1)  AI Can Be Used to Predict Customer Intent:-

Your customers may contact you for a multitude of reasons. Some of these reasons are fairly straightforward, others are intricate, yet, rarely are they entirely novel.

With the immense data that you are collecting with every recorded phone call, chat interaction and email, you have a strategic asset that can be used to train machine learning models to understand customer intent within conversations.

Once you understand true customer motivations, you can then use AI to optimise interactions through:

• Smarter routing of your customers
• Presenting potential up-sell and cross-sell suggestions for advisors during customer conversation

Flagging interactions for fraud and compliance risk

2) AI Can Help You to Track Customer Effort:-

Customer effort is one of the leading indicators of loyalty. Analysing customer effort can guide companies in identifying emerging issues before they explode into major issues.

Traditionally, effort has been quantified through structured questions on a survey. However, AI and machine learning techniques, combined with text analytics, can aid in evaluating the level of effort expressed in any piece of unstructured customer feedback.

AI can do this through interpreting word choice and sentence structure, as you can quickly understand which aspects of the customer experience cause friction in any feedback source – not just in surveys.

3) AI Is Best Implemented With the Support of the Entire Team:-

Before you deploy AI, it is worth considering that one of the biggest risk factors in any IT implementation, system upgrade or system change are the human users of that system.

By failing to communicate in an open, honest, transparent way how this technology is going to benefit them, you will meet resistance.

If you simply say, we are rolling out this new robotic-led approach on Monday, your employees will inevitably be negative towards the technology and may even actively sabotage it.

Instead, you need to get people involved in the process. Ensure they can test out the technology in a safe environment and make sure they are comfortable with it, before you even start rolling the technology out.

4) AI Increases in Value With Good Knowledge Management:-

Any AI application will only ever be a good as the knowledge at its disposal. You need to ensure that when a question is answered in the contact centre, that knowledge is captured and delivered into the knowledge management system (KMS), so that customers, bots and advisors can feed off it.

After all, how can AI be used to make decisions when it does not actually know anything? It can learn but it needs relevant data to do that.

This is why it is so important to have processes and procedures in place that enable you to feed accurate data and intelligence into the KMS.

Many businesses are too reliant on their employees as a source of knowledge and therefore run the risk that if people leave the business, they take the knowledge and understanding that they have gained with them.

5) AI Is Driven by Customer and Employee Data:-

Any strategy that uses AI and machine learning should be considered within a broader customer experience AI strategy that considers how data will be leveraged across both the customer and employee journeys.

There are many opportunities to apply AI and machine learning across the customer engagement process.

For example, knowing the right moment to proactively engage with customers online, routing to the best agent based on the desired business outcome and assisting them to accurately handle enquiries – AI and machine learning can help drive all of that.

However, AI applies to more than just customer journeys. It can also help identify why specific agents are better than others at certain contact or customer types, increase the speed and accuracy of workforce planning and scheduling and automate task completion post-contact.

Most firms love to talk about the value of customers but don’t get value for customers right. That’s ironic because customers that get value create business value in return by increasing profitability and market share. Academia has written about value for customer for decades. But businesses have been sluggish and incomplete in applying it.

We asked ourselves: Why is that? How can we do better? What can companies gain if they understand value for customer? What is a CX pros’ role in this?

Misconception (“What”): Value for customer is about value for money

Value for customer is actually “A customer’s perception of what they get versus give up.” It has four dimensions: functional, economic, experiential, and symbolic. Siloed efforts by marketing, CX, product, sales, or pricing fail to create value across all dimensions. Worse, lacking a horizontal view of the customer, these efforts can cancel each other out.

Customers make trade-offs between these value dimensions. They are willing to give up value in a less important dimension if they get high value in another, more important one. But customers have a threshold for how much they are willing to give up depending on their context.

Misconception (“How”): Features of a product or service create value for customers

Value isn’t inherent but a perception. Context (worldview, situation and comparisons) determine what customers value and how they form that perception.

To form value perceptions, many people use “mental shortcuts.” Especially, when they are under time pressure or unfamiliar with a product or service.

Misconception (“Who”): Your firm creates and delivers value for customers

When trying to accomplish a goal, a customer derives value not from interacting with a single firm but from her own actions and interactions with many different organizations and people. For example, to become healthy, a customer creates a value network that includes a doctor but also a physiotherapist, friends and family, associations, and insurance firms – getting different value from each.

Firms that understand customers’ value networks and what value they seek from the firm vs. other actors can help customers create more value.

CX professionals must step up to improve value for customer

CX pros have the horizontal view of the organization along customer journeys. That’s critical to understand what customer want to accomplish, who they interact with as they do and what value they want from each actor – inside and outside your firm.

If you are a CX pro, volunteer to help your firm to improve value for customers! Get started by understanding how well your firm helps customers create value. Then, define metrics for value for customer, focus your research and design practice on identifying what customers value and finding ways to help them create it. Finally, pivot your CX ecosystem to help customers create (rather than destroy) value.