Where UX meets growth. I design the experience and then get people to show up for it.

The problem

Moving cities usually means losing your sports circle. Existing apps log activity or book venues, but none help you find the right people to play with.

The centrepiece

What I did

1. Interviewed 30+ athletes and coaches in Delhi and Mumbai.
2. Dropped activity logging and the social feed to focus on one job: finding people to play with.
3. Designed the Player Card as profile, discovery card and shareable collectible.
4. Mapped 12+ UX flows across 3 design sprints, from onboarding to Team Up requests.
5. Built the brand, prototype and waitlist site at squadhq.in.

By the numbers

Context from my research

The problem

AI nutrition apps lose people because they feel foreign: Western meal models, no explanation, and no human behind the advice. In India, food is cultural, emotional and personal.

What I did

1. Literature review: Mayer's trust model, TAM, explainable AI and human-in-the-loop.
2. Qualitative interviews turned into 2 personas.
3. Survey with 150 responses on what builds or breaks trust.
4. Designed 5 core screens straight from the findings.

What the data said

Recommendations

1. Explain the AI's logic in simple, visual ways.
2. Localise food and language. A dosa is not a salad.
3. Expert validation from nutritionists and doctors.
4. Real user stories and regional food influencers.

The finding

Over 4 minutes hovering over “+ Add Path” without ever clicking.

How I investigated

1. Wrote a hypothesis in Autoplay's search and filtered sessions.
2. Used knowledge level and hesitation as the variables to compare.
3. Read the insights and related sessions, then chatted with the AI in real time.
4. Grouped two matching sessions into a collection.
5. Rebuilt the golden path by hand, from login to creation.

The screens

Friction → fix

What I shipped

1. A long-form blog for PMs on the real cost of a missing “why”: wasted sprints, cluttered backlogs, lost revenue.
2. 3 LinkedIn and 3 X posts: one educational, one feature use case, one humour.
3. A 7-section SEO audit, including dedicated landing pages for Golden Path Analysis and an “AI Session Replays vs traditional tools” page.
4. A 3-email creator outreach sequence: cold intro, day-3 follow-up, day-5 close.

One of the posts

LinkedInThe hardest part of product growth? Not tracking clicks. Not funnels. It's understanding why users drop off. Numbers tell you the what. Intent analysis tells you the why.

The problem

The growth team spent hours prospecting by hand, with targeting, outreach and CRM living in separate tools.

The pipeline

What I did

1. Wrote the PRD and user stories from the team's pain points.
2. Specced contact scoring, sequence automation and CRM sync.
3. Ran 2-week sprints with engineering through to deployment.
4. Launched campaigns across Singapore and the US with Apollo and WebEngage.

Outcome

The problem

Parents lack trustworthy, age-specific nutrition advice. Most apps stop at age 5, while the parenting and nutrition tech market grows 25% a year.

How it stands apart

The stage-gate plan

1. Idea: market research and interviews with young mothers, validated by pediatricians.
2. Concept: AI meal plans, expert advice, community and learning content.
3. Strategy: PRD, persona and positioning.
4. Validation: beta with 150 users across three age groups (2-5, 6-12, 13-18).

The problem

Manual data entry, physical counts and human error: the brand was losing time and accuracy on every item in stock.

What I did

1. Research, competitor analysis and SWOT.
2. Mapped user flows for admins and shoppers.
3. Wireframed product pages, checkout and the admin panel.
4. Built the admin flows: products, tags, SKUs, pricing and stock.
5. Storefront checkout and sales analytics.

The screens