The contact center is the beating heart of every organization. It’s at the forefront of customer interaction. And since your customers generate revenue and build your business, gaining insight into what they need, want, and enjoy is critical. That’s how text analytics works in the contact center.
Text analytics supports your business by automatically analyzing all open and free text to determine customer feedback—based on the issues they want to discuss, friction, and sentiment. This analysis provides an in-depth understanding of your business from the viewpoint of your customers—the individuals who matter most to your success.
How Text Analytics Works to Improve ALL Business Initiatives
When used correctly, text analytics in the contact center is pivotal to business change and business improvement. After all, every department can benefit from knowing your customers better. But who exactly has a stake in the insight garnered through text analytics?
Let’s take a look at some text analytics use cases and their potential impact on your business.
Contact Center Teams Discover What Drives Customer Activity
What drives customer activity in your business? This is critical information for customer service managers, call center supervisors, QA managers, marketing leads, and product teams. Every department can benefit from greater customer feedback.
How text analytics works is through AI that automatically tracks and analyzes all unstructured text from customers. This approach uncovers keywords, topics, and customer sentiment trending in the contact center. You’ll then learn if you have a problem, how often it occurs, and what can be done to fix it.
Each department can request to keep track of the customer activity most important to them. For example:
- your marketing team can track customers talking about a new promo code;
- your product team can track the new product/service update;
- and your call center can track overall customer sentiment, the most common issues in customer support, and customer satisfaction.
QA Managers Detect Training Opportunities
What if you could find areas where your agents are failing or succeeding in their duties? This is essential for QA management, and yet it can be extremely difficult to uncover knowledge gaps that actually impact the bottom line. But with text analytics, your QA team can detect training opportunities and root causes by only auditing conversations worth the effort.
Instead of auditing random interactions, text analytics can highlight topics, problems, and complaints that occur regularly and then provide conversations to audit that match those areas. You can also pick conversations based on friction—customer topics that correlate to long and extensive interactions. In both cases, QA managers gain insight into agent training opportunities based on known problems.
Product and Sales Teams Gain Critical Feedback on Products and Services
Most product and sales teams rely on product and service surveys to understand their customers. The problem is that this isn’t very efficient. Maybe 10% of customers actually respond to surveys, and then their responses are limited to the questions asked. This means that many bugs, issues, and requests get missed.
Customers come to contact centers with feedback on features, new product questions, bug fixes, and more. With text analytics, your product and sales teams can gain insight into what the customer actually cares about in their own words.
Using artificial intelligence, text analytics analyzes every customer support ticket, email, and chat message to provide a product/service roadmap. You’ll get feedback on everything from specific frictions to trends in feature requests, bugs, and even what features your customers love and can’t live without. It’s the best way to take your design and development to the next level.
Marketing Teams Track Marketing and Messaging Success
It’s easy to calculate the cost and benefits of quality customer support, but the success of customer outreach can be more difficult to track. When your company rolls out a new promotion or marketing message, how do you know if it’s working as it should? Text analytics can highlight marketing issues and even track how often customers mention their outreach efforts when they contact support.
With insight into text data, marketing teams can be informed about the impact of their efforts across platforms. They can track keywords such as “summer special” or “promo code 1234” or keep track of more general terms such as “social media” or “video” to see what customers are talking about. It’s a great way to find problems or see if customers respond well to discounts, specials, or promotions.
IT Teams Uncover Website and UX Issues
You know that customer-centric design is critical to success. But uncovering if your website and UX are actually customer-centric requires lots of feedback; more than most IT teams receive. The good and bad news is that customers love to complain to contact centers about issues. And with text analytics, website and UX complaints can be easily shared with IT for quick fixes.
IT teams can use text analytics to track known issues by keyword or uncover new issues from customer trends. They can even track specific problems to see when they appeared and when they were solved. In this way, they can perform A/B testing to see if the update to the website worked well or created another issue. This insight can be used for everything from payment systems to improved navigation and better customer engagement.
Text Analytics Drives Positive, Important, and Realistic Business Changes
The contact center should not operate in a silo; they understand customers better than any other department. The key is sharing that information across the business, and that’s where text analytics is invaluable. It provides an in-depth understanding of your customers’ needs and wants directly from their own words.
You’ll learn issues as they relate to products, services, customer support, IT, sales, and marketing, so you can drive business change and business improvement across the board. Text analytics is all about learning what drives your customers and then using that information to make informed business decisions.