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As a matter of fact, a customer experience is qualitative and emotion-based. But why are companies obsessed with turning it into a quantitative measure?

Whether they measure Customer Satisfaction, Customer Effort, or Net Promoter Score, they want to track a number. We know tracking these scores can highlight the need to improve weak areas, but the numbers alone won't offer the insight you need to make improvements. 

Many companies rely on these scores because they don't have time to analyze them more in-depth. So, that's where text analytics come into play!

Text analytics software lets you gather and analyze insights from thousands of open-text customer comments. This guide will show how text analytics help improve customer experience in an easy-to-understand way. Let's explore!

The Importance of Text Analytics Nowadays 

Text analytics can identify new insights and meaningful patterns by transforming unstructured text into structured data. According to Allied Market Research, the global market size of text analytics is expected to reach $29.42 billion by 2030, growing at a CAGR (compound annual growth rate) of 17.8% from 2021 to 2030. 

Any business that wants a superior customer experience should utilize text analytics for mining customer feedback and complaints. If you don't regularly assess the qualitative data of what customers like or don't like about your products/services, you'll find it challenging to deliver that superior experience. 

Here are some benefits of text analytics:

• Provide objective results - It's easy to introduce bias or make mistakes when you manually analyze data, not to mention the amount of time you might have to spend looking at feedback one by one. With text analytics, the process is objective, meaning you'll get the same results no matter who looks at your data. It's essential when you need to make data-based decisions that can affect your business. 

• Collect scalable feedback - It becomes a burden if you receive dozens or hundreds of feedback at once. Text analytics allows you to analyze customer comments in a scalable way. 

• Turn unstructured text into insights - Text analytics simplify the analysis of survey results and help you get the most out of the data you've collected. 

5 Ways To Improve Customer Experience With Text Analytics

1. Immediately solve customers' issues

What issues are your agents struggling with in particular?

Are your customers facing any recurring issues that your company needs to fix?

Does your FAQ (Frequently Asked Questions) page match the questions that customers most frequently ask?

Text analytics help you answer all of these questions. Real-time AI (artificial intelligence) will automatically detect and analyze the volumes and trends of your customer's problems and queries. You can make better decisions about how best to help your customers.  

For issues that can't be resolved immediately, you can use topic and sentiment analysis to categorize problems and implement relevant actions. For example, you can reference relevant people or departments to the customer and automate sending emails to both parties. This action helps customers feel their issues will be dealt with instantly. 

This approach works better when compared to a standard survey form, where customers might enter a complaint and get nothing back at all. For example, you can integrate text analytics into daily employee workflows, ensuring a smooth customer experience. 

2. Detect hidden trends early 

With the rise of social media platforms and other digital channels, customers share their daily lives more and more online. This abundance of data can help you identify emerging trends. Uncovering these trends provides you with new opportunities and an edge against competitors. 

Text analytics serves to ingest a considerable amount of online data, then identify customer trends or emerging businesses that could threaten your business. It's beneficial if you are about to launch new products or services, and it helps you understand the data scientifically and bring out accurate insights. 

3. Set priorities quickly and efficiently 

Customers always expect timely, personalized, and effective customer service interactions. However, it's challenging if your business falls short of resources and efficient workflows to handle all queries. Manually managing tickets and routing them through the right agent is time-consuming and error-prone. 

But text analytics can automatically categorize tickets and assign them to the most appropriate agent. Furthermore, with sentiment analysis, text analytics can determine the urgency resolution and prioritize tasks based on the tone of customer communication. 

4. Gather customers' feedback on products/services

Let's say you conduct a survey to check on customers' satisfaction with your products. You're particularly interested in exploring what they think about your new cost. If you receive hundreds of responses, it's tough to read them one by one-it'd take too long, and you'd risk discrepancies in the outcome due to human error or bias. 

Instead, determine the keywords you want to concentrate on, such as "price" or "cheap," and discover which issues or topics your customers discuss concerning your products.

With text analytics, you'll quickly have an overview of what customers think. Simply use the answer filter to show responses that include a specific answer to your chosen question. Text analytics is super helpful in gathering and filtering data, especially when up to 80% of text collected by companies is unstructured. 

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5. Improve your customer support operations

Imagine you sent a customer satisfaction survey to customers. By analyzing their feedback within each response and follow-up exchange, you can see how team members perform in relation to customers' interactions. It's key to improving the quality of your staff over time. 

All you need to do is include a merge field track to note the case owner's name and see which agent worked with which customers. Then, when customers click on your survey link, it'll auto-populate their case owner's name together with their details in the background. 

In short, by auto-examining your customer text interactions, text analytics can help you:

• Promote self-service opportunities - Analyze trends in customer issues to determine what FAQs are most common. 

• Automate your helpdesk - Text analytics can use AI to trigger automation in your helpdesk.

• Better route customer inquiries - Automatically classify the support ticket and assign it to the most appropriate pool of agents. 

• Prioritize tickets depending on query type - Clear your backlog to prioritize tickets.

Conclusion

Delivering an outstanding customer experience is more than just replying to emails or answering calls. It involves looking through different layers to understand what a customer really wants and expects. By using text analytics, businesses can dig deeper and evaluate the said and unsaid to bring out the right insights.