What do your customers think about your business?
As a contact center, answering that question with deep insight and accuracy is essential to your success. After all, customers are willing to pay up to 13% more for their products and services in order to enjoy a satisfactory experience. They are also more than happy to share their bad experience with others and warn them away from your business.
The more knowledge you have about your customers’ expectations, the better you can deliver what they need and want. That’s why contact centers can rely on text analytics for customer surveys.
The Value and Challenge of Customer Surveys
Customer surveys help your customers feel valued, heard, and appreciated. They are also an invaluable method of getting daily customer feedback that you can act upon.
With surveys (CSAT, NPS, and more), your contact center can measure satisfaction, gauge expectations, and investigate customer motivation. When done well, you’ll gain an unfiltered impression of the customer experience—both positive and negative. This means you can keep a constant pulse on what your customers think, what they want, and how they feel.
And that’s invaluable information. There are a few challenges for contact centers when it comes to gaining customer survey information, though.
- Few customers will take the time to respond to surveys. Only 1 in 26 customers will actually complain—the rest will say nothing.
- Customers need incentives to talk with you. Survey response rates can fall as low as 2% depending on incentive and motivation or can soar past 85% when well-executed.
- Customers don’t want to say much. To get the best results, surveys need to be as short as possible—data suggests there’s a sharp drop-off rate above 15 questions.
That’s why it’s essential to gain as much actionable insight as possible from every single survey. It would help if you dug deep into their open-ended feedback to extract insight on sentiment, emotion, problems, trends, language, and key phrases.
Leveraging Text Analytics to Improve Customer Survey Insight
According to McKinsey, “organizations that use technology to revamp the customer experience can carve out significant differentiation—increasing customer satisfaction by 15 to 20 percent, reducing cost to serve by 20 to 40 percent, and boosting conversion rates and growth by 20 percent.”
Text analytics software uses natural language processing and machine learning to break down text information for critical analysis.
But, what does that mean?
It means it can help you uncover survey trends you might not realize exist and organize customer feedback into actionable information. It will also help you manage your survey insight because it automatically scans and analyzes thousands of surveys at a time—even mapping results to customer support tickets.
How you use text analytics to transform your unstructured survey text into quantitative data for you to gain insight is up to you. Here are five ideas to get you started.
#1. Listen to ALL Feedback, Not Just Some
One of the biggest mistakes many call centers run into with customer surveys is only reviewing a few responses. Often, there’s only time to read the really good or bad reviews, but this doesn’t give you the entire picture. Even customers that offer a middle-of-the-road survey response can have valuable insight.
The use of Text Analytics and AI allows you to analyze ALL of your customer surveys at one time and parse out information to isolate areas of friction and satisfaction. You’ll uncover real issues with real input from all your customers.
#2 Organize Survey Results and Highlight Trends
With text analytics for surveys, you can organize the results by useful insight.
- You can sort bugs out first—by keyword and volume—and make those issues a high priority.
- You can also sort feedback based on product, service, agent, or feature.
- You can quickly identify areas that are and aren’t working for your customers and make adjustments.
The essential element is finding patterns within your survey results to have actionable data to move forward. Text analytics allows you to get to the true root cause of customer satisfaction or dissatisfaction and see where your problems are occurring and how to solve them. This encourages real positive change for your customers and your company.
#3 Tag Surveys for Proactive Outreach
Customers like attention—it’s human nature. That’s why it’s important to reach out to customers who complete your surveys. If they’re happy, you can reach out and thank them for their time and offer an incentive to remain loyal. If they’re unhappy, you can reach out to help change their minds.
Text analytics offers tagged data to segment your customer surveys based on issues, sentiment, complaints, and more. Then, using these tags, you can build an effective outreach campaign targeted at specific users—notifying them of improvements or personalizing offers in order to stimulate win back and prevent churn.
#4 Build a Better Product/Service Roadmap
Deciding what products and services you should move forward with should not be a stab in the dark. An accurate roadmap requires tough decisions and often painful trade-offs. Should you build a new product or update your current product with new features? Often, it’s a combination of both, and you need continual customer feedback for it to turn out best.
Text analytics analyzes your customer surveys (and more) every week and month to create a to-do list of the most common customer complaints, requests, and problems, helping you to make informed decisions on what comes next. You can analyze:
- Number of survey responses for each request/issue,
- Trends over time,
- Satisfaction score,
- And every other response associated with it.
Armed with this information, you can begin building a roadmap based on real customer feedback, not just a hunch.
#5 Improve Call Center Support Agents Skills
Support is often one of the areas customers most often complain about and celebrate. A lot of information about your call center is to be found in surveys.
However, it requires a lot of completed surveys to understand the satisfaction rating of each agent and identify who needs training and who deserves a reward. Still, the results are not always accurate. After all, agents dealing with difficult issues and unhappy customers might still get negative satisfaction scores even if they handled the situation correctly.
Text analytics can help overcome this issue by using AI technology to automatically read and analyze support tickets and survey results at the same time. Like you would for product and service analysis, text analytics for surveys can help you map topics against ticket volumes, trends, and customer satisfaction.
Ultimately, you'll truly identify your top-performers and those agents who could use some extra help.
Increase the Power of Customer Surveys with Text Analytics
Customer surveys have always been a valuable way to collect feedback on your company’s products, services, and support. They are an essential tool, but without analytics help to pull out every ounce of insight, survey results offer limited scope for learning.
By combining the power of text analytics with your customer survey results, you'll gain far more insight into what your customers think. Each analysis is another opportunity for feedback and insight.
Text analytics opens your understanding of customer satisfaction to a whole new level of understanding that supports change. The possibilities are endless.