How To Use AI-Driven Analytics to Improve the Customer Experience

6 mins read
How To Use AI-Driven Analytics to Improve the Customer Experience

In 2020, artificial intelligence (AI) and machine learning applications will fundamentally change the customer experience (CX).

A recent Forbes article estimated that 90% of customer service interactions are based on artificial intelligence. Considering the dominance of chatbots, interactive voice response (IVR), and self-curated website content, this is realistic.

But the one area where AI is outperforming any previous system is analytics: analyzing data to get insights. AI-based analytics has the potential to improve the customer experience by delivering data-driven insights on an unprecedented scale.

Here is how.

1. Access to greater amounts of data

First, AI is helping businesses collect more and more data. The number and quality of the available data points determines the accuracy and information content of each analysis report, whether or not AI-driven.

 AI is helping businesses gain access to an unprecedented wealth of data is natural language processing (NLP) and conversational AI.

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

Modern business telephone services with Voice over Internet Protocol (VoIP) business telephony services often already include transcription options. Going even further, some analytics platforms can perform sentiment analysis, using artificial intelligence to analyze the pitch of callers’ voices.

2. Unify different data points

Much of the customer travel data is scattered across a variety of incompatible platforms. From AI-powered WordPress analytics plug-ins to different Customer Relationship Management (CRM) platforms to internal legacy systems.

AI can help unify these vast amounts of data.

Cross-platform analysis applications can extract data points from a variety of sources, and automatically convert them to compatible formats. If a customer’s profile is stored in an old system, makes an irritated call to support, clicks on a website link, leaves a review, or responds to a call to action in a newsletter, the system will include it in calculations.

3.Create dynamic customer profiles

Thanks to the union of AI-based analysis platforms, it is possible to perform high-level behavioral analyzes.

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

More importantly, instead of remaining static after they are created, these profiles are constantly updated by AI analytics tools. Changes in behavior or interests are systematically reflected there. This is possible thanks to the independent and continuous operation and computing power of artificial intelligence.

Based on these detailed and dynamic customer profiles, a highly personalized customer journey can be designed. In fact, systems are advanced enough to allow even predictive personalization.

4. Implement predictive personalization

Artificial intelligence can identify the needs of your customers even before (potential) customers realize them on their own.

Based on dynamic customer profiles, contextual information, and probability analysis, the AI can tailor the CX to meet emerging customer needs.

Predictive analytics is already being implemented successfully by countless companies. Apps vary – from Netflix suggesting what to watch next and Harley Davidson identifying valuable customers ready to make a purchase to Sprint sending proactive retention offers to customers prone to unsubscribe and Caesar’s Palace deciding what to buy most efficient upgrades for customers.

Common to all these predictive analytics and personalization applications have in common is a CX enhancement.

5. Obtain real-time information for customer service

Finally, AI-powered analytics applications can provide a direct foundation for interactions between customers and representatives of human companies.

Given the vast wealth of data available on each client, and the high number of clients, it is impossible for an agent to personally retain the details of each of them personally. Or, indeed, direct the same customer to the same agent every time.

Still, AI can automatically provide the information necessary to make each interaction personal, efficient and satisfying.

Many UCaaS (Unified Communications as a Service (UCaaS) and VoIP platforms have built-in AI analytics tools that will automatically extract relevant records about a customer who contacts a company and make them available to the agent managing the interaction.

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

In this way, the AI enables uninterrupted service for customers – something that 96% of them highly value – and relieves human agents, allowing them to do their jobs more efficiently and focus on matters. more complex.

Conclusion

Artificial intelligence permeates all aspects of the business sphere. The analytics capabilities are an invaluable benefit for companies looking to improve CX.

Using AI to collect high-quality data, unify information from different sources, create dynamic customer profiles, implement predictive analytics, and gain real-time insights, companies can build integrated, personalized end-to-end customer journeys. 

It is never too late to implement AI analytics and increase your CX and business success.

Matthew White

Matthew is a dedicated businessman and an angel investor. He usually features his written works in several business blogs and works as a marketing consultant to various companies.

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