BILAL

PRODUCT DESIGNER
May 2017 - Mar 2021

Amazon Academy

Bringing world-class test prep experience to every corner of India, at 0.024% of the cost.

0→1
a kindle initiative
desktop, android app
single-person ux team
full-stack ux deliverables

Case study

~18 minutes

  • My impact

    in a nutshell

    End-to-end interaction and visual design for the desktop and Android app.
    Led the development of a design system optimized for learning

    Consulted with Kindle Research to conduct user interviews & usability studies.
    Recruited and facilitated design swarms for problem identification
    Worked with principal engineers leads to fine-tune personalization algorithm for AdaptivePractice™.

    Elevated the UX over the course of 11 internal betas, 4 school betas, 2 private betas before the public launch
    Grew from a single member team (L5) to a design lead (L6) of the UX team

    Ownership

    Design Craft

    Collaboration

    Drive Results

    Continuous growth

    1.2M

    40+

    Registered Users

    Net Promoter Score

    Launched on:

    Android, Desktop

  • My impact

    Sr. UX Designer

    2017-2021

    Manager(s)

    🌱
    I led the design charter for this product that went from concept in May 2017 to launch in Jan 2021, amassing over 1.2 million registered users and a NPS of 40+.

    🤝
    In constructing the adaptive practice flow, I co-proposed to the Kindle engineering leadership the use of behavior models such as Flow and Bloom’s taxonomy

    📚
    Conducted research with educators to adapt traditional teaching methods in the digital context.

  • My impact

    Sr. UX Designer

    2017-2021

    🖍️
    I created Guru UI, a design system that is optimized for learning. It ensures the UX doesn't break on low-end devices, unreliable network and renders math & science characters accurately.

    📈
    To curb the team's first-conclusion-bias, I developed a shared moodboard with 50+ team members that grew to include 400+ ideas from various learning apps.

    🧪
    Each quarter, I led usability studies with students from our partner schools to beta test certain UX decisions.

    As Charlie Munger famously said, the mind works like a sperm and egg: the first idea gets in and then the mind shuts. This is our energy-saving device. Our tendency to settle on first conclusions leads us to accept many erroneous results and cease asking questions.

    Manager(s)

  • An avg undergrad student in India spends more than ₹150,000; commutes long hours to get trained for JEE and yet receives a one-size fits all coaching without any clarity on weak areas.

    Customer pain-points 🤕

    Avg. household income in India is ₹24,000

    JEE: An entrance test conducted for admission to Top-20 engineering colleges in India.

  • 🇮🇳
    With a population of 1.33 Bn, the Pupil-Teacher ratio (PTR) in India is 47:1 (global avg. 21:1)

    ✍️
    Each year, over 10 million students take the Joint Entrance Examination (JEE) in India, compared to 2.2 million students taking the SAT in the United States.

    💸
    India has the highest percentage of household income spent on undergrad test-prep tuition, at 72%, compared to the global average of 24%

    One-size-fits-all

    Stressful

    Expensive

    Customer pain-points 🤕

  • I facilitated 1-on-1 interviews and group discussions with students from our partner schools

    "…all the students in my class are asked to practice the same set of 80 practice questions each day, regardless of my proficiency in the topic"

    "there are so many unknowns throughout this journey that it gets overwhelming"

    "…I wish I could learn about my weak areas at a sub-topic level"

  • To form

    a hypothesis

    design swarms

    "Insight Jam"

    w/ educators

    "Your assumptions are just expensive guesses. Hypothesis-driven thinking turns those guesses into testable bets."

