in based on socio economic factors
  • Their past purchase/chat/interaction history and how that might be relevant to their current needs

All of this information can then be used to personalize their experience in the moment (e.g. show them products they’re mostly likely interested in right now), anticipate what they’ll do next, or what type of conversation they might have with a chatbot or customer service agent, so you can make individualized, relevant recommendations. 

For example – Greg recently purchased a new smartphone from Shop Electronics. A few days later he’s back on their website. Shop Electronics knows who he is, his previous purchase history, and sees he’s now browsing phone cases. Using AI and predictive analytics, their chatbot proactively engages Greg, saying, “Hi Greg. We hope you’re enjoying your new phone. Can we help you find the perfect phone case for it?” 

With the click of a button, Greg is shown a range of cases that will fit his new phone perfectly. 

Instead of autocompleting Greg’s Google search, the company is essentially autocompleting his experience in a way that shows they care.

The expectation of consumers today is that everything exists in the world of the now and that their interactions will be personalized
— McKinsey & Company

Why does this matter?

Think about the relationships in your life – what you know about people changes the way you interact with them. You wouldn’t talk about last night’s football game with a friend who hates sports – why should interactions with companies be any different? 

You have more than enough data to tell you who your customers are and what they want – it’s time to start using it. Technology makes it easy. As expectations continue to rise, customers are going to demand that you show them you know who they are and won’t tolerate impersonal, disjointed experiences. In other words, if you continue to talk football with a customer who hates sports, in 2019, they’re going to take their business elsewhere. 

Learn more about how to use AI to transform your customer experience in our eBook, plus find out what else is in store for customer experience in 2019 in Part 1 and Part 2 of this series.