How to Use Text Analytics to Improve Your Customer Experience

With text analytics, you can examine open-text feedback for an organized, actionable, high-level view on the feelings and the comments

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Sara Staffaroni

December 11, 2019

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With text analytics, you can examine open-text feedback for an organized, actionable, high-level view on the feelings and the comments your customers make about your company. Paying attention to open-ended feedback is crucial if you want a clear representation of your customer experience (CX).

An added advantage of text analytics is that it helps uncover trends that you might not have even realized existed–questions you might not even be asking on your customer surveys.

Why you should use text analytics

Scalable feedback. While feedback is manageable when you receive messages every once in a while, it becomes a burden when you receive dozens or even hundreds of comments a day. With text analytics, you can analyze a huge volume of customer comments in a way that’s also scalable. 

Objective results. It’s easy to make mistakes or introduce bias when you’re manually analyzing your data, not to mention the amount of time your team might have to spend looking at comments one by one. With text analytics, the process is objective which means that no matter who’s looking at your data you’ll get the same results. That’s key when you need to make decisions that can affect your business. 

Turn unstructured data into insights. Think of text analytics as a way to simplify the analysis of survey results and with it get the most of the data you have collected. Because you’re looking at unstructured data, it’s really like listening to your customers freely talk about your products.

 How to use text analytics to improve CX 

Step 1: create dashboards to see the data that matters the most

Creating a visual dashboard with your text analytics data is the first step toward improving your customer experience. Forget about spreadsheets— dashboards are your way to see data in a way that’s human-friendly so you can easily understand the information collected using text analytics. 

With dashboards, you can customize the information being shown so that you only see the data you’re interested in a way that’s clutter-free and looks great. The ideal dashboard shows you customer comments in real-time, extracting the keywords and phrases that are most relevant. Filter dashboards by important merge fields—like region, agent, or product—and send personalized dashboards to stakeholders across your organization.

Below is an example of GetFeedback’s text analytics dashboard.

GetFeedback text analytics dashboard

It’s also really useful to create dashboards that present more or fewer data depending on your role. For example, support agents can benefit from knowing real-time information on their rating and monthly CSAT score, but they might not need to know the overall sentiment score for the whole company or what keywords are mentioned the most.

Step 2: analyze data to avoid losing customers

Happy customers are loyal customers, that’s why it’s so important to be able to measure how your customers feel about your brand. 

Too often, however, we fail to act on an urgent issue before it’s too late. Not because we don’t want to but simply because we don’t have the information before it turned into a critical issue.

With text analytics you can use sentiment analysis—the automated process of understanding an opinion, either written or spoken—to quickly detect and avert a possible brand crisis and face losing customers. By flagging expressions like “I bought milk for my baby and I noticed it was expired after feeding her!” you’ll be able to act just in time to prevent an issue from getting into a reputational problem.

Step 3: get insights on what your customer thinks about specific areas

Say you sent a survey to your customers to check on their general satisfaction with the product they bought. You’re particularly interested in knowing what they think about the cost because your current model is very different from the competition. 

If you receive responses by the hundreds, you probably can’t afford to ask people to read them manually–it’d take too long and you’d risk discrepancies in the results due to human error or bias. 

Instead, you can determine the keywords you want to focus on, like “cheap” or “price” and discover which topics or issues your customers are talking about in relation to that product. 

Using text analytics, you can quickly have a general overview of what your customers really think. Simply use the answer filter so that you only show survey responses that included a specific answer to the question you’ve selected.

Once you’ve untapped that information, you’ll be better informed to make decisions to improve your customer experience.

Step 4: discover hidden trends the moment they arise

The beauty of text analytics is that it can detect problems affecting lots of people before you even realize there’s a trend, 24/7, thus giving you a huge advantage when it comes to resolving them in time. 

With today’s information overload saturating businesses, it’s easy to feel overwhelmed, not knowing exactly where your priorities should be. For example, if you start to see your sentiment score suddenly drop, you may want to investigate further and look deeper into the negative keywords during that time to figure out what the issue might be.

You might discover that a certain feature in your product isn’t working quite right and that a lot of customers are confused and frustrated. With that information in your hands, fixing the problem quickly becomes much easier.

Step 5: understand what your customers think about support staff

Imagine you sent a customer satisfaction survey to your customers and you included questions about their experience with customer support. By analyzing the text within each response, and follow-up exchanges, you or the customer support manager can see how specific team members perform in relation to the customer’s interaction. This is key to improving the work of your staff overtime. 

All you have to do is make sure that you include a merge field track to track case owner name before sending off that survey so that you can see which agent was working with which customers. Then when your customer clicks on your survey link, it will automatically populate their case owner name along with their name, email, and case number in the background.

Conclusion

Part of improving your customer’s experience involves looking beyond number ratings and instead focusing on open-ended feedback. Doing that, however, can be a painful process for your team because it requires a lot of time and resources, plus you risk getting it wrong due to human error. 

Using text analytics is a great way to look at open-text responses in a way that is both quick and scalable, and can have a real impact on improving your customer experience which in turn can benefit your business. 

With the power of a customizable dashboard that shows you the data you need in a way that is friendly and understandable, you’ll be able to quickly get a screenshot of the context surrounding your stats and numbers. Use it to discover trends as soon as they pop up, know what your customers really think about you and avoid the next big CX issue.

Learn how GetFeedback can help you exceed customers’ expectations—start your free trial today.

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