Identify Content Gaps in your FAQs and Chatbots with Semantic Clustering
Discover gaps in your content, improve your self-service and enhance your users’ experience thanks to our semantic clustering functionality.
What is semantic clustering?
Semantic clustering is the process of grouping search queries that are similar on a semantic level into clusters based on meaning.
What are the benefits of semantic clustering?
Semantic clustering enables organizations to discover gaps in their content.
Companies can leverage this functionality to identify missing content and add additional answers and information to ensure that their customers can find the information they are looking for quickly and easily, without having to raise a support ticket.
Thanks to our semantic clustering tool, companies can fill these content gaps by adding content in their knowledge base, enabling them to provide instant support to their users, thus enriching customer experience and increasing customer satisfaction.
How does semantic clustering work?
When users can’t find the information they’re looking for or their search results in an unsatisfactory answer, they react negatively. That translates into users not clicking on the answer that has been provided, leaving a bad evaluation or feedback, leaving the page, or getting in touch with you through another channel.
This indicates that the user either did not receive an answer or that the answer provided was not precise enough or incorrect. It is a good indicator that some valuable information is missing and consequently needs to be created.
Inbenta semantic clustering functionality can:
✓ Identify these negative signals.
✓ Map all the orphan questions that did not receive any answers or unsatisfactory ones.
✓ Analyze the content thanks to our powerful Natural Language Processing technology.
✓ Group them into clusters based on meaning and similar intents.
Example of semantic clustering at work
Let’s take an airline company such as GOL Airlines for example. They might receive a certain number of unanswered queries regarding the time gates close for boarding. As humans have different ways of asking the same question, they could phrase it as follows:
“What time should I arrive?”
“When do gates close?”
“Boarding time”
All these queries use different words, but the intent behind them is the same: find an answer about what time gates close for boarding. Inbenta’s semantic clustering functionality will group all these unanswered questions into one cluster with the same meaning, essentially when the passenger should arrive at the airport for their flight.
When analyzing their search or chatbot results, the company will be alerted to the fact that crucial new material needs to be created in order to answer their customers’ questions.
Are you ready to bring your content to a whole new level?
Try our semantic clustering functionality for yourself for FREE or get in touch with us to arrange a demo.