How we're using aggregated feedback to improve our mentoring experience
If you've recently or are currently ending your mentorship, you'll see a note that we'd like to use your feedback to improve our mentor's performance. In this article, we'll outline how your private feedback can be used to improve the MentorCruise service, and how we'll make sure your anonymity and privacy are always intact.
How your private feedback helps
Even if you decide not to opt into using your aggregated data, your private feedback is extremely valuable to us.
As we mentioned, the feedback stays between us. Our moderation team uses the data to identify mentors who are underperforming, and the feedback may be a deciding factor in whether we decide to end our relationship with a mentor.
We will never share specific anecdotes or specific feedback with mentors, it aims to solely help our team make the right decision.
How we can use aggregate data
If you allow us to use aggregated data, we can use anonymized data for the following use cases.
AI Feedback
If enough feedback has been collected to the point where anonymity can be guaranteed, we may send pre-processed data (removing all names or other personal information) to OpenAI OpCo, LLC.
This allows us to generate further anonymized and private feedback, only utilizing overall patterns, rather than your specific feedback. Our models are trained and tested by our team and have been ensured not to leak any identifiable information.
The feedback will be displayed to the mentor in a concise report. We have trained our AI prompt to exclude identifiable information and single instance events, and will only display the feedback to mentors if at least 8 other pieces of feedback are available. That way, your anonimity is protected.
Personal Feedback
Should a mentor underperform or be on the verge of being disconnected from MentorCruise, our moderation team may seek a conversation. Aggregate data from private feedback may help the team communicate patterns that the mentor needs to improve on.