Predictive analytics in customer service

Predictive analytics

Predictive analytics in customer service

Today, it’s no longer enough for businesses to provide fast and friendly service – or even respond to their customers in real time. Now, it’s about predicting your customers’ needs; ensuring customers have the information they need before they are even poised to make a purchase.

In the current market, even retailers that have made significant investments in CRM and sales force automation solutions are starting to re-pivot their entire culture and process around the customer experience post-purchase.

According to a recent Gartner study, 50% of all customer interactions will be influenced by real-time analytics by 2018.

So what is predictive analytics?

Predictive analytics is an expanding field of technology that’s becoming increasingly important in the world of customer experience. Essentially, predictive analytics helps businesses to predict future events. It relies on a combination of data mining, statistics, modelling, machine learning and artificial intelligence. Patterns from historical and transactional data are used to identify risks and opportunities for the future.

In a retail context, predictive analytics is about merging customer data and analytics platforms with customer experience technology – including CRM solutions and content management systems.

Importantly, predictive analytics is also ever-evolving: with the machines constantly learning and digesting information about customers to help increase retailers’ understanding of what their customers need.

So what does this mean for you?
For retailers, predictive analytics is vital in helping you understand – and predict – future customer behavior. So, for instance, if a customer has purchased a particular item online, predictive analytics can help you determine the likelihood of that customer buying again, based on their individual buying patterns. It can also help you determine the best time, and method, to contact the customer to optimise the likelihood of a repeat sale.

Done correctly, predictive analytics can be a highly valuable tool in driving long-term, profitable customer relationships.

However, before you invest in any predictive analytics solution, it’s important to think carefully about how you are currently responding to your customers. Do you have sufficient understanding of your customers’ needs right across the sales lifecycle? If a customer buys a product or a service from you, how do you go about understanding their needs on an ongoing basis? Do you have enough data to determine when they would be interested in making a repeat purchase – and what they would be interested in purchasing? Are you missing out on potential sales simply because you don’t know exactly what your customers might want?

To clarify your requirements – and understand the possibilities – it’s worth talking to a technology partner – like Sable37 – about predictive analytics and how it could help you improve the experience you’re offering to your customers.

Find out more
Contact Sable37 now to discuss predictive analytics for your retail business.

Or, to learn more about the future of customer experience, download our whitepaper now: Customer experience is the new ‘product’

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