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Customer Experience

Using Text Analytics to Improve Your Customer Experience

How Text Analytics Gain Insight Into What Your Customers Want & Need

Customer experience (CX) is one of the leading differentiators in business today. It impacts how likely people are to purchase your products and services, recommend your brand to others, and become loyal repeat customers.

But it’s impossible to know exactly how and where your CX is succeeding or missing the mark without asking customers themselves. Ignoring their voice isn’t just a missed opportunity to understand and improve their experience. It could also spell trouble for your brand.

73% of all people point to customer experience as an important factor in their purchasing decisions (PWC).

If you’re collecting feedback from customers along their journey, whether directly through surveys or indirectly through social media and review sites, you’re already on the right track. The next thing you need to think about is how you’ll actually process that data, analyze it, and feed it back into CX improvements.

That’s where text analytics comes in. It’s your most powerful tool for getting insight into what your customers are feeling and what their experience has been. Let’s take a closer look at text analytics and how it fits into your CX program.

Understanding text analytics

Manually sifting through thousands of pieces of unstructured feedback is time consuming and unrealistic for most CX teams—and you’re bound to miss critical patterns and KPIs that machines are better equipped to recognize. Automating the process with text analytics can help.

Before we get into a high-level overview of how it works, let’s break down some terminology. You’ve probably heard the words text analysis, text mining, and text analytics thrown around in conversations about customer feedback.

Text analysis (not to be confused with analytics) and text mining are interchangeable terms for the process of quickly sifting through unstructured comments and identifying qualitative insights. For example, if you need to get a broad understanding of comments from a customer survey, you could use text mining or analysis to sift through the unstructured feedback and determine the main topics and attitudes represented in each comment. You’ll get a general sense of how your customers feel and notice some trends in what types of responses came up.

Text analytics, on the other hand, focuses on extracting quantitative insights. Much like numerical analytics, text analytics processes the findings from your text mining or analysis exercise to give you a measurable view of your CX data. This can be represented visually in a graph, table, or chart that quickly and clearly shows you quantifiable metrics from a large dataset of customer comments.

While text analysis or mining helps you determine the sentiment of individual feedback, text analytics gives you concrete insights about all your customer comments as a whole. Text analytics can tell you how many customers felt a certain way or had a specific type of experience, so you can identify and prioritize common themes and act on them.

text analytics

Why do you need text analytics?

With text analytics, you can turn customer feelings, beliefs, and opinions into insights you can actually use. By taking unstructured comments and organizing them into actionable, high-level observations about your brand, you get a clearer picture of your CX strengths and weaknesses.

Here are three important business reasons for using text analytics in your CX program.

1. Make data-driven decisions

When you’re going through feedback manually or on an ad-hoc basis, it’s easy to make mistakes or introduce bias. And it’s also a drain on time and resources. With text analytics, you can dig deep into what your customers are saying, get objective results, and prioritize your business decisions based on all available information. You might even extract insights you weren’t necessarily looking for in your survey questions, which can shed valuable new light on your customers and their expectations.

2. Understand the full picture

Using text analytics lets you take your CX insights to a whole new level. Rather than fixating on just a few bad surveys or complaint calls (which tend to overshadow all the other feedback you get), you can scale your discovery process to include thousands of customer comments. You’ll get a more holistic picture of what your customers are feeling and experiencing when they interact with your brand. That level of understanding translates to informed, strategic decision-making that better serves all your customers, not just a small handful.

3. Validate your CSAT and other KPIs

Paying attention to unstructured data from your customers is like having a conversation with each one of them. When analyzed quantitatively, those insights lend credibility and depth to other performance metrics you’re tracking. You can use them to validate your CSAT scores and other KPIs and show concrete evidence of your commitment to CX excellence. You’d be surprised by the power of high scores to turn customers’ heads and retain their loyalty

54% of U.S. consumers say customer experience at most companies needs improvement (PWC).

Make the most of your customer’s voice

Are you using all the information you have at your disposal to make the best possible decisions for your brand and customers? If you’re collecting customer feedback, but not analyzing or acting on it, you could be sitting on a mountain of missed opportunities. Take some time to review your current CX program and see where text analytics can help you get in tune with what your customers want and need.

 


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