How to extract keywords from Delighted NPS Survey Comments using generative AI
How to Extract Keywords from Delighted NPS Survey Comments using Generative AI
Are you struggling to find valuable insights from your Delighted NPS survey comments? Don't worry - you're not alone. Many companies struggle to identify important themes and trends from their customer feedback. In this post, we'll show you how to use generative AI to automatically extract keywords from Delighted NPS survey comments.
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 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 Delighted NPS survey comments include:
- Identifying common themes and trends in customer feedback
- Improving product features and functionality based on customer feedback
- Personalizing customer interactions based on feedback
- Identifying areas for training and improvement in customer service
Teams that might find these use cases helpful include: product, customer success, marketing, and operations.
Finding your input data and identifying preliminary keywords
You first need to identify the data that you want to work with. Here, we are looking at Delighted NPS survey comments. You can extract this data using the Delighted API, export it in CSV format, query a list of comments from your data warehouse or BI tool, or copy and paste with an example comment.
For more information on the Delighted API see here: https://delighted.com/docs/api
Next, it can be helpful (but not necessary) to identify common keywords that you may want to extract from your Delighted NPS 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 comments around a particular product feature may provide insights into product improvement opportunities non-obvious to the initial comment.
Once you have your data and preliminary keywords identified, you can use generative AI to automatically extract keywords from your Delighted NPS survey comments. This will help you identify important themes and trends in your customer feedback, and improve your product and customer service accordingly.