    "you're not building,

    you're experimenting"

    "you're not building,

    you're experimenting"

    — somebody's tshirt

    — our program director

  • Approach

    i.e UX big bets

    1. Adaptive Practice

    2. Bite-sized Learning

    3. Deep Analytics

    4. Affordable

  • Approach

    i.e UX big bets

    1. Adaptive Practice

    2. Bite-sized Learning

    3. Deep Analytics

    4. Affordable

    very

    >

    Empower every student in every corner of India to dream big

  • Metrics 🧪

    Acquisition

    Engagement

    Conversion

    Retention

    App downloads

    Cost per install (CPI)

    Daily active users (DAU)

    Monthly active users (MAU)

    Goal completion rate

    Churn rate

    Retention rate

    Measuring success

  • Metrics 🧪

    🧗‍♀️ Time to Level Up (T.L.U)

    As practice questions for any given topic are divided into various difficulty and cognition levels, it is helpful to gauge at what rate the student moved on the proficiency scale.

    From internal betas to public launch, T.L.U improved by 37% i,e from 19 questions to 12 questions

    📝 Pressure Index (P.I)

    To assess whether a student can recall concepts during a test and not succumb to performance anxiety, even if they can answer practice questions correctly.

    From internal betas to public launch, P.I improved by 125 basis points

    ⏰ Time to Correct Answer (T.C.A)

    In the context of time-crunched competitive exams, it is not enough to just get the questions right. It is also important to maintain your pace and avoid the risk of not attempting all of the questions.

    Measuring success

    • To personalize the practice experience, let us understand the student motivations.

    • Adaptive Practice

      Signals needed to create a personalized plan

    • Adaptive Practice

      Learn where they get stuck with interactive hints and step-wise solution reveal

    • Adaptive Practice

      Learners don’t feel comfortable taking decisions on their own for the fear of being under-informed.

      When possible, eliminate decision-making completely and when not possible, provide good defaults. Keep their end of commitment as simple as “just showing up.”

    • Adaptive Practice

      Look for signs that the student is ready to proceed to the next topic

    • Adaptive Practice

    • Adaptive Practice

    Adaptive Practice

  • Bite-sized Learning

    2.

  • Bite-sized Learning

    You can sift through just the formulae during your revisions.

  • Bite-sized Learning

    Long videos are broken down into short, topic-level coverages.

  • Deep Analytics

    3.

    Figma

  • Deep Analytics

    It is more than just a mirror.

    How might we not just show the current reality but future potential?

    Performance diagnostics as a compass, not as a report card.

    Design Swarm

    Study

    Internal Beta

    Reward effort and not outcome.

    Collaboration Story

  • Deep Analytics

    “…currently, we only receive the overall score and time taken per question. I’d love to be able compare my stats with the rest of the class”

    Social cohorts are a powerful motivator for behavior change. Learners can see how their peers are progressing and be inspired to do the same. Make sure that peer performance is visible and that learners have access to tools that can help them track their own progress.

  • Deep Analytics

  • Reading vs. Learning

    Pushed-back against inheriting Kindle's Page UI which was built for reading

    Operant conditioning: components grow in tiers as users are rewarded for their progress.

    Additional components for a guided UX


    To make students feel comfortable using the app right away, we designed font treatments including math and science symbols that resembled those used in several well-known digitized textbooks.

    Pictographs that are somehow familar to their textbook covers

    The average internet speed in India is 1.5Mbps and the average smartphone has 8GB of storage. We reduced the file sizes by more than 80% by converting images of equations into LaTeX code and this allowed us to render the equations as fonts.

    Simulate the Physical

    Low-end Devices & Unreliable Network

    “Design systems hash out the easy problems,
    so products can focus on the hard ones”

    Design System 📐

  • Little Big Details ✨

  • What this project taught me

    How not to facilitate product-design brainstorming sessions

    Be clear about who needs to be consulted and who is okay with just being kept informed.

    Smaller groups seek the truth.

    Larger groups seek consensus

    How not to define the minimum-lovable

    We kept asking ourselves what the problem was, so much so that we didn't realize we even had started solving for what the problem wasn't.

    Always outline what we shouldn't solve for before most product meetings.

    If the work doesn’t require creativity, delegate it, automate it, or deprioritize it.

    Impatience with actions,

    patience with results.

    Distilling something down to it's essence is a muscle you need to build.

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