Goal:

To develop a scalable growth and operations strategy for Optima Learning by expanding its mentor network, introducing a seasonal GDPI revenue stream, and reducing onboarding drop-offs to help users reach the product’s “Aha” moment faster.

Tools & Technologies Used: Airtable, Zapier, Campus Nodes, LinkedIn, Product onboarding and user journey analysis, Mentor supply and capacity analysis

What I Did:

Analyzed the capacity constraints of the premium 1:1 mentoring model and identified that a working professional/MBA student can realistically mentor only 3–5 students per week.

Identified that with 40+ mentors, the premium tier would physically cap at approximately 150–200 students before compromising the 1:1 mentoring promise.

Proposed scaling the mentor network from 40 to 400 mentors while maintaining operational efficiency and protecting the quality of the 1:1 experience.

Recommended building an automated internal operations layer using Airtable and Zapier to handle recurring operational processes, allowing the team to focus more on strategy as the mentor network scales.

Proposed sourcing additional mentor supply through Campus Nodes by onboarding freshly joined MBA students at an average cost of ₹1,000 per student per month, along with LinkedIn as an additional sourcing channel.

Proposed introducing a standalone GDPI preparation pack immediately after CAT results to capture seasonal demand and act as a revenue booster during the post-CAT period.

Analyzed the existing 13-screen onboarding process and identified it as a major potential source of user drop-off before users experience the product’s “Aha” moment.

Recommended condensing the onboarding journey into a 3-step Smart Default flow or using progressive profiling to reduce friction and pre-fill common persona inputs.

Proposed using the simplified onboarding experience to immediately deliver a personalized AI study plan and then prompt users to schedule their 1:1 mentor call.

Challenges and Learning:

Challenge: Balancing rapid mentor-network expansion with the physical capacity limitations of 1:1 mentoring, while simultaneously reducing onboarding friction and capturing seasonal CAT/GDPI demand.

Learning: Developed a deeper understanding of marketplace supply constraints, mentor capacity planning, operational automation, seasonal product strategy, user onboarding optimization, and progressive profiling.

Result:

Created a scalable framework to expand the mentor network from 40 to 400 mentors while using Airtable and Zapier to automate internal operations and reduce the operational burden on the team.

Established Campus Nodes and LinkedIn as potential channels for building a larger mentor supply base, with freshly joined MBA students targeted at an average cost of ₹1,000 per student per month.

Identified a standalone GDPI pack as a seasonal revenue opportunity following CAT results.

Developed a simplified onboarding approach designed to reduce drop-offs by moving users from a lengthy 13-screen process to a 3-step Smart Default or progressive profiling experience.

Designed the onboarding flow to deliver the AI study plan earlier and connect users to the 1:1 mentor experience faster, helping them reach the product’s core value proposition sooner.

Website: optimalearn (dot) com