Manan WasonPersonalized product templates
Could we earn more from what we know about each customer's industry?
Flip for the result ↻Product Manager · 5+ yearsOpen to PM roles
I turn customer data into products people actually use.
Data-driven PM with an engineering background, working on personalization. I've scaled an enterprise customer data platform, shipped personalization that earns millions, and built 0→1 platforms across NA, EU, ANZ and India.
NowProduct Manager, Indofast Energy
Experience5+ years · 3 as an engineer
StrengthsPersonalization · customer data · 0→1
EducationMBA, SPJIMR · B.Tech CSE
Based inBengaluru, India
Shipped
Homepage action panel
How do we get returning customers back to work faster?
Flip for the result ↻Customer identifier usage reporting
Which customer identifiers actually drive personalization, and where?
Flip for the result ↻Personalization roadmap
How do we put relevant content in front of more customers?
Flip for the result ↻Shop by Use Case · Signage
How do shoppers find the right sign when they think in use cases, not products?
Flip for the result ↻In-house floor-plan platform
Can we stop paying for third-party floor-plan licenses?
Flip for the result ↻Automated asset recovery
How do we recover more assets without manual searching?
Flip for the result ↻Experience
From writing the code to owning the roadmap
Three years building infrastructure software at Verizon, an MBA, then product roles in data, personalization and e-commerce.
Jul 2026 – Present
CurrentProduct Manager
Indofast Energy · Bengaluru
Leading the 0→1 build of an automated asset recovery platform, using predictive clustering and live dashboards, which has lifted asset recovery by 15%.
Jun 2024 – Jun 2026
Associate Product Manager
Vista (Cimpress) · Customer data, personalization, category experience
Scaled Vista's customer data platform across Cimpress brands and owned the personalization roadmap, shipping personalized templates, a homepage action panel and use-case navigation worth $3.6M in gross profit and $1.4M in revenue, with +26% returning-customer conversion and +37% personalized impressions.
Sep 2023 – Oct 2023
Product Manager Intern
Dr. Reddy's Laboratories · Supply assurance
Closed data integration gaps in supply assurance with a supply confirmation indicator that removed 15+ hours a week of manual Excel work.
Jul 2019 – Jul 2022
Intern: Feb – May 2019
Full Stack Developer
Verizon · 5G Ultra Wideband infrastructure
Built and scaled the software behind Verizon's 5G Ultra Wideband rollout across 200+ sites in 50+ cities, including an in-house floor-plan platform that saved $20M and faster workflows for 22K users.
Skills
The toolkit behind the work
Recognition
Podium finishes and peer awards
National product competitions during my MBA, and recognition from colleagues at Verizon. Each links to the certificate or award.
2nd Runner-UpIIMA
PM Live · IIM Ahmedabad
Netflix India growth case: live sports and regional content with watch parties, built on a 45+ user survey and RICE prioritization.
View award ↗National FinalistMMT
MakeMyTrip Young Turks' Business Challenge
NegotiaStay: a bid-and-counter-offer flow to move Tier-2 and Tier-3 hotel bookings online.
View award ↗Verizon peer recognition
Case studies
How I think through product problems
A small library of nine case studies and venture pitches. Each one starts from a measurable problem and ends with the metric I'd use to prove it worked.
Retention · Streaming2nd Runner-Up · IIM-A
N
Netflix: new audiences in India
Growth had stalled despite price cuts. A survey of 45+ users found 60% wanted live sports and many lacked regional content.
- Bet
- FlixTV: live sports and regional shows, with NetFam watch parties
- Metric
- MAU, churn, live viewership, CLV
Full breakdown
Primary research
- 60% interested in sports streaming; 40% in a native watch party
- 62% prefer yearly plans; 71% would take a cheaper plan with ads
RICE prioritization
| Feature | Reach /1000 | I | C | E | Score |
|---|---|---|---|---|---|
| FlixTV | 600 | 3 | 100% | 5 | 36,000 |
| NetFam | 400 | 2 | 80% | 3 | 21,334 |
Pricing and 5-year plan
Keep tiers, add ₹50 add-ons for live and watch party on lower tiers, and start with smaller leagues before bidding for IPL-scale rights. Projected ~80M additional subscribers by 2027.
