Text mining helps improve support efficiencies
As a support manager of a medium-sized organization, you probably receive a large volume of customer comments. Most of you would also probably agree that it takes a substantial amount of manual effort to read, understand and respond to all of these requests. That’s where text mining comes in.
Text mining tools help boost customer satisfaction
Text mining tools turn support centers into insight centers:
1. Analyzing customer interactions and emotions: Sentiment analysis, is a text analytics technique used to determine the tone and polarity of customer expressions.
Here’s an example of a negative customer reaction:
I am really disgusted with Hotel A, when I got to my room it smelled like cigarette smoke and I specifically asked for a non-smoking room. I was also really upset because the bathroom floors were really dirty. It’s listed as a 4 star hotel online, but I disagree. I am never staying there again.
For support centers, customer comments, like the one above, become direct windows into how your customers feel about products, or how satisfied they were with the service they received. A hotel manager can now take immediate action to improve the overall cleanliness of it’s hotel rooms and ensure specific customer requests are respected.
2. Identifying problem areas and suggestions for solutions: Feedback from call center logs, or live chat conversations can provide actionable insights for future product requirements.
One such example:
Hello, I bought a baby seat from your company a week ago but I was disapointed because the built-in seatbelt was really hard to adjust. The belt buckle kept getting stuck and it was really hard to close.
Prioritizing product requirements is a very important step in the product development process. Here we product feedback that could help us make improvements to new product features and more importantly to the quality of the products produced.
3. Assess agent performance and service quality:
Here’s an example of a possible customer comment:
Company A kept me on hold for 15 minutes! They didn’t even fix my problem! Next time i’ll save myself the trouble and shop online at Company B.
Armed with this insight a support manager can take appropriate action to reduce call wait times and improve issue resolution rates. In addition, it’s also apparent that your biggest competitor offers consumers the option to shop online.
Text mining produces bottom line business results
Since they are often on the front-lines, support teams are at the core of an organization’s information gathering strategy. It’s clear that the insights obtained from customer comments can help reduce customer churn, and improve call center operations. Moving forward, businesses should look for more effective ways of integrating text analytics tools into their existing support process.