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You already know a lot about your customers. Every time they call your contact center, live chat with an agent, send an email, submit a help ticket, or fill out a survey, they provide you with helpful feedback. They’re telling you what works, what they think needs to be fixed, where they’re confused, and what they want more of.

You just need to listen! And it would help if you listened to all of it because only one out of every 26 customers is likely to bring up their complaints, and 72% of customers will share a positive experience with six or more people. So, you have to listen and listen carefully. Still, you also have to analyze what your customers are saying to truly take advantage of customer feedback and improve the customer experience in measurable ways.

And that’s where text analysis of customer feedback is invaluable.

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The Importance of Customer Feedback in the Contact Center

There’s no doubt that customer expectations are at an all-time high. Customers expect brands to respond more quickly, offer more personalization, and demonstrate more empathy than ever before. They hope to walk away from every interaction feeling positive. That’s why, for 96% of customers, customer service is essential for brand loyalty.

And the benefits of improving the customer experience cannot be overstated.

But for your brand to provide an exceptional customer experience, you have to know precisely what your customers want and need. It’s not only essential to gain customer feedback in any way possible, but then you have to put all that data together in an easily understandable way that can help you make informed decisions.

How Text Analytics Can Improve Contact Center Performance

Gaining and analyzing all customer feedback can be immensely time-consuming and laborious if done manually. But text analytics changes all that by using AI and machine learning to do the hard work for you.

With AI text analytics, your contact center can automatically read, analyze, and translate every piece of customer feedback into an actionable format that managers, supervisors, and agents can use to make your customers happier. Here’s how it works:

Identify and Fix Issues

Your customers are constantly telling you what is wrong and where they can use your help. You just have to gather all that insight, divide their issues by topic, and analyze areas where improvement is needed. From there, you can create more accurate knowledge bases, provide better agent training, tell R&D where adjustments need to happen, speak to sales about pricing issues, and more.

And since contact center text analytics uses your customers’ own words to dissect each issue, you can focus on those areas that truly matter most. There’s no guessing about what type of “shipping problem” is being discussed. Text analytics will break down exactly where shipping is struggling so you can make specific adjustments to increase customer satisfaction.

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Uncover Trends for More Efficient and Effective Customer Support

Most customer support is reactive. It focuses on responding to a customer after they’ve contacted you. But proactive support and engagement go above and beyond to stop customer frustration before it starts.

With AI and natural language processing, text analytics can uncover trends and volumes in the contact center. What this means is that you can adjust the experience to better support your customers by:

  • Prioritizing self-service opportunities based on the most frequently asked questions.
  • Routing customers to the best agents during peak periods for faster and more efficient support.
  • Automating your help desk with AI-triggered customer support.
  • Prioritizing support tickets based on the query and your best-trained agents.

Analyze Customer Sentiment in Real-Time

Text analysis intelligently scores every customer interaction for sentiment using natural language processing to identify keywords and text structures that reveal customer opinions and emotional behavior. And by analyzing how your customers feel when they contact you, you can adjust your support to provide a better experience.

You can even set up real-time alerts on the quality of the customer experience. For example, you can set up notifications in conversations where politeness isn’t detected or empathy is lacking. Then, post-interaction, you can perform a more detailed analysis to see how sentiment evolved throughout the conversation and to determine if your agents made the experience a positive one.

Provide Proactive Agent Training, Coaching, and Recognition

Once you identify which issues most affect your customer experience and uncover trends in high volume issues, text analytics can also help you understand agent performance in these areas. It allows you to connect the customer experience to agent interaction and determine if your support is satisfactory.

With contact center text analytics, you can identify agent knowledge gaps and star-performing agents through detailed analysis. You can then combine this data with CSAT, response time, and first contact resolution to proactively train and coach your agents to get their best work. Deeper insights into agent performance will help you provide rewards for a job well done and additional training for areas of concern.

Leverage Text Analytics for Better Customer Experiences

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The more insight you have into the customer experience, the better. It’s only by understanding all customer feedback—whether shared on social media, sent in an email or mentioned in chat—that you can genuinely exceed expectations in every interaction.

The key is allowing your customers to say what they want; however, they want to say it. Then using text analytics to gather, organize, analyze, and translate this feedback into action items for improvement.

When you let AI and machine learning do the heavy lifting of understanding customer feedback, you must sit back and implement the changes to get results.

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Positive customer experiences are the key to a thriving contact center. Download our free e-book to discover call center customer experience best practices to improve your customer experience strategy.

 

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