But how does text analytics actually work in CustomerGauge?
CustomerGauge’s Text analytics covers both topic and sentiment analysis.
- Topic analysis categorizes customer comments into business-relevant topics. For example, “our account manager is really supportive” would be categorized under the topic of “Account Management”.
- Sentiment Analysis allows you to determine the sentiment - positive, negative, neutral, or mixed - of a customer comment. One of the best uses of sentiment analysis is the ability to get to the “feeling of a comment” without having to read every single comment.
How can you get started with Text & Sentiment Analytics?
Based on your industry, our Text Analytics functionality provides you with an industry-specific training library such as IT, Retail, Financial Services, etc. If you don’t fall into one of our standard industries, you also have the ability to upload a custom library that is specific to your organization.
In either case, as soon as there is a completed survey with a comment, the CustomerGauge system will automatically categorize those comments into topics for you. That way you can focus on analyzing your results and improving the customer experience based on the most emerging topics.
The way this works is through a pattern-matching algorithm that assesses your comments and the likelihood that they are associated with one or more of your topics. Here’s a visual example of how the CustomerGauge system automatically categorizes comments into topics following a survey completion:
1. The survey is submitted with a comment in the comment box
2. The comment box carries the following text: “Have been having problems with the tool lately, particular functions do not work.”
3. Based on your industry, our functionality will automatically categorize “product” as topics for this comment.
Report on the results
4. You can then quickly analyze topic results and their frequency in the CustomerGauge system - that way you can easily understand which topics are emerging and need your attention.
5. We’ve also provided the option to link NPS and Topic frequency - the image below shows the topic of “Product”, its frequency in customer comments (36), and the NPS of these 36 surveys (33). In other words, from these 36 survey comments that were assigned the topic "Product," the overall NPS of "Product" from these comments was a 33. The further to the right the topic dot is, the more it was mentioned by promoters.
6. You can track your sentiment analysis here as well, in the event that the comment carries a sentiment that doesn’t necessarily correspond with the NPS given by the respondent – for example, a promoter who writes a comment complaining that support is too slow. Sentiment analysis will automatically register this as a “negative” sentiment and save your team time from having to read the entire comment or ticket to understand if something needs to be acted upon quickly.
View the entire list of reporting options and how to set them up here.
Enrich the Reporting Labels with Your Terminology
We also understand that customers in various businesses may use more diverse terminology than what our standard industry libraries offers. For example, instead of using “Account Management”, some businesses may use “Customer Success Team”. As a result, we’ve made it easy for you to provide us with the Reporting Labels you’d like to use for topics without affecting the accuracy of results, just the name given.
Turn on Keyword Recognition
We realize that your customers might know your products and services in more detail and they may provide more specific feedback in the comment box.
For example, instead of saying :
“ Your product is great, but I would prefer for your support team to respond faster.”, a customer might say:
“Your Delivery Manager is great, but I would prefer for your CSM team to respond faster.”
To make sure you are fully supported with text analytics, we’ve also added an option to set up Keyword Recognition - you can provide us a list of relevant keywords you would like to see tagged along with the topic. There are some considerations to keep in mind when setting up Keyword Recognition that are covered in more detail in this support article.
Keep your Library updated
If you need to make improvements or updates to your library, our CustomerGauge team can help you with this.
You can add new topics or new example comments for existing topics to your library and also make corrections to existing comments to help train the library for the future by working with your Customer Success Manager and providing a very simple Excel file or two.
Your Customer Success Manager can also help you "promote" certain comments that you feel the system did a particularly good job of assigning topics to. By doing this, you are helping to train the library further so that it becomes even more likely to identify similar comments in the future and apply the same topic(s).