Team Prod Wizards: Manan Wason, Rohan Garg, Vincle Mable Vas
Offline → online · TravelNational Finalist
MMT
MakeMyTrip: moving hotel bookings online
Online channels account for under 20% of hotel bookings. Tier-2 and Tier-3 travellers distrust online prices and prefer to negotiate.
- Bet
- NegotiaStay: bid a price and let hotels counter-offer
- Metric
- North star: number of hotel bookings
Full breakdown
Persona
Raj, 45, sweet shop owner in Roorkee. Relies on word of mouth, wants low cost and trust.
RICE prioritization
| Feature | R | I | C | E | Score |
|---|---|---|---|---|---|
| NegotiaStay | 9 | 8 | 9 | 9 | 72 |
| SelectStay (pay per amenity) | 8 | 7 | 8 | 7 | 64 |
| SmartStay alerts | 8 | 7 | 7 | 8 | 49 |
Go to market
Pilot in North Indian hill stations like Shimla with many local hotels, then expand based on negotiation success rate and bookings.
Team: Manan Wason, Rohan Garg, Vincle Mable Vas
Engagement · OTTProduct case
AX
Airtel Xstream: Watch Together
Low DAU/MAU: viewers watch alone and leave, and people who live apart can't enjoy a show together the way they would in person.
- Bet
- Watch Together: synced playback in a party room, with invite links and host controls
- Metric
- DAU/MAU, guarded by sync latency and join success rate
Full breakdown
Who it's for
- Long-distance couples, college friends in different cities, families living abroad, parents and children
Pain points
- Playback falls out of sync, no way to interact, chat scattered across other apps, and hosting is hard
MoSCoW prioritization
| Priority | Features |
|---|---|
| Must (MVP) | Create party · invite link · synced playback · host controls |
| Should | In-app chat · emoji reactions |
| Could | Voice chat · audience polls · shared queue |
| Won't (for now) | Mini games · video reactions |
Experiment
A 4-week randomized test, 50% solo vs 50% Watch Together, on users who stream at least twice a week. Hypothesis: synced playback and friend invites lift DAU/MAU by 2–3%, because social viewing reduces churn.
Risks I planned for
- Friends without a subscription: a preview lobby, with entitlement required before playback
- Sync drift: a low-latency sync service with regular state reconciliation
- Spam invite links: links that expire, plus host approval
- People defaulting to Meet or Zoom: ship light chat first and validate demand before building voice
Roadmap
Iteration 2 brings chat and reactions into the app. Iteration 3 adds voice, polls, shared queues and reminders to build a weekly habit.
Prototype
Monetization · AI builderProduct case
E
Emergent: more paid subscriptions
Users couldn't see the value before paying, couldn't try before committing, and couldn't buy credits flexibly.
- Bet
- Pay-per-use credits plus custom credit add-ons on Pro and Team plans
- Metric
- Free-plan activation, then subscription conversion
Full breakdown
Segments
- Small business owners and founders who need to visualize and pitch ideas to investors
- Non-technical users (PMs, consultants, students) who need to prototype without code
Features and experiments
- Customizable credit plan: an "Add more credits" bundle on the plan page. Measured by bundle conversion and add-on revenue.
- Pay-per-use credits: ad hoc purchases to lift activation on free plans, followed by subscription nudges that show the saving.
- Product overview hub: a homepage layout test with USPs, templates and social proof, measured by homepage signup rate.
Prototype
Conversion · FintechProduct case · SPJIMR
P
Paytm: fixing the recharge funnel
Only 35% of users landing on bill pay complete a transaction, and 60% return the next month.
