vertical industry cases
Every vertical has a gatekeeper who is not your user. In healthcare it is the regulator. In fintech it is the central bank. In edtech it is the parent. In logistics it is physics. Your product roadmap bends around them whether you like it or not.
Generic PM frameworks pretend that building a product for hospitals is the same as building one for banks. That the skills transfer cleanly. That user research is user research, a sprint is a sprint, and a roadmap is a roadmap.
They are wrong.
Every vertical has its own physics. Compliance regimes that dictate what you can ship and when. Domain experts who will dismiss you if you cannot speak their language. Users whose definition of “good enough” is shaped by decades of non-digital workflows. And in India, each vertical carries additional weight — regulatory bodies that move at their own pace, infrastructure gaps that make Western playbooks irrelevant, and price points that force product creativity you will not find in a Silicon Valley case study.
After reviewing thousands of case study answers across eight years of cohorts, the pattern is clear. The PMs who struggle most are not the ones lacking frameworks — they are the ones who apply horizontal frameworks to vertical problems without understanding the domain. This page gives you four verticals, each with the context that matters.
Healthcare: where the user is not the buyer
Healthcare product management in India operates under a constraint that breaks most consumer PM instincts: the person using your product is rarely the person paying for it, and neither of them made the decision to adopt it.
A doctor uses your EMR system. The hospital CIO bought it. The government regulator approved it. The patient whose data flows through it has no say. Four stakeholders, four sets of incentives, one product.
The Ayushman Bharat Digital Mission (ABDM) changed the market in 2022. It introduced a unique health ID for every citizen and a framework for health data exchange — the equivalent of UPI for medical records. But unlike UPI, adoption has been painfully slow. Hospitals resist because digitizing records means accountability. Doctors resist because structured data entry slows them down. Patients do not know it exists.
| Healthcare PM reality | What it means for your product |
|---|---|
| ABDM compliance is mandatory for government hospital partnerships | Your architecture must support health ID linking from day one — retrofitting is expensive |
| Doctors have 3-5 minutes per patient in OPD | Any UI that adds even 30 seconds to a consultation will be abandoned |
| Data privacy under DPDPA 2023 requires explicit consent | Every data flow needs a consent layer — not a checkbox, a genuine consent UX |
| Tier-2/3 hospitals run on paper and WhatsApp | Your “minimum viable” is not a web app — it is a WhatsApp integration |
| Procurement cycles are 6-18 months | Your sales cycle is longer than your dev cycle — plan accordingly |
Product review at a healthtech startup building an EMR for multi-specialty hospitals. Three months post-launch, adoption is flat.
PM: “We have 14 hospitals signed. Only 3 are actively using the system. The other 11 completed onboarding but reverted to paper within two weeks.”
CTO: “Is it a training issue? Should we send more support staff?”
PM: “I spent a week in Jaipur sitting next to doctors in OPD. The problem is not training. A doctor sees 60 patients in a 4-hour OPD shift. That is 4 minutes per patient. Our system requires 2 minutes of data entry per consultation. We just ate half their patient time.”
CEO: “Can we simplify the forms?”
PM: “We need to eliminate the forms. The doctor should speak, and the system should structure. Voice-to-SOAP note. If we cannot get data entry under 20 seconds, this product is dead in OPD.”
The team pivoted to voice-first input. OPD adoption went from 3 hospitals to 9 within six weeks. The insight was not 'make it simpler' — it was 'match the doctor's existing workflow speed.'
Healthcare product adoption is not about features. It is about fitting into workflows where every second is already allocated.
The PM lesson: In healthcare, your competition is not another software product. It is paper. Paper has zero learning curve, zero downtime, zero compliance overhead, and infinite flexibility. Your digital product must be faster than paper for the clinician’s specific workflow — or it will lose. Every time.
India-specific context: Eka.Care, Practo, and MFine each learned this differently. Practo succeeded in patient-facing booking because patients have time to browse. MFine struggled with doctor-facing teleconsultation because the doctor’s time is the constraint. The ABDM framework means every healthtech PM must now understand consent flows, health ID linking, and data portability — skills that did not exist in this job description three years ago.
Fintech: where the regulator ships before you do
Indian fintech is the most regulated consumer product vertical in the country. The RBI does not just regulate — it actively shapes what products can exist.
Paytm Payments Bank learned this violently. In early 2024, the RBI barred Paytm Payments Bank from accepting new deposits or onboarding new customers — citing KYC non-compliance, cybersecurity gaps, and unauthorized account creation. A product that served 300 million users was effectively frozen by a single regulatory action. Paytm’s stock lost 40% of its value in days.
This is not an edge case. This is the operating environment.
The Paytm case is a masterclass in what happens when product velocity outruns compliance discipline. The company created accounts without proper KYC. They prioritized user growth metrics over regulatory requirements. The RBI did not care about DAU or transaction volume — they cared about whether every account was tied to a verified identity.
What Indian fintech PMs must internalize:
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The RBI is a stakeholder, not a constraint. You do not “handle” compliance. You design for it. The best fintech PMs in India read RBI circulars the day they drop — not because legal asked them to, but because every circular is a product requirement.
