Customer service 101: well-trained contact center agents. They are your first point of contact and the individuals most directly responsible for customer satisfaction. 31% of customers say that “a knowledgeable customer service representative” is essential for a good experience.
The problem is that not all call center training is up to developing knowledgeable agents. And that’s mainly due to a lack of insight into why your customers are contacting you and what issues they are most frequently calling about. While your contact center might monitor calls, track CSATs, review first contact resolutions, and examine other KPIs, it’s not enough. Without text analytics tools to help you dig deeper, there’s a whole range of customer issues that could be going unnoticed.
Text analytics uses AI and business intelligence to help you review 100% of customer text interactions automatically. You can check every customer query to understand what’s happening within your contact center and the customer experience. It’s all about making better and faster decisions based on insight garnered from unstructured data such as text, tweets, posts, support tickets, and emails.
Here are five ways text analytics tools can be used to:
Does your contact center waste valuable time and energy answering the same simple query repeatedly? Unless you review every customer support ticket, email, and live chat, you might miss common simple questions that would be better served by an FAQ or a Knowledge Base rather than your agents.
With text analytics, AI automatically tags every text-based interaction and divides them by topic or issue. You can delve into high-volume queries to uncover trends in customer questions and create FAQs based on that insight. You will save your agents time, but you’ll also ensure that your agents have this information at the tip of their fingers to use in conversations and to point customers to for further help.
For example, with text analytics, you might discover that 15% of all your customer queries are about “returning or exchanging a product.” Then, upon further research, you find that most of the questions need only basic information about the process of returning or exchanging a product? You can create a Knowledge Base—both internally and externally—to more quickly resolve these issues, fill in any knowledge gaps, and increase customer satisfaction.
Do your agents need sales, product, or soft skills training? What customer queries come into your contact center the most? Your training should match your needs and not the other way around.
With text analytics tools, you don’t have to guess what topics are most important to your success as a contact center. Instead, you can quickly uncover the volume trend of issues and detect spikes in contact drivers. You can then continually monitor these issues and read what customers are saying.
You can develop your training plan to match the type of queries that your agents deal with day-in and day-out—and being as specific as possible in your training results in better first contact resolutions, greater efficiency, higher productivity, and more prepared agents.
It’s not enough to know why and how your customers are contacting you; you also need to understand agent performance. And that means understanding what customer queries your agents struggle with the most and thus where more training is required.
With text analytics, every customer query can be reviewed and analyzed, but you can also monitor every agent's response and result to reveal if or when someone is struggling. You can see what types and topics of tickets each agent answers the most, how long it takes if the customer had to contact you again for more information on the same issue, and more.
You can provide additional training on the issues where they struggle to maintain a high customer satisfaction score and bring them up to par.
Just as you can uncover knowledge gaps, text analytics can also help you identify star-performing agents. AI automatically reviews every text interaction to provide you with detailed analytics and a customer satisfaction score for each agent. To find your star agents, you can then combine this knowledge with your other customer support metrics, such as CSAT, response time, and first contact resolution.
If an agent performs exceptionally well, you can then provide rewards for a job well done, ask them to mentor their fellow agents, assign them the most complicated customer interactions, etc. The key is that text analytics tools help you mitigate risk by uncovering which agents can best handle which queries for better routing.
Every contact center manager struggles to analyze large volumes of customer queries to uncover trends. This means that it’s hard to discover what customer issues take up most of your time. This is where text analytics AI comes in. It will give you all the details you need on hundreds of thousands of queries.
For example, you might discover that your customers regularly complain about print issues from their reporting screen. Upon looking further, you can figure out who’s at fault for the problem: a bug with the button, insufficient user permission, or general outages in the cloud. From there, it’s feasible to train your agents on how to solve these problems or get IT to make a simple fix.
You can quickly connect customer queries to time-consuming issues and then do what’s needed to provide better support. And because text analytics tools can get so granular, you can make specific adjustments.
Knowledge is power. The better you understand everything that’s happening in your contact center, the better you’re able to come up with approaches that make sense and result in customer satisfaction.
You can automatically review all unstructured text data with text analytics tools and pull out critical insight for agent training. This saves you time, increases productivity, improves agent engagement, and enhances customer satisfaction.