Examify

Examify is an application that helps students study smarter. It uses algorithms to tell the student what to study and when, so that he/she can optimize their study time and remember concepts better.

On launching, we got to 100,000 users in 10 weeks with $0 marketing spend.

Role: Co-founder, COO

Skills: Leadership, Team-building, Operations, Process design, Interaction design

The Problem

Students in India face a lot of pressure to perform well in a couple of exams which their parents believe decide their entire future. Their lives are completely filled with school, tuition classes and test series, leaving them no time for anything else.

These years are the most harrowing years of any Indian student’s life because of the sheer number of text-books, exercise problem sets, past years’ question papers, model question papers, etc. that they have to make their way through.

The Product Vision

We envisioned a product which would take the load of managing the students’ study schedule (what to study, when to study, how often to study which topic, etc.) off the students’ shoulders.

Our product would empower the students to leave the administrative work of managing their studies to us, and thus allowing them to focus only on the learning and to maximize the ROI on the time spent studying.

What We Did

We built a platform for students to easily find the most important questions that they should be studying.

To do this, we sourced and digitized tens of thousands of question papers from all over India. We tried multiple vendors to handle the digitization, but finally had to create our own process to deal with the added complexities of digitizing question papers. We had to build many parts of the workflow for this huge effort ourselves.

Then we added signals such as frequencies and user feedback to determine the ranking of questions.

We reached 100,000 users within 10 weeks of launching, without spending any money on marketing. This growth was mainly due to our PR push, which saw us being featured on the front page of Hindustan Times, the 3rd largest English newspaper in India.

However, getting the product in front of a lot of users only served to solve for a part of the Acquisition, Activation, Retention, Revenue, Referral (AARRR) funnel. We quickly realized that we were not able to retain our users as much as we would like them to.

We went through multiple iterations of the product, starting with a Pinterest-style trending questions list, to a Q&A based product, to a feed of most important questions, to an analytics dashboard that showed the students their progress. With every major iteration, we solved the next major problem as we moved down the AARRR funnel.

What I Would Do Differently Today

With the benefit of hindsight, I realize that we relied too much on Quantitative data, and did not do enough qualitative research into our users.

  • We got our personas wrong at the very outset. We also did not make them concrete, so many of the product decisions went through because we did not have any persona to evaluate them against. Today, I would make a concerted effort to create detailed, specific and relatable personas. That would have helped us avoid many costly mistakes.
  • We stumbled around different products because the quantitative data would only give us the symptoms. We did not have insights into why certain aspects of our product were not working, or working. Today, I would pay much more attention to getting at the root of the user’s behavior by conducting contextual inquiries, interviews and other methods.
  • We also focused too much on solving one part of the funnel, rather than look at optimizing the larger picture. Because of this, we lost out on thousands of customers who tried us for a couple of times, but then gave up on us.
  • We did not set up the right communication channels and values within our own team.
  • We did not iterate quickly enough. In this, we were hampered by both using legacy technologies as well as not being “minimum” enough in our “minimum viable products”. We should have adopted design thinking much more deeply and worked with lo-fi prototypes and conducted usability studies before moving into development.

 

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