5 Data-Driven Strategies for Improving Customer Experience

Blog Post •
Customer experience can make or break a retail or e-commerce business—and the numbers prove it. With 75% of customers willing to pay more for a great experience and over half ready to walk away after a bad one, CX is everything. Yet many retailers overlook the critical role data plays in shaping that experience—limiting their insights and, ultimately, their impact.
woman looking at tablet

Customer experience is arguably one of the most important priorities for retail and e-commerce businesses. 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 research data from Zendesk), but 53% will leave permanently if the experience is poor.  

Many retailers underestimate the crucial link between data and customer experience (CX). As a result, they collect and use only a fraction of the available insights—often surveying just 7% of their customers. This narrow view limits their understanding of customer needs and behaviors, ultimately capping their ability to deliver meaningful support across the entire journey.

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 e-commerce 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 engage with your brand across multiple touchpoints—from social media ads to your online store, to customer support. Along the way, they might join your email list or use a chatbot to ask about product details like sizing or quality.

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 e-commerce 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.