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Transforming customer experience with AI and Machine Learning – Ericsson

Today, that are many apps that excel in using AI to enhance the customer experience. Some of the more popular applications from, for example, Apple and Uber, are inspiring in terms of customer experience management. There are learnings to be had here, especially in terms of engaging with customers in the ways they want to engage. This could be across many different channels, including social media apps and mobile apps. Traditional ways of engaging with customers are becoming irrelevant; people don’t necessarily want to be on the phone to somebody.  To pioneering companies, this is clear, and many of our service provider customers are investing, acquiring and partnering to make sure they capture new opportunities to enhance the customer experience.
In telecom BSS we’re starting to use AI and Machine Learning in Ericsson Digital BSS with our customers. Just a few years ago, service providers would mass market a single offer at a time to consumers (or a small number of offers). What we’re seeing now with AI is the ability to market to much smaller customer segments, giving consumers a far better experience than they are receiving today. Micro-segmentation is one of the capabilities we’re developing to add value to the Digital Experience Platform (DXP). A series of customer intelligence AI improvements spans similar interest recommendations, dynamic segmentation, and next best offer (NBO).

Focus has shifted to creating the services that consumers actually want
With our new ML learning algorithms, we look at all our customers’ data, their customers’ usage patterns and purchases and identify micro-segments that may not be traditionally apparent. The next step is aligning product offers to these micro-segments, as opposed to having a broad stroke approach. By marketing new offers to these micro-segments, we increase the chance the consumer will be interested in that offer. There’s a couple of things happening here. Consumers get a better customer experience, getting more of what they want, tailored to them. And the flip side of this is more revenue per user, with the added ability to upsell components consumers might not have known about.
This is exciting because, suddenly, consumers can be targeted with personalized products. Instead of having a new mass market product, it changes the conversation to “here’s a product for you, we know  how you use the service, and we’ve invented a product for you.” Consumers are more likely to engage in that interaction and to get that kind of personalized treatment. Tailoring products to people was difficult in the past because characteristics like age, income bracket or other measures was limiting in trying to figure out who the consumer is and what they want. Now there is much more granular detail about how they are using services that can be used to help deliver the best possible product to specific target groups.
With the advent of both Next Best Offer (NBO) and Similar Interest recommendation AIs, we provide a guided selling experience for consumers and Communication Service Providers. NBO, for example, will help the CSR identify the best new plan for a consumer during customer interactions.  Similar Interest analyzes all of the upsells and cross-sells that other consumers have chosen and makes recommendations at the point of purchase for add-ons and other products available for purchase. 

 Service providers can create new products faster than ever before
We’re doing things we didn’t think were possible a few years ago. Working with service providers, we are building AI that can create product offers by itself. By analyzing the existing product portfolio, looking at products that are successful, then looking at customer usage patterns, and looking at customer complaints – AI is able to analyze that information and predict that, for example, adding another 100 minutes of free voice into this package has a high chance of success. It’s able to create that product by itself. The product management person still approves the newly created product before it launches and makes sure everything else is ok and they can launch it quickly.
And there’s more; AI in the form of chatbots can reduce mundane, manual tasks to a minimum, freeing up agents to deal with more complex tasks and spend more time with people where it’s needed most. AI can make it easier for customers to complain, and even better, it can proactively engage to prevent complaints.
I discussed all this and more (e.g., the importance of the master product catalog) with TM Forum’s Aaron Boasman-Patel, Vice President of AI and Customer Experience, at a recent TMF event, Digital Transformation World Series .  Watch the full discussion on raising the bar for customer experience with predictive and pre-emptive AI & ML