In 2020, artificial intelligence (AI) and machine learning applications are fundamentally reshaping customer experience (CX).

A recent article in Forbes estimated that 90% of customer service interactions are AI-powered. Given the predominance of chatbots, interactive voice response (IVR), and auto-curated website content, this is realistic.

But the one area in which AI is surpassing any previous systems is analytics: parsing data for information. AI-powered analytics has the potential to enhance CX by providing data-driven insights at an unprecedented scale.

Here is how.

1 – Access Greater Quantities of Data

First off, AI helps businesses collect ever-greater amounts of data. The number and quality of available data points determine the accuracy and information content of any analytics report, whether AI-driven or not.

One prime way in which AI helps businesses access an unprecedented wealth of data is through natural language processing (NLP) and conversational AI.

Modern AI can record spoken words and parse their meaning. This means that information from any spoken interaction can be harnessed to create a more integrated, personalized, end-to-end customer journey.

Modern Voice over Internet Protocol (VoIP) business phone services often already include transcription capabilities. Going even further, some analytics platforms can perform sentiment analysis, using AI to parse the tone of callers’ voices.

2 – Unify Disparate Data Points

Many of the data on customers’ journeys is scattered across a variety of incompatible platforms. From AI-powered WordPress analytics plugins over disparate Customer Relationship Management (CRM) platforms to internal legacy systems.

AI can help unify these huge amounts of data.

Cross-platform analytics applications can pull data points from a variety of sources, and automatically convert them into compatible formats. If a customer profile is stored in a legacy system, if they make an irritated call to support, if they click on a website link, if they leave a review, or respond to a call to action in a newsletter – the system will include it in calculations.

3 – Create Dynamic Customer Profiles

With the information AI-driven analytics platforms unite, it is possible to perform high-level behavioral analytics.

These approaches yield dynamic customer profiles, encompassing a (potential) customer’s identity, loyalty, values, interests, preferences, needs, segments – and much more.

More importantly, rather than remaining static once created, these profiles are constantly kept updated by AI analytics tools. Changes in behavior or interests are systematically reflected in them. This is possible thanks to the independent, continuous operation and the computational power provided by artificial intelligence.

On the basis of these in-depth, dynamic customer profiles, a highly personalized customer journey can be designed. In fact, systems have advanced sufficiently to make even predictive personalization possible.

4 – Implement Predictive Personalization

AI can identify your customers’ needs even before (potential) customers realize them themselves.

Based on dynamic customer profiles, contextual information, as well as probability analyses, AI can adjust CX in tune with customers’ emerging needs.

Predictive analytics is already being successfully implemented by countless companies. Applications vary – from Netflix suggesting what to watch next and Harley Davidson identifying high-value customers ready to make a purchase, to Sprint sending proactive retention offers to churn-prone customers and Caesar’s Palace deciding on the most effective upgrades for guests.

What all these applications of predictive analytics and personalization have in common is a CX enhancement.

5 – Derive Real-Time Insights for Customer Service

Finally, AI-driven analytics applications can provide a direct basis for interactions between customers and human company representatives.

Considering the immense wealth of data available on every customer, as well as high customer numbers, it is impossible for an agent to personally retain the details of every single one of them. Or, indeed, to route the same customer to the same agent every time.

Still, AI can automatically supply the information needed to make every interaction personal, efficient, and satisfying.

Many Unified Communications as a Service (UCaaS) and VoIP platforms integrate AI analytics tools that will automatically pull relevant records on a customer contacting a business, and put it at the disposal of the agent handling the interaction.

More than that, since AI can track the contents of a conversation, the needed information can continuously be updated – and suggestions for actions, and even phrasings can be provided.

In this way, AI enables seamless service for customers – something that 96% of them value highly – and takes pressure off human agents, leaving them to do their job more efficiently and focus on more complex issues.


Artificial intelligence is permeating every aspect of the business sphere. Its analytics capabilities are an invaluable boon for businesses looking to improve CX.

By harnessing AI to gather high-quality data, unify information from disparate sources, create dynamic customer profiles, implement predictive analytics, and derive real-time insights, businesses can curate integrated, personal, end-to-end customer journeys.

It is never too late to implement AI analytics, and boost your CX – and business success.