3 Datasets That Will Enhance Your Customer Experience

Customer experience. User experience. Data and analytics. What do these things really have to do with improving the bottom line?

Today, more and more companies are realizing that true competitive advantage lies in creating an engaging customer experience (CX) — one that is personal, fast, easy and useful. The proliferation of digital CX solutions means that marketers and business owners can better quantify customer experience and incorporate related data into their business strategies. By using advanced analytics, companies can make better use of their customer and user experiences, leading to higher satisfaction (and loyalty) in the long term.

Why Does Customer Experience Matter?

In the digital marketplace, customers are more demanding than ever before. More than half of customers today say they’ve switched companies solely because of poor user experience. Companies who fail to embrace CX as a strategic path to growth won’t just be lagging — they’ll get left behind.

The ability to use active and passive data to better gauge your customer and their journey is imperative to creating the optimal customer experience and improving journey mapping. Companies must collect, analyze, unify, sync and augment customer data across the entire customer journey, from awareness to purchase to support to advocacy.

Many brands are enhancing their data collection and analysis capabilities by implementing automated systems such as customer relationship management (CRM) platforms to drive these insights. The data that’s collected can ultimately be fed and connected to other applications within a cloud suite to stimulate and house interactions across your company. Below are three important datasets to track and analyze in order to improve your overall customer experience.

Discovery Data

Learning how your customers got to know your brand is an important step to improving customer experience. By collecting various data points, companies can gauge the success of their marketing strategies.

For example, paying attention to the click-through rates of links communicated through marketing emails, text messages, and other channels can reveal whether or not a marketing strategy is leading to actual sales. Businesses may use these touchpoints to contextually share information regarding sales events and extra in-store discounts.

Using this data can allow businesses to know who is interacting with their marketing strategies and to what extent. They can now tailor their messaging to achieve better results with their target market.

Knowing your target audience is key to running a business. When you know your target audience, you know how to reach them and encourage conversions. Even if you think you know your target audience well, there’s always room for improvement, and data can help you identify where you can improve.

Purchasing Data

Too often, businesses don’t put themselves in their customers’ shoes, instead creating a buyer’s journey that best fits their own needs. They aren’t the ones making purchases, though — the customers are. This means it’s important to create a buyer’s journey that is customer-centric and will provide the best experience possible. Without fully understanding the purchase journey, that’s hard to do.

Data makes it possible to understand what customers have to go through and where the friction points are without real-time interaction. A recent study shows that after one purchase, a customer has a 27 percent chance of returning to your store. While that’s not a horrible return rate, if you can get that customer to come back and make a second and third purchase, they have a 54 percent chance of making another purchase. Data allows you to watch behaviors and trends that lead up to, occur during and happen after purchases, giving you better insight into the purchase journey.

Emotional Data

Big data analytics can also detect patterns in customer behavior, and use these to adjust a business' offering. Reports can be used in conjunction with behavioral analysis to find out why people are interacting, and what the implications are. For example, a customer may call to cancel a subscription without giving a reason. By using associated data, businesses may be able to review the kind of experience this particular customer has had. Have systems been slow, or have they received poor service? This will allow them to make informed deductions about their customer’s behavior and act accordingly.

Collecting and using the right data can help you identify the pain points your customers are experiencing and learn how to improve. As customers express their frustrations about your products and point out where you’re falling short (even if they aren’t expressing it directly to you), make sure to collect that feedback. With this insight, you can then make improvements and changes to create the best version of your product possible.

By asking questions in polls, surveys, and feedback forms, you can learn what you should enhance to increase customer loyalty and increase income. With big data analytics, you can estimate the following indicators:

1. Current level of customer satisfaction
2. Metrics that have a major impact on customer loyalty
3. Factors that affect customer negative feedback
4. How to improve customer/employee performance
5. Things that need to be improved
6. Things enjoyed by customers

Final Thoughts

Data is a powerful tool that, when used correctly, can make all the difference to a business. Not only can it help you improve the customer service you provide, but by doing so, it also enables you to improve your company and products, create customer loyalty and create a clear plan for the future that will keep your business moving forward.