What are feedback analytics insights?
Learn about how to analyse your users’ article reactions
HelpKit insights are a great way to understand how your customers are using your knowledge base so that you can learn from it and improve your articles.
What are HelpKit feedback insights?
💬 Feedback insights gives you access to your articles feedback sentiment where you can learn from your users article reactions and their comments.
When a user lands on your help article page they’ll have the option to provide feedback via the feedback box at the bottom of the article. The options show three distinctive emojis indicating a negative, neutral or positive experience.
If the user reactes with a negative or neutral feedback, a feedback popup will show up prompting the user to optionally provide more context and their email address.
In your dashboard, the feedback insights page will look like this:
You can find the two new pages in the HelpKit dashboard by navigating to the new Insights
tab in the top menu bar.
At the moment feedback analytics will provide you with the following data:
Dashboard
- Satisfaction Score: This is the percentage of positive article reactions (users that voted on your article with the 🤩 emoji) out of all received reactions. You can see the same number applied to the
Like Votes
card on the right. The higher this percentage, the better perceived your knowledge base is.
- Total Articles: The number of articles that have received a reaction
- Total Votes: The number of total votes submitted to all of your articles
- Total Comments: The number of total comments submitted to all of your articles
- Like Votes: The absolute and relative number of article reactions that deemed your articles helpful
- Neutral Votes: The absolute and relative number of article reactions that deemed your articles neither helpful nor useless
- Dislike Votes: The absolute and relative number of article reactions that deemed your articles useless
Article Table
The article table displays all your articles that have received a reaction. You can filter based on the reaction’s sentiment as well as the number of received comments. By clicking on the article a dropdown will open that allows you to:
- open the article on a separate page
- edit the article in Notion
- read associated comments
Comments Table
The comments table displays a list of all received comments. You can search and filter through your comments based on:
- Feedback text
- Article title
- Usefulness (Reaction type)
- Email (This is an optional field for users to fill out)
- Creation date
Be aware of review bias
Research suggests that people heed negative reviews more than positive ones — despite their questionable credibility. This means that the number of neutral or negative article reactions might be far higher than those from positive reactions. This can skew your usefulness score.
Last updated on October 11, 2024