The 3 types of analytics set to transform customer experience

Every industry – from banking, utilities and telecommunications to retail and transport – is becoming increasingly commoditised. Price and product offerings are becoming increasingly similar, making it hard to tell one company from another.

Today, the omnichannel experience is the only tangible means for customers to differentiate between companies, and is therefore critical to business success. From mobile apps, chatbots, click-to-call solutions, online forums and social media, there has been an explosion of different channels that customers can use to get in touch with a business.

>See also: AI’s impact on customer experience

However, most of these channels are in silo, and do not share information with one another. So while many organisations recognise the need to provide their customers with the option to contact them via different channels – there is remarkably little coordination or consistency between these methods of communication.

More often than not, companies fail to share data or even communicate the same message to consumers. This causes frustration and inefficiency, increasing customer churn and damaging the reputation of the business.

Analyse this

In order to provide an excellent customer experience, organisations must take a holistic view and ensure every interaction is consistent across all channels. Moreover, by consolidating data from all points of customer contact, behaviour patterns can be analysed instantaneously and accurately; which has the potential to change the face of the customer care as needs can be understood, anticipated and acted upon. The data gathered can give valuable insight, which can then be used to define strategies to meet customer expectations.

>See also: 4 factors set to impact customer experience management

Fortunately, the technology businesses’ need to keep up with customer expectation is already emerging, and the advent of high speed, high volume and high velocity analytics – facilitated by advances in big data analytics and artificial intelligence – will allow organisations to detect the nature of a customer engagement and present a quick, personalised solution. In order to create a holistic experience, organisations need to analyse customer data using three kinds of analytics:

1. Descriptive Analytics

Descriptive analytics give companies the means to see what is going on in business interactions clearly, in real time.

By setting up a platform that casts itself over the entire hub and consolidates data from every channel, organisations can use analytics to create a ‘report card’ that will show exactly what customers are getting in contact about, and how they are doing it. This data helps businesses to spot potential issues with current care procedures, key trends in demands and to improve the overall efficiency of the customer hub.

2. Predictive Analytics

Predictive analytics collates past information – using statistical models and machine learning technology – and uses this information to predict what will happen in future. In other words, predictive analytics helps by forecasting what, when and why something could happen.

If a customer that phoned the day before about a complaint sends an email, the company should be able to recognise this is the same person and anticipate the query they will have, reducing customer wait time and increasing the productivity of the customer hub.

>See also: Businesses ‘lack skills to implement’ AI and data analytics

This will help an agent or a service engineer understand the context for a customer engagement. For example, in the case of a telco business, the operations team can access information about the customer such as the handset being used, the data and call usage patterns and can see any potential issues that the customer may be calling about. By having an understanding of why a customer is getting in touch beforehand, businesses can resolve issues faster – saving the customer trouble, and the company time and resources.

3. Prescriptive Analytics

With the right technology, it is now even possible for a customer experience platform to predict the ‘next best action’ for individual customers when faced with an enquiry, regardless of which channel the customer is using.

As this technology develops, businesses will be able to anticipate customer needs, and provide a solution for basic issues on a completely automated basis – freeing up agents to tackle more complex issues faced by customers.

>See also: Using big data analytics to win back customer confidence

If implemented properly, this will ensure that customers have a seamless experience that caters to them personally, and remains consistent between a high-street branch, over the phone and online.

As pressure increases on businesses to deliver a better customer experience, those who can analyse their customer data best will come out on top. Organisations must adapt their current contact centres so they can find out the best way to improve their product and service offerings, and improve levels of satisfaction for customers in turn.


Sourced by Shashi Nirale, SVP and GM, EMEA at Servion Global Solutions


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Nick Ismail

Nick Ismail is a former editor for Information Age (from 2018 to 2022) before moving on to become Global Head of Brand Journalism at HCLTech. He has a particular interest in smart technologies, AI and...