Tutor Learner Connect App
SikshaMitra
Embedded Files
Project Overview
Project Overview
User Research and Empathy Study
User Research and Empathy Study
Insights from User Research
Insights from User Research
User Journey Map and Empathy Study revealed that
💡Tutors who have profiles on existing product, post creating profiles become dormant after initial weeks unless some leaner contacts them.
💡Users from 2 and 3 tier cities who are potential users are mostly not using these products
💡Hesitation due to lack of technical proficiency
💡Language barriers
User Persona
User Journey Map
Need for engaging more Tutors
Almost all products in market have designed features such that focus is on learner user segment, tutors are charged for advertising but do not have good engagement. Missing the insight that “better engaged & dedicated Tutors will engage Learners better” , as one of the users put it.
User Friendliness
Applications currently need to improve their Accessibility , in terms of making it more user friendly, simple to use, addressing challenges such as language barriers, using iconography, screen readers to convey information easily
Lack of Engagement
Most of the Apps do not have good number of engagement options for Users like, community pages, social media/external media connect for recommendations and drawing in more interested crowd
Key Insights into User Pain Points
Key Insights into User Pain Points
Ideation
Ideation
Potential Solutions and Features Proposed
Potential Solutions and Features Proposed
Product Design Action-ed based on User Insights
Product Design Action-ed based on User Insights
Based on the Empathy Maps and insights generated from primary and secondary research, design outcome in form of Low-Fidelity Digital Wire-frame of SikshaMitra.
User Flow:
Low - Fidelity wire-frame in Figma:
Product Feature Prioritization
Product Feature Prioritization
Low - Fidelity Wire-frame User Reaction
Running through the L0w - Fi prototype with users led to discovery of multiple areas of improvement and how users perceived the product features.
Based on the insights , product feature prioritization was categorized on parameters of Value v/s Effort into four categories MoSoCoWo
Affinity Diagram on miro:
Usability Study
Usability Study
Multiple test parameters were action-ed with users to gain insights. The notes from Usability study and Observations :
Incorporating Usability Study Insights
Incorporating Usability Study Insights
Problem Re-framed
Problem Re-framed
Re-framing the problem based on usability study insights
💡Both Tutor and Learner users feel withdrawn as they do not find much Resources and Engagement options on platform
💡For lack of assistance in advertising and complex user flows, Tutors leave platform as they do not find even minimal platform fee charged, justified
💡Tutors need help showcasing their skill sets and digital advertising it, as 30% of target user segment are not tech savvy
Solution Action-ed as below:
Accessibility Considerations
Accessibility Considerations
Product Value Proposition
Product Value Proposition
Aligning Product Design with User needs and Value proposition
Aligning Product Design with User needs and Value proposition
Hi-Fidelity prototype on Figma:
Metrics, Impact and Takeaways
Metrics, Impact and Takeaways
Success Metrics and North Star Metric
Success Metrics and North Star Metric
🎯User Engagement will be tracked through, Active Users on platform from these two focus segments : Tier 2 & 3 cities and Metros. Active user percentage will be tracked using the ratio of, Number of active users (segregated for these above two ) over a 3 week period
🎯Average Revenue generation will be tracked through, (Number of services availed by Users (in form of schedule confirmations, live sessions accessed, pre- recorded courses availed, institutional connects availed) over 2 week period) / (Number of Active Users of the platform)
🎯Bounce Rate of Users, will be tracked through these two measures, which will be indicative of user interest, product outreach & impact, ease of use, ability to retain, engage and provide learner base
Number of Users who left pre-sign up or midway sign-up registration
Number of Users who became dormant post following time break points of, 3 weeks and 6 weeks
✴️ North Star Metrics in form of key value generator for users, would be Number of confirmations that a Tutor signs monthly.
Thank You!
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