AI isn’t coming. It’s here.
We’re seeing AI bloom everywhere throughout the customer experience – adaptive product recommendations, predictive analytics and chatbots that are intelligent, conversational, even witty.
Everyone’s getting on board. According to Statista, the total AI market is predicted to grow to over $1.5 trillion by 2030. And a recent Forrester study revealed that 84% of technical leaders feel they need to implement AI into apps to maintain a competitive advantage – with 70% agreeing that the technology has graduated out of its experimental phase and now provides meaningful business value.
So the practical AI revolution is happening. But as companies gravitate towards embedding AI tools in their customer journeys, it’s casting the good ol’ human-to-human experience in a whole new light.
Let’s look at a few ways AI is transforming the customer experience before diving into what that means for us fleshies.
Powering a slew of predictive, highly-personalized recommendations
It’s the classic urban myth of the 2020s: Tuesday, you’re talking about freezing food with your friends and Wednesday, you’re being shown suspiciously-relevant chest freezers in ads. But whether your phone is listening to you or not is becoming a moot point. Because AI now knows what you want before you want it.
Businesses can use AI engines to aggregate and crunch customer behavior data to generate super-personalized product and service recommendations. These personalization engines have been around for a while – think Amazon’s “Customers also bought” or Netflix’s “Because you watched…” – but they’re only getting more sophisticated (and more accessible for smaller businesses).
As unsettling as it can be when personalized ads are a little too accurate, when used in the customer experience, this level of personalization helps to increase conversions, build customer loyalty and create the kind of customer experience that’s increasingly in demand.
Using machine learning to improve search for customers
AI is also being used to improve upon the search bar experience.
Now on the surface, this may not have the “wow” effect as some other use cases – but connecting customers with the resources, products or services that they need is no small function.
One way that AI enhances the search function is by offering an AI-powered search experience that’s personalized for each customer. By crunching a customer’s search patterns and usage data – like past purchases or support queries – the engine can predict what will be most helpful for that person and offer them tailored results.
Also, that kind of user data can be aggregated business-wide to improve search in a more macro way and enhance the overall user experience.
Using natural language processing to generate insights on customer feedback
Now we’re in “wow” territory.
Brands can use the sophisticated language processing of AI to scour customer feedback and generate insights. The AI engine will process whatever review and support data it’s fed and identify common themes, trends and prevailing emotions.
This can help brands figure out what their customers are saying about their products and services, and what they might need to improve. This kind of natural language processing can also help businesses understand the overall sentiment of their customers by automatically categorizing feedback as positive, negative, or neutral. This is super useful for businesses that want to make sure their customers stay happy.
On top of that, language processing can be used to identify customers with “flight risk” attributes or those who may defect to a competitor.
Providing customer support with conversational chatbots
In many ways, customer support is an excellent use case for AI. Take, for example, a chatty bot that provides automated, speedy answers to customer requests and points them to where they can seek deeper help.
But as bots get more sophisticated and more accurately mimic a real human conversation, there’s a potential pitfall.
As companies lean more on AI for customer support, they risk under-serving parts of the support experience that can’t be replicated by bots.
It’s likely that real human support experiences will become more and more scarce as the era of AI seeps into CX.
But that’s exactly where real opportunity lies.
Those moments of human connection are where relationship-building happens. When a support agent empathizes with your frustration and genuinely cares about helping you solve an issue, that’s an interaction that leaves an impact. As more AI gets woven throughout CX, those memorable human moments will become even more powerful.
Also, as helpful as AI is, you always want a real human to be a touch away. You definitely don’t want to recreate the frustrating experience of being lost in call center menus, just with more shiny tech.
And when customer issues require complex problem solving that’s unique to their situation, there’s no replacing the adaptive problem-solving and soft skills of human agents.
The best of both worlds
In an ideal CX, AI interaction and human interaction strengthen each other.
There’s absolutely a way for companies to leverage the rising tide of AI and have it streamline the customer experience, but that only reinforces the importance of offering a genuine human connection.
Want to see how Glance’s Guided CX solutions let you embed real, human support moments in your customer experience?
