What if you could predict your customer’s needs before they ever asked you for something?
How about being able to see the things that are negatively impacting your customer’s experience in real-time? That way, you could fix problems before they had a lasting impact on your client’s loyalty to your brand. Thanks to artificial intelligence, and state-of-the-art analytics solutions, it’s now possible to use predictive analytics and real-time analytics to enhance CX in a new way.
Today, we’re going to be looking at some of the ways you can use real-time, and predictive analytics to get an edge over your competition.
1. Forecast Customer Needs
One of the most obvious ways to use predictive analytics in CX is by forecasting your customers needs ahead of time. According to McKinsey, prediction has the potential to be the future of customer experience, particularly as client expectations of companies continue to expand.
Now more than ever, your customers are expecting faster, more intuitive and relevant experiences from their favourite brands. The digital age and web-based transactions have made clients less patient. The rise of innovative new shopping experiences during the pandemic accelerated this trend even further. Predictive analytics could be the only way to keep up with demands in the current landscape.
Through big data and machine learning, companies can use predictive analytics to figure out what a customer needs before demand increases. This can make it easier to stock products that are likely to see a peak in popularity or even suggest new products to customers during a sales pitch.
2. Maintain Long-Term Customers
Part of being able to predict the needs of customers is being able to determine when and how they’re going to need extra help from you. Repeat customers are much more valuable to any brand than a one-off client. With predictive analytics, you can boost your chances of turning a single purchase into a long-term relationship, by predicting exactly when your customer is going to need you.
By looking at previous buying behaviour and trends displayed by similar clients, you can see when your customers might want to re-purchase a subscription from you and send them an offer at just the right moment. When you keep on top of your customer’s needs and let them know you’re still around when they need it most, you’re less likely to experience churn.
According to CDO of JD Power, predictive analysis is one of the most powerful tools for identifying customers at the brink of churn and stopping them from leaving your company behind.
3. Provide Better Customer Service
For service providers, real-time and predictive analytics offers endless opportunities offer greater value. Rather than just responding to customers when they have an issue with their connection strength or a problem with their data centres, you can offer to constantly monitor and support your clients. Service management services are becoming increasingly popular in the digital age.
In B2B landscapes, clients can’t afford for their digital solutions to stop working for even a moment. One minute of outage could lead to endless lost opportunities. Fortunately, real-time analytics can allow you to keep track of your customer’s service, and even set up notifications when something goes wrong.
Over time, as you develop a baseline for what’s normal for that customer, it’s also possible to create predictive analytics that can easily detect when a problem might happen before the issue begins.