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UPI is free infrastructure, not free money. Zero MDR means your payment product generates zero direct revenue. PhonePe, Google Pay, and Paytm all lose money on every UPI transaction. The product challenge is converting payment frequency into financial services revenue — insurance, lending, investments.
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Lending is where the money is, and where the risk is. Buy-now-pay-later products like Slice, LazyPay, and ZestMoney grew fast. Then defaults spiked. Then the RBI tightened norms. Several shut down. The PM lesson: in lending, your north star metric is not disbursement volume. It is 90-day default rate. If you optimize for growth, you die at scale.
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India has 190 million credit-underserved adults. They have bank accounts (thanks to Jan Dhan) and phones (thanks to Jio) but no credit history. Building credit products for this segment requires alternative data — UPI transaction patterns, phone recharge frequency, utility payment regularity. This is a genuine product innovation frontier.
India-specific context: The India Stack — Aadhaar (identity), UPI (payments), DigiLocker (documents), ABDM (health) — is the most ambitious government-built digital infrastructure in the world. Every fintech product sits on top of it. If you do not understand how Aadhaar eKYC works, how UPI settlement flows, or what the Account Aggregator framework enables, you cannot build fintech products in India. This is not optional knowledge.
Edtech: where the buyer, the user, and the beneficiary are three different people
Indian edtech had its reckoning. BYJU’S went from a $22 billion valuation to near-bankruptcy. Unacademy laid off 1,000+ people. WhiteHat Jr shut down. Vedantu merged to survive.
The industry’s mistake was treating education like a consumer product. Run Facebook ads, acquire users (parents), optimize for conversion (enrollment), and measure success by revenue. The actual learning outcome — whether a student improved — was nobody’s OKR.
This is the fundamental tension in edtech PM: the buyer (parent), the user (student), and the beneficiary (the student’s future employer or college) are three different people with three different definitions of success.
| Stakeholder | What they want | What they measure | PM implication |
|---|---|---|---|
| Parent (buyer) | “My child should crack JEE/NEET” | Test scores, rank improvement | Your sales pitch is outcome-based but your product must deliver process |
| Student (user) | Engagement, not boredom | ”Do I want to open this app?” | Gamification helps retention but can mask learning gaps |
| College/Employer (beneficiary) | Actual competence | Performance in real tasks | No edtech company measures this — and that is the industry’s blind spot |
Edtech startup, post-BYJU's collapse. Board meeting on strategy pivot.
CEO: “Our CAC is Rs 12,000 per student. Average revenue per student is Rs 8,000. We are losing Rs 4,000 on every acquisition.”
Sales VP: “We can push annual packages. Rs 24,000 upfront, that fixes the LTV.”
PM: “What is our 90-day retention?”
Sales VP: “...28%.”
PM: “So 72% of students we acquire stop using the product within three months. Pushing annual packages means we collect more money from people who will stop learning in 90 days. That is not a business — that is a refund liability.”
CEO: “What do you propose?”
PM: “Fix the 90-day retention first. If a student is not logging in by day 14, intervene. Call them. Understand why. Our product problem is not acquisition — it is that the product does not create a habit.”
The company shifted from sales-led to product-led. They introduced a 14-day free trial with a human mentor check-in at day 3 and day 10. Paid conversion dropped from 15% to 8%, but 90-day retention jumped from 28% to 61%. Annual revenue per retained student tripled.
Edtech's original sin was optimizing for enrollment instead of learning. The companies that survived 2023-2024 were the ones that measured what mattered.
The PM lesson: In edtech, retention is the only metric that matters. A student who enrolls but does not learn will churn, leave a bad review, and damage word-of-mouth — which in Indian families travels faster than any ad campaign. The parent who spent Rs 24,000 on a course their child abandoned will tell every other parent in their network. Your NPS is set at the dinner table, not in-app.
India-specific context: Pragmatic Leaders — the PM training program I run — has trained over 10,000 professionals. The biggest lesson from running cohorts since 2018: completion rate is the leading indicator of everything. A cohort with 80% completion generates 3x more referrals than one with 50% completion, regardless of content quality. The product is not the content. The product is the structure that ensures people finish. Case-based learning, peer cohorts, weekly accountability — these are features, not pedagogy. They are retention mechanics.
Logistics: where the product is the physical world
Software PMs build products constrained by code and design. Logistics PMs build products constrained by roads, weather, labour laws, and the fact that a truck can only travel 250 km in a day on Indian highways.
Delhivery, India’s largest independent logistics company, processes 1.5 million shipments daily. Their product is not an app or a dashboard. Their product is a promise: this package will reach that pin code in X days. Everything else — the sorting centres, the route optimization algorithms, the delivery partner apps — exists to keep that promise.
