5 Data-Driven Strategies for Improving the Customer Experience

Customer experience is arguably one of the most important priorities for retail and eCommerce businesses in 2021. And when you look at various survey data and reports, it’s no wonder why.  

Not only are 75% of customers willing to pay more to shop at a business with a great customer experience (per new research data from Zendesk), but 53% will leave permanently if the experience is poor.  

Unfortunately, many retailers don’t realize that the connection between data and customer experience (CX) is vital. As a result, they limit their collection and use of data significantly – only sampling about 7% of their customers in customer experience surveys. And this limited knowledge of customers’ needs and attitudes places an artificial cap on their ability to support customers throughout the customer journey.  

In this post, we’ll look at the importance of data in customer experience strategy and highlight a few specific ways you can (and should) use big data to improve your existing customer experience.  

The Importance of Data in Customer Experience  

Customer data can offer deep insight into virtually any topic. And because it’s factual (i.e. based on measurable standards and on real-life behavior), it’s also incredibly useful.  

For instance, customer experience data can shed light on issues like customer engagement, churn risk, and customer satisfaction levels by collecting information from individual interactions and feedback.  

Once they have this data, retail and eCommerce businesses can then take an honest look at their customer journey, pinpoint what’s working and what isn’t, and make improvements to better cater to their customers’ needs. 

5 Ways Data Can Improve Customer Experience  

Finding valuable applications for customer data is difficult, though – especially if your business is battling the flow of big data. However, there are some pretty simple ways you can use big data to improve customer experience strategy. Let’s look at 5.  

Increase Strategic Decision-Making 

The most obvious application is decision-making. Since the insights allow you to see your customers more clearly, you can use them to uncover critical pain points that are driving loyal customers away and discover new opportunities to delight leads and new shoppers. For example, you might find better ways to market your products, fulfill orders, or deliver an omnichannel experience that makes shopping more seamless.  

Regardless, making decisions based on reliable data can both protect your bottom line and help you build stronger customer relationships.   

Enhance Customer Mapping 

Customers interact with your brand at various touchpoints throughout the customer journey. For instance, they might follow a path from your social media ads to your eCommerce store and finally connect with your customer support team while waiting for an order to arrive. And during the journey, they might join your email subscriber list and get some information from a chatbot on the quality or sizing of a product.  

Using customer data, you can clearly see how all of these touchpoints fit into your customers’ experience with your brand. More importantly, you can use that data to pinpoint strengths to capitalize on and weaknesses to work on.   

Improve Customer Service 

Customer support is at the heart of your brand. Whether your customers are struggling to find the right product, having issues placing an order, or want to know the status of a delivery – they turn to your customer support team.  

Keeping up with customers’ requests is challenging, though. And it’s becoming even more difficult since customers want complete answers in real-time.  

Luckily, customer data is useful here as well. Not only can it be used to create visual IVR experiences that your shoppers can use to find answers on their own, but it can also be fed to machine learning algorithms and chatbots that can evolve their responses to fit your customers’ needs.  

Make Real-Time Pricing Adjustments 

Pricing is volatile in retail and eCommerce industries. One minute a product may be languishing on the shelves and the next it could be sold out and back-ordered weeks into the future, thanks to a new fad on social media.  

To price products appropriately, you need to be able to see sales in real-time across all channels. Data helps you do that, making it easy to adjust your prices to supply and demand, even when products go viral.  

Predict Trends 

While data often looks backward, predictive data analytics gives you a glimpse of future buying behavior. With this perspective, you can make smarter decisions about product sourcing and inventory management. You can also plan marketing campaigns and customer interactions that will support the expected demand.  

In doing so, you can increase customer satisfaction and customer loyalty.  

Building a successful customer experience strategy can’t be done without data. Fortunately, it doesn’t have to be. By collecting customer feedback and extracting relevant information from their shopping behavior, you can improve your decision-making, predict trends, map customer touchpoints, make pricing adjustments in real-time, and enhance customer service.