A comprehensive case study covering 0-to-1 product design, CMS architecture, growth strategy, traction, and an honest postmortem of what went wrong. Built 2016–2018.
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The Short Version
I solved the "what should I watch tonight" problem for 50,000 people — built an entire product, a CMS, and a content operation from scratch — secured $40K from Facebook, achieved 2.5-minute average sessions in an industry where 30 seconds is standard. Then we shut it down. Here's what really happened.
| Metric | Result |
|---|---|
| 📲 App Downloads | 50,000+ |
| 💸 Paid Marketing | ₹80-100K |
| ⏱️ Avg Session Time | 2.5 min (10× industry avg) |
| 🚀 Funding | $40K — Facebook Accelerator 2016 |
| 📸 Instagram Community | 8,000+ engaged followers |
| 🗓️ Timeline | Mar 2016 – Aug 2018 |
| 👤 Role | Founder & Chief Product Designer |
The honest headline: We were ahead of our time, underfunded, and we made the classic founder mistake — we fell in love with the product before we fell in love with the business.
01 — Origin Story
All good startups begin the same way: a conversation that won't leave you alone.
It was 2015. India's startup ecosystem was buzzing. OTT platforms were multiplying. A friend — who would become my co-founder — and I were doing what we always did: debating what to watch.
The conversation was unremarkable on its surface. "What are you watching these days?" But as we mapped it out, we realized the question was harder than it should be. We had Netflix. Hotstar. YouTube. Star World. BookMyShow. A dozen fragmented sources, each with its own app, its own login, its own recommendation logic — and none of them talking to each other.
We started asking friends. Then friends of friends. The pattern was consistent: people spent 20–25 minutes deciding what to watch — longer, in many cases, than the content itself. Decision fatigue wasn't a theory. It was the lived reality of entertainment in India in 2015.
That conversation became a hypothesis. The hypothesis became a startup. The startup became two and a half years of the most educating, humbling, exhilarating, and ultimately painful work of my design career.
02 — The Problem Space
By 2015, India was at a content inflection point:
The result: a paradox of choice. More content than ever. Less clarity about what to watch. The streaming industry was focused entirely on content acquisition — not content discovery. That gap was the opportunity.
Viewers in metro and Tier 1 cities were inundated with content across 5+ platforms, with no unified way to discover, save, or decide what to watch — leading to decision fatigue, platform-hopping, and wasted evenings.
Primary audience: Tech-savvy smartphone users, 16–28, in metro and Tier 1/2 cities.
03 — Research & Hypotheses
We were bootstrapped with no budget for formal research. What we had was hustle and a network.
Every existing solution was platform-specific or genre-specific. IMDb rated movies. JustWatch tracked streaming availability. Nothing aggregated OTT + TV + live venues into a single, opinionated, personalized feed.
More importantly: users didn't want a list. They wanted a recommendation — something that felt like a smart friend saying "you'll love this, and it's on Hotstar right now."
We understood the incoming OTT wave clearly. We knew Netflix, Amazon, and Hotstar were going to flood India with content. We bet — correctly — that this would increase the discovery problem, not solve it. The paradox of choice would only get worse as more platforms launched.
We were right about the problem. We were wrong about our timing and our ability to survive long enough to be proven right.
"We believe that if entertainment seekers aged 16–28 in Indian metros could see personalized recommendations across OTT, TV, and live venues in a single swipeable interface, they would spend less time deciding and more time enjoying — making entertainment discovery a daily habit, not a chore."
04 — The Solution: Consumer App
We weren't building a search engine. We were building a recommendation companion — opinionated, personalized, and contextual. The design had to feel like a smart friend, not a database.
Core Feature Set
1. Personalized Recommendation Feed
A swipeable card interface — the binary decisiveness of Tinder, applied to content. Swipe right to save, left to dismiss. Each interaction trained the algorithm. Low-commitment inputs generate high-quality behavioral data faster than any survey.
2. Cross-Platform Content Aggregation
Movies, TV shows, OTT content, local events, theater releases — unified in one feed. The algorithm factored in time of day, location, viewing history, and social graph trends.
3. The Watchlist
Save anything. Access it across sessions. Share it. The watchlist was the product's memory — what differentiated us from a one-time recommendation engine.
4. Contextual Push Notifications — Our Retention Engine
Users received alerts like: "Breaking Bad is now available on Netflix India" or "The Dark Knight is airing on Star Movies tonight at 9pm." Each notification had a distinctive, recognizable sound — users knew immediately it was Watchlyst. It created a signal-based return mechanism rather than hoping for habitual opens.
5. Event Discovery — The Differentiator
The feature no competitor had. Live events, comedy shows, exhibitions, theater — discoverable alongside your Netflix queue. Hyper-local, location-aware, time-sensitive. Nothing else in the market combined digital content with live experiences.
