How to extract keywords from HappyFox CSAT Survey Comments using generative AI
How to Extract Keywords from HappyFox CSAT Survey Comments using Generative AI
As a company, you want to stay on top of your customer satisfaction rate. HappyFox CSAT surveys are a great way to gather feedback from your customers. However, analyzing each and every comment on these surveys is a daunting task. In this post, we’ll show you how to use generative AI to automatically extract keywords from HappyFox CSAT survey comments, making it easier for you to identify important insights.
What is Keyword Extraction?
Keyword extraction is a natural language processing (NLP) technique that involves identifying the most important or relevant words or phrases in a piece of text. You can use it to extract key information and themes from text that has many applications, such as search engine optimization (SEO), content analysis, and topic modeling.
Keyword extraction can be performed manually, but it can also be automated using machine learning algorithms. These algorithms learn to recognize patterns and features in the text that are associated with important words or phrases, and can be trained on a labeled dataset of text.
You can use keyword extraction to analyze and summarize large amounts of text data to quickly identify the most important information and themes.
Example Use Cases
Use cases for extracting keywords from HappyFox CSAT survey comments include:
- Identifying common issues and trends in customer feedback
- Improving response times and customer experience
- Identifying areas for training and improvement in customer support teams
- Spotting opportunities for product improvement based on customer feedback
Teams that might find these use cases helpful include: customer support, customer success, product, marketing, and operations.
Accessing your HappyFox CSAT Survey Comments and Identifying Preliminary Keywords
You first need to identify the data that you want to work with. In this case, we are looking at HappyFox CSAT survey comments. You can easily access these comments through your HappyFox account. Export the comments in CSV format, query them from your data warehouse or BI tool, or copy and paste with an example comment.
Next, it can be helpful (but not necessary) to identify common keywords that you may want to extract from your survey comments. Generative AI tools can be used to both identify and measure frequency of keywords but also to suggest additional keywords you may not have been aware to look for. For example - you might find that recurring customer inquiries around billing may provide insights into product improvement opportunities non-obvious to the initial support inquiry.
Once you have your data and preliminary keywords identified, you can use generative AI to automatically extract keywords from your HappyFox CSAT survey comments. This will help you identify important themes and insights from your customer feedback quickly and efficiently.