Understanding User ratings
At Headstrt, we believe in empowering users to share and learn from each other on a global scale on countless topics, anytime they like in the most personalized way possible. While we have the luxury of several motivated, creative, empathetic & progressive users on our network, taking an empirical approach to mentee/mentor performance almost always benefits everyone. While selecting or deselecting users for partnerships will be decision-based on several factors, at Headstrt we are of the view that Ratings & Reviews will almost always enhance the decision making for requesting partnerships at Headstrt and will motivate the entire network to do their level best, as performance will now be linked to better business/growth opportunities in future.
Only users who have partnered with each other over Headstrt sessions will have the opportunity to rate each across a variety of cuts and leave private reviews for each other towards the conclusion of every session on the Headstrt platform. We are exclusively enabling feedback from users who have completed sessions at Headstrt to leave Ratings & reviews, to make sure that interactions outside Headstrt or personal networks don’t bias/inflate ratings/reviews for users, and as platform we are able to serve our network with as accurate a data point as possible on ratings.
Each Mentor will be getting rated by every Mentee they have partnered with, over a Feedback, Micro-Mentorship, Consultation, Sharing Experiences session. The objective is to help the Mentor grow faster as a coach and benefit from unbiased feedback from a skilled, diverse and demanding audience. We would like to see our Mentors not just to walk out with cash, but also with valuable mentoring skills and a larger network. Below are the 6 sub-parts of Mentor ratings:
Empathy: Empathy towards problems and situations that matter to a mentee, does establish a better rapport with the mentee.
Command over situation: Mentees, in general, prefer working with Mentors who are able to quickly grasp the situation with the help of Active listening and asking pertinent questions back to the mentee to develop a better sense of the situation.
Transparency & Accuracy: Mentees are much more satisfied to work with Mentors who are able to demonstrate the expertise & knowledge they claimed on their profile. How much did you live to your promise?
Going Above & Beyond: Mentors who go out of their way to help the learners get much stronger reviews and repeat partnerships from the same learners. How dedicated did your mentee find you for this session?
Competency: Expertise attracts future revenue and creates a solid value add for the mentee. How resourceful did your mentee find you?
Recommending Mentor: How excited is your mentee to introduce you to fellow learners in their network?
Based on the above components, we will calculate a simple avg from above to arrive at aggregate ratings a Mentee has shared for the Mentor. So a Simple Avg(4, 5, 4, 4, 4, 3) from 1 session, will produce 24/6 or 4.0 Rating for that session. Over time we will keep adding scores from every session to this total and divide it by Number of Sessions multiplied by 6 to arrive at aggregate rating. So
Aggregate Mentor Rating = Sum(All Individual Ratings for all parameters) / ((Number of Sessions) * 6)
In addition to ratings, we also encourage Mentees to leave a private review for the Mentor, which Mentors are welcome to publish on their profile. Publishing a mentee review is solely at the discretion of the Mentor and Headstrt takes a disinterested stance when it comes to encouraging users to publish the same for their profile.
We feel compelled to display Mentor ratings to better guide Mentees with their selection. Headstrt wants to empower users with the relevant data to help them make the best decisions for partnerships, and provide an empirical score to Mentors so that they could better prioritize their areas of improvement. Ratings ultimately would also help decide if a Mentor is eligible to get compensated for their help at that point on Headstrt marketplace.
Each Mentee will be getting rated by every Mentor they have partnered with, over a Feedback, Micro-Mentorship, Consultation, Sharing Experiences session. The objective is to help the Mentee grow faster as a learner and benefit from unbiased feedback from a skilled, diverse and unbiased audience. Below are the 6 sub-parts of Mentee ratings:
Sincerity & Attitude: This is about how diligent, humble & concerned your mentor found you for this session. In general successful mentors prefer to work with mentees who are deeply invested in the situation at hand and are more coachable.
Transparency: Mentors, in general, prefer working with users who are honest about ground realities and can demonstrate a fact-driven approach.
Pertinent Conversation: Mentors are more engaged when mentees drive the discussion around the initial ask as that matches the Mentor’s agreed value add and interests.
Realistic Goals: How pragmatic was the goal set by the mentee for this discussion, fees, and cadence. Ideally, a good balance b/w attractive value add from the session and being realistic for the mentor drives a happier ecosystem for our marketplace.
Utilization to potential: How successful were you in terms of harnessing the mentor’s intelligence to their fullest for this session?
Recommending Mentee: How excited is your mentor to introduce you to his networks based on this session?
Aggregate Score on Profiles
While Mentees and Mentors are rating each other across different parameters, we work to project aggregate Mentee & Mentor Rating scores for every user based on ratings they receive from Mentors & Mentees over time. These are scores that we would be displayed on their profiles to aid decision making for other users to partner with them. A comprehensive summary of underlying components that make up those aggregate scores would be visible to each user so that they are able to better appreciate what factors they are doing good at and what factors they could possibly invest in improving on. Our vision is that this breakdown will empower all users to grow their skills at points where they matter the most.