6. Social Layer
Share what you're watching. See what friends saved. Spark conversations. Our organic growth engine before we had budget for paid acquisition.
| Decision | Rationale | Alternative Rejected |
|---|---|---|
| Swipe-card UI | Binary inputs reduce cognitive load and train the algorithm faster | List/grid browse |
| Contextual notifications with branded sound | Habit-formation requires recognizable, meaningful triggers | Generic push alerts |
| Events + OTT + TV in one taxonomy | Differentiation — no competitor had this scope | Separate sections per content type |
| Preference quiz onboarding | Cold-start fix — needed behavioral signals before first recommendation | Show generic trending content |
Card Design Evolution
V1 — Initial card explorations
Notification card — our retention engine
App in Motion — Interaction Prototypes
Search card expand animation — the key micro-interaction
Initial Versions and Testing
Future Versions and Plans
Watchlyst search card expansion micro-interaction
▶ In Cinema — content card animation
▶ On TV — broadcast schedule card
🎨 V2 Minimalist Card Design — Figma
05 — The Solution: Admin CMS
Surfacing personalized entertainment recommendations at scale required hundreds of API calls per minute, web crawlers refreshing content data continuously, and human editorial judgment layered on top of algorithmic curation.
The CMS was, in many ways, harder to design than the consumer app — and more strategically critical. If the content pipeline broke, the app went empty. If the editorial experience was bad, our writers quit.
Our content contributors were college students without regular laptop access. Standard admin interfaces — designed for desktop power users — were completely wrong for our context. We designed a mobile-first CMS from scratch. That was a non-obvious problem most startups never face.
Three distinct roles, each with a purpose-fit interface:
Writer — Content creation, tagging, first draft submission. Fully mobile-optimized. Minimum fields, maximum speed.
Editor — Review, fact-checking, SEO tagging, linking related content. Could reject or request revisions. Operated as the quality gate.
Publisher — Final approval, scheduling, push notification triggers. Had visibility into content performance and distribution analytics.
This pipeline ensured content quality without bottlenecks. Writers kept producing while editors reviewed in parallel and publishers controlled the schedule.
Building the CMS taught me something that shaped every subsequent role: the user experience of internal tools directly determines the quality of what users see. Bad internal UX → bad content → user churn. Investing in operational tooling wasn't overhead — it was product strategy.
06 — Growth & Community Strategy
With zero paid marketing, our growth relied entirely on organic community-building. The Instagram account became our primary distribution channel — and an unexpected product feedback loop.
The unexpected insight: Our Instagram community wasn't just marketing — it was a live research panel. Comments and DMs told us more about user intent than any formal survey. We knew what users wanted to watch before we had enough in-app data to see the pattern.
The 8K community and engagement rates are the story here. Browse the full social archive and pixel art project below.
07 — Traction & What the Numbers Said
50,000 downloads. Zero paid marketing. $40K raised. 2.5-minute average sessions — 10× the industry benchmark.
These numbers validated the core hypothesis: users genuinely wanted unified entertainment discovery. The session time was the most meaningful signal — people weren't bouncing. They were actively discovering, saving, and engaging.
The notification system was our strongest retention mechanic. Users came back specifically because of contextual alerts — knowing their favourite movie had just landed on OTT felt like a service, not spam. That's difficult to build and we executed it well.
Being selected for the Facebook Accelerator 2016 cohort was a milestone beyond metrics. It meant our product vision was credible enough for external evaluation. The $40K was operational fuel. Access to Facebook's product and growth teams was the real value — frameworks for thinking about scale that we hadn't had before.
We saw these signals. We chose to focus on acquisition over fixing retention. That was the wrong call — and the next section accounts for it honestly.
08 — The Failure Autopsy
This is the section that separates a project page from a case study. Anyone can document what they built. The harder, more valuable thing is to document why it didn't work — and mean it.
We were years ahead of the problem we were solving.
In 2016, India's OTT influx was still relatively low. The paradox of choice — our core insight — wasn't acute enough yet for mainstream users to seek a dedicated solution. Jio hadn't launched yet. Netflix had just entered India. The content explosion we'd anticipated was still 12–18 months from becoming a genuine mass pain point. We were building infrastructure for a problem that hadn't fully arrived.
We couldn't close angel investment and ran out of runway.
Despite cracking the Facebook Accelerator, we couldn't close angel funding. India's angel ecosystem in 2015–16 was active but risk-averse on consumer apps without clear monetisation. We couldn't tell a compelling enough revenue story. Funds ran out. The team dispersed.
We had a monetisation strategy — we just never executed it.
The model was clear. We'd studied InShorts and others. Multiple revenue streams were designed:
The model was viable. We never pressure-tested it with actual partners. We told ourselves: first get users, then get revenue conversations. That sequencing cost us everything.
We spent too much time perfecting the app and not enough time on the business.
This is the most honest thing I can say. We were designers and builders at heart. The product got enormous care and attention. The business did not. We believed good enough product would pull everything else forward. It doesn't work that way.
We solved discovery but not daily habit-formation.
The notification system brought users back on signal — a specific trigger, a relevant moment. But we never built a strong enough reason to open the app unprompted, as a daily ritual. Discovery is episodic. Habit requires a consistent daily hook. We never closed that gap.
We chased an unproductive tangent too early.
At one point, we started exploring IoT devices — hardware that could change TV channels directly from the Watchlyst app. It was exciting. It was also completely wrong for a bootstrapped team with limited engineering resources. We spent months on a hardware exploration that should have gone into retention strategy or monetisation conversations.
