A knowledge base is a collection of information that can be accessed by different users for various purposes. It can be used externally by customers or prospects who want to learn more about a product or service, or internally by employees who need to find answers to common questions or problems.
Discover (powered by SupportGPT) provides a very easy way to create a knowledge base, leveraging your customer support interactions, such as emails, chats, calls, surveys, etc., to create relevant and useful content for the knowledge base. It can identify topics with knowledge gaps and generate draft articles you can publish to your knowledge base.
- Articles generated by Discover align with the actual needs and expectations of the customers, and reflects their language and tone.
- Articles can be updated on a regular basis, based on your interactions between valued customers and knowledgeable support agents.
- Saving costs and resources by reducing the workload of support agents. Reduce time for content writers to write and publish relevant support articles.
- A good and extensive knowledge base improves customer satisfaction and loyalty by better enabling self-service options across channels and providing better customer experience.
- Sales and conversions can be increased by educating potential customers about the features and benefits of the product or service, and addressing their objections or concerns.
- It also enhances employee productivity and efficiency by reducing the time spent on searching for information or repeating the same tasks.
A good knowledge base is an important asset for a company that can improve both external and internal outcomes. By leveraging articles generated using customer support data, create a knowledge base that is relevant, useful, and engaging.
Discover Dashboard
A notification at the top shows the number of articles SupportGPT has generated. Clicking on View all generated articles takes you to Discover → Automation → Knowledge gap
Discover Automation
Clicking on Automation in the left menu and knowledge gap gets you to the following screen.
The banner at the top shows how many articles were generated for the gaps detected and the number of tickets covered by these generated articles.
Each card shows you the number of tickets this can article can help address in the identified ticket.
Click on view article open the article in the Topic view
Discover All Topics
In all topics page, the following icon helps you identify topics for which SupportGPT has generated articles.
Clicking on the article icon takes you to the Topic View → Generated articles
Discover generates two types of articles
1. When Discover detects a gap in the knowledge base, then it generates an article.
2. Even if discover detects no knowledge gap, but identifies that it can generate a good article for the topic, it generates one.
To identify if an article is generated for a gap or not you can look at the article generated icon.
This icon indicates article is generated where a knowledge base gap has been identified.
This icon indicates article is generated but no knowledge base gap for the topic has been identified.
Discover: Topic View Page
On topic view page, when you scroll below the metrics, you have two tabs Tickets and Generated articles.
Click on Generated articles to see the list of articles SupportGPT generated
Click on the article to see the generated article.
You can upload the article as a draft to your help desk for further editing or you can copy the generated article to your clipboard and paste it to a tool of your choice for further editing
To upload the article, click on upload and to copy yhe article click on copy.
Select the integration and the necessary options and click upload as a draft.
How can you give feedback on the article?
Every article has a 👍 or 👎 option.
Clicking the 👎 should get you a screen for additional feedback that can help improve the articles for you.
Frequently Asked Questions
Q) How does Discover ensure articles are contextual?
A) Discover leverages the interactions between a user and an agent to generate the articles. This ensures, the article is very contextual and is leveraging your customer support data to generate the article. Articles generated using this method are more accurate and relevant to solving the user queries.
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