The PM challenge in logistics is that your product has a physical constraint layer that does not exist in pure software:
| Software product constraint | Logistics product constraint |
|---|---|
| Server response time (ms) | Road transit time (hours/days) |
| API rate limits | Vehicle capacity limits |
| User session timeout | Delivery partner shift limits |
| A/B test results in days | Route optimization results in weeks |
| Rollback a bad deploy in minutes | Recall a misrouted shipment in… you cannot |
Delhivery’s PM innovation was not in the delivery app — it was in the middle mile. They built automated sorting centres that reduced per-shipment processing time from 4 minutes to 45 seconds. They used machine learning to predict shipment volume by pin code and pre-position inventory in forward warehouses. They built a real-time tracking system that reduced customer support calls by 60% — not because the UX was better, but because customers could see their package moving and stopped calling to ask where it was.
India-specific context: India’s logistics cost is 14% of GDP — compared to 8% in the US and 6% in Europe. This is not just a macro statistic. It means that for every product sold online, logistics eats a disproportionate share of the margin. A Rs 500 product with Rs 80 shipping cost has 16% of its value consumed by delivery. In tier-3 cities, that shipping cost can be Rs 120 because last-mile infrastructure is worse. The PM job in Indian logistics is relentless unit economics optimization — shaving Rs 2 off each shipment across millions of shipments. There is no glamour in it. There is enormous impact.
BigBasket demonstrated this during COVID-19. When demand surged 5x overnight, the product team made a brutal but correct decision: cut the product catalogue from 20,000 items to 2,000 essentials. They stopped serving individual houses and switched to apartment-level delivery only. They converted the BB Daily milk delivery fleet into an essentials delivery fleet. Every decision was about matching supply capacity to demand — not adding features. The PM who suggested dropping 90% of the catalogue saved the company.
The cross-cutting pattern
Four verticals, one insight: the domain is the product requirement.
In healthcare, your product must be faster than paper. In fintech, your product must be more compliant than your competitor. In edtech, your product must create habits, not just deliver content. In logistics, your product must respect physics.
Generic PM frameworks — prioritization matrices, sprint planning, user story formats — are necessary but insufficient. They are the grammar of product management. The vocabulary comes from the vertical.
The PMs who thrive in vertical products share three habits:
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They spend time in the field. Not user interviews over Zoom. Actual field time. Sitting in an OPD watching a doctor use your EMR. Riding with a delivery partner at 5 AM. Watching a student attempt a practice test and give up at question 7. The data tells you what happened. The field tells you why.
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They read regulation as product requirements. The RBI circular is not a legal document to hand off to compliance. It is a PRD from a stakeholder who can shut your company down. The ABDM specification is not an integration task — it is a product architecture decision. Read the primary sources.
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They build domain vocabulary early. A fintech PM who cannot explain the difference between a PPI and a full-KYC wallet will not earn the trust of their compliance team. A healthtech PM who does not know what a SOAP note is cannot design a clinical workflow. You do not need a medical degree or a banking license. You need to speak the language well enough to ask good questions.
Pick the vertical closest to your product (or pick one you want to break into). Answer these questions — not with generic PM thinking, but with domain-specific knowledge.
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Who is the regulator? Name the specific regulatory body. What was their most recent circular or directive that affected products in your space? What does it require?
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Who are the three most important stakeholders — and which one is NOT your user? Map the buyer, user, and decision-maker. Where do their incentives diverge?
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What is the physical or regulatory constraint that no amount of software can remove? In healthcare, it is consultation time. In fintech, it is KYC. In logistics, it is road infrastructure. In edtech, it is attention span. Name yours.
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What does your competitor’s product look like — from the inside? Sign up for it. Use it for a week. Not a demo. Not a competitor analysis deck. Use the product as a real user in your vertical would. Document every moment of friction and every moment of delight.
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What domain-specific metric matters more than NPS or DAU? In healthcare, it might be “time to diagnosis.” In fintech, “90-day default rate.” In logistics, “cost per shipment per km.” In edtech, “completion rate.” Name the metric that domain experts care about — the one that will never show up in a generic PM framework.
You are a PM at a healthtech startup building a patient records platform. You have 40 hospitals on the platform. The government just announced that ABDM health ID linking becomes mandatory for all digital health records within 6 months. Your platform does not currently support ABDM integration. Your CTO estimates 4 months of engineering work. You have two other major features in the pipeline that hospitals have been demanding — a billing module and a lab integration. Your sales team says you will lose 5 hospital renewals without the billing module.
Your quarterly roadmap is set. The billing module is committed for delivery in 8 weeks. The ABDM mandate gives you 6 months. Your CTO says you cannot do both in parallel — the team is 6 engineers. How do you prioritize?
your path
HealthifyMe's PM is deciding whether to build a native feature for diabetes management or partner with an existing diabetes management app and offer deep links from the HealthifyMe dashboard.
The call: Do you build native or partner, and what is the one question you'd answer before deciding?
HealthifyMe's PM is deciding whether to build a native feature for diabetes management or partner with an existing diabetes management app and offer deep links from the HealthifyMe dashboard.
The call: Do you build native or partner, and what is the one question you'd answer before deciding?
Where to go next
- Indian market context for these verticals: Indian Market Cases
- Pricing patterns that differ by vertical: Pricing and Monetization Cases
- Growth strategies shaped by vertical constraints: Growth and Acquisition Cases
- How to approach any case study systematically: How to Approach Case Studies