The founding team fell apart in sequence.
We started with shared conviction and good energy. But as complexity scaled, alignment drifted. My co-founder's responsibility was monetisation strategy and business development — the path forward we couldn't find together. Our founding developer left in a dispute. Our founding sales and marketing person followed.
I was left managing product, design, content, community, and operations simultaneously. We ran the show for 8–9 months after the team fell apart. You can sustain a lot on stubbornness. You can't build a business on it.
The right co-founder changes everything. The wrong dynamic costs everything.
We had shared excitement about the problem. What we didn't have was complementary strengths and shared accountability for the parts that were hardest. That difference matters more than any product decision.
09 — What I Would Do Differently
Not platitudes. Specific decisions, specific reasoning.
1. Find the right co-founder before writing a line of code.
Not someone who shares your excitement about the problem. Someone who is genuinely strong where you are weak, and who takes ownership of the hard, unglamorous work — investor relationships, revenue conversations, business development. My strength was product and design. I needed a co-founder obsessed with the business, not just the product.
2. Build monetisation strategy in parallel, not after.
We told ourselves: first get users, then figure out money. Understandable for first-time founders. Still wrong. We should have been in monetisation conversations with platforms, brands, and event companies from month three. The product gives you credibility. Revenue conversations give you runway.
3. Treat investor outreach as a design sprint, not an afterthought.
We weren't meeting enough investors consistently. Fundraising is a design problem — you're designing a narrative for a specific audience with specific decision criteria. We didn't put the same craft into our investor pitch that we put into our product. That mismatch showed.
4. Kill the IoT detour immediately.
When you're small, bootstrapped, and have a working consumer product, the answer is never to start building hardware. Constraints are productive. Stay ruthlessly focused on the core.
5. Solve retention before scaling acquisition.
Find the users who love the product most. Understand why. Fix what stops others from having that same experience. Then grow. We had the retention signals. We chose to look away.
10 — What This Failure Unlocked
Running Watchlyst stripped me of design ego in the best possible way.
Before Watchlyst, I was a designer. After Watchlyst, I was a product person who happened to be a great designer — and that distinction matters more than most people realize.
When I returned to Avizva after shutting down operations, I brought something with me that no client brief or design role had given me: the visceral experience of building a product, taking it to market, watching users engage with it, watching the business fail to support it, and walking away having learned more from the failure than from any success.
I lost the fake creative pride that designers often carry.
There's an intellectual vanity that designers develop — a belief that good craft is sufficient, that the work speaks for itself. Running a startup destroyed that belief in me. Good design is necessary but not sufficient. It has to sit inside a working business. I stopped being precious about design and started being practical about outcomes.
I learned that every person plays a critical, irreplaceable role.
As a founder wearing five hats simultaneously, you feel the absence of every missing function acutely. There's no "that's not my job" when you're it. I came out of Watchlyst with deep respect for what sales people, developers, operations people, and marketers actually do — and a far healthier ability to collaborate with them as a peer, not just as the designer who hands things off.
I started designing with GTM thinking baked in.
At Airtel, at Microsoft — in every role since — I've never treated launch strategy or monetisation as someone else's problem. I bring that lens into product conversations from the start. What does this feature unlock for the business? Who does it reach? How does it grow? These became design questions, not business questions.
I understood what design thinking actually means — applied outside design.
Watchlyst made design thinking operational for me, not theoretical. I applied user research to content strategy. I applied prototyping thinking to the CMS. I applied systems thinking to the editorial pipeline. Design thinking isn't a methodology for designers — it's a cognitive approach that works on any problem. That realization shaped every leadership role I've held since.
11 — Conclusion
Watchlyst failed as a business. It succeeded as an education.
We were early. Under-resourced. In a market being redefined by entities with orders of magnitude more capital. Netflix, Hotstar, and Amazon were all investing in recommendation engines as core product infrastructure. We were a three-person team trying to stay relevant in a space that would soon be dominated by billion-dollar content budgets.
But in that 2.5-year sprint, I built things I'd never built before: a recommendation algorithm, a mobile-first content management system, a content operation, a social community of 8,000 engaged people, a pitch that convinced Facebook to invest — and a product that 50,000 people downloaded without us spending a single rupee on marketing.
I made every mistake a first-time founder makes. And I understood, in visceral detail, why they are mistakes.
Every product decision I've made since — launching Airtel Thanks 2.0 to 100M+ users, shipping AI features used by millions in Excel, building design systems across five product teams — has been shaped by what I learned building and watching Watchlyst fail.
That's not a consolation prize. That's the actual value.
The best design education isn't a course, a certificate, or a bootcamp. Sometimes it's a startup that doesn't make it — if you're honest enough with yourself to learn from it.
| Archive | Link |
|---|---|
| All Dropbox assets | Parent folder |
| Presentations & docs | Google Drive |
| Original Notion draft | Watchlyst App: Idea, Product & Strategy |
Abhishek Saxena is a senior product designer with 12+ years of experience building products at Microsoft, Airtel, Samsung, and two startups. Based in India, open to global design leadership opportunities.