- Bet
- PayExpress: single-tap pay with auto-applied coupons and plan nudges
- Metric
- Transaction completion time and rate
Full breakdown
Pain points from the journey map
- Complex navigation, information overload, limited payment options, a cumbersome checkout
Proposed features
- PayExpress (quick win, high impact): single-tap pay, auto-applied best coupon, recommendation nudges
- Paytm Central (major project): personalized home with priority alerts, consolidated view and voice search
- AutoBot (fill-in): SMS-based data tracking, auto-pay mandates, multi-account management
Risks I planned for
- Auto-applied coupons users dislike, irrelevant recommendations, nudge fatigue, alert overload
Launch
Pilot with users near their recharge date who use Paytm moderately, with test and control groups, then refine from heatmaps and drop-off data.
0→1 · FintechVenture pitch
SS
StockSwipe
80% of surveyed would-be investors felt they didn't know enough about the market, and 91% wanted personalized recommendations.
- Bet
- Swipe through stock picks matched to your goals and risk, linked to your broker
- Model
- ₹999/year subscription plus partner commissions
Full breakdown
Market
- TAM 115M demat accounts, SAM 31M active NSE users, SOM 18M on discount brokers
Product
- Risk and goal questionnaire feeding a matching algorithm with an explained similarity score
- Swipe-to-invest cards, stock profiles, an interest dashboard and price alerts
- Integrations with brokers like Zerodha, Groww, Upstox
Regulation
Designed around SEBI investment-advisory rules: suitability checks, transparent methodology and cost disclosure, data protection and investor education.
0→1 · CommerceVenture pitch · 2023
SoS
ShopOnSpot
Viewers see a product in a video and can't find it online without manual searching.
- Bet
- A browser extension that tags products in a playing video and links to stores
- Model
- $0.50 per sponsored click; organic results free
Full breakdown
Why now
- E-commerce growth, browsers phasing out third-party cookies (favoring contextual ads), and India's ₹12B+ influencer market
Market sizing (YouTube only)
- TAM $76.8B in ad clicks, SAM $7.68B in search marketing, SOM $384M
Positioning
Plotted against Google Lens, Pinterest, Amazon StyleSnap and CamFind on convenience and accuracy; ShopOnSpot wins by working inside the video.
Phygital retail · ARProduct concept
M
Mallorama
Mall footfall is falling: shoppers face long queues, repetitive stores and fitting rooms, while 85% still value touch and feel.
- Bet
- An AR smart mirror for virtual try-on across every store in the mall
- Metric
- Mirror users who go on to purchase, online or in store
Full breakdown
Personas
- Radha, 45: time-poor, can't find stores in a large mall
- Kanav, 30: avoids queues, finds every mall the same
- Shreya, 20: trend-led, budget-limited
Features
- Virtual try-on with complete-the-look recommendations and WhatsApp sharing
- Mall-o-list: a QR-linked wishlist showing store location, offers and nearby shops
Metrics
AARRR: unique mirror visitors, wishlist signups, repeat use, purchases and social sentiment.
Acquisition · TravelProduct case · SPJIMR
TS
TravelSite: group stays and tour guides
Group travellers have few suitable options and a slow booking process. Foreign tourists lack a trusted way to book licensed guides.
- Bet
- TStays: compare hostels and homestays across booking partners
- Metric
- First-booking activation, repeat bookings, NPS
Full breakdown
RICE prioritization
| Feature | R | I | C | E | Score |
|---|---|---|---|---|---|
| TStays | 9 | 8 | 8 | 9 | 64 |
| TS Verified | 9 | 6 | 6 | 6 | 54 |
| TripAlert | 8 | 6 | 6 | 6 | 48 |
New revenue line
A marketplace for India's 3,500+ licensed regional guides, with license verification, multilingual search, scheduling and SOS help, monetized by commission.
Guardrail metrics
Guide earnings per day, retention of newer guides, guide diversity and review sentiment, so commission doesn't erode tour quality.
Education
Engineering first, then business
SP Jain Institute of Management and Research
MBA, Information Management & Finance · 2022 – 2024
SRM Institute of Science & Technology
B.Tech, Computer Science and Engineering · 2015 – 2019
Contact
Building something with data at its core? Let's talk.
I'm open to product roles in personalization, data platforms, growth and 0→1 products.