सSaral Shiksha Yojna
Courses/Technology Product Entrepreneurship

Technology Product Entrepreneurship

CS9.424
Ramesh Loganathan + Prakash Yalla•Monsoon 2025-26•4 credits
Sample Papers/TPE end-sem mock paper · Paper 3

TPE end-sem mock paper · Paper 3

Duration: 120 min • Max marks: 100

Part 1 — Higher-Order Concepts (20 Marks Total, @5 each)

0 marks
  1. 1.Customer Segments for a D2C Returns Platform A startup is building a returns-management platform that lets shoppers return online orders to any local kirana store instead of waiting for a pickup. Identify: a) One specific target customer; b) One key problem they face; c) Why they may pay for this solution; d) One way to test interest quickly.5 m
  2. 2.Problem–Solution Fit for Construction Site Safety A startup wants to use AI-powered cameras to detect safety violations (missing helmets, near-misses, blocked exits) at large construction sites. a) Who is the customer; b) What is the main problem; c) What is one simple MVP they can test first; d) What concern might *site supervisors* have that the founders may underestimate?5 m
  3. 3.Idea Hexagon — Electric Mobility Using the Idea Hexagon, generate six startup ideas in the electric-mobility space (e.g., charging infrastructure, battery management, fleet electrification, second-life batteries). Each idea must clearly specify the target user and the core problem being solved.5 m
  4. 4.Business Model Basics — D2C Foodtech A startup is building a subscription platform that delivers diabetic-friendly, dietitian-curated meals to homes in metro cities. Identify: a) One target customer segment; b) The core value proposition for this segment; c) One possible revenue model beyond the obvious subscription; d) One channel to reach customers.5 m
  5. 5.Your TPE Startup Idea (Bonus 5 Marks) Write down a one-line ad-lib for your idea as per the framework shared in class. State: a) Target user; b) Main customer pain; c) Product benefit; d) One gain for the customer. ---

Part 2 — Advanced Framework Application (40 Marks total, @20 each)

0 marks
  1. 1.Case: DriveSafe Telematics DriveSafe is building a plug-and-play telematics device for last-mile delivery fleet operators (5–100 vehicles each). The device tracks rash driving, fuel theft, and route deviation. Fleet owners like the cost savings, but drivers actively resist the device because it "monitors them." Some fleet owners have pulled out citing driver attrition. Three large incumbents already sell to enterprise fleets (>500 vehicles). Questions: a) Identify the beachhead customer segment (5) b) List two customer pains and two gains the product addresses (5) c) Explain how DriveSafe can differentiate from the large incumbents (5) d) Suggest one go-to-market strategy that handles the driver-resistance problem (5)20 m
  2. 2.Case: FarmFresh D2C FarmFresh is a D2C platform that delivers chemical-free vegetables directly from a curated network of organic farmers to urban households. Customers love the quality but churn at month 4 — they cite "limited variety" and "delivery slots that don't match my schedule." Acquisition cost is rising. The founders have 8 months of runway and one strategic decision to make. Questions: a) Identify two hypotheses the startup must test (5) b) Classify each as a problem risk or a solution risk (5) c) Suggest one MVP experiment to reduce month-4 churn (5) d) Propose one revenue model adjustment that could improve unit economics (5) ---20 m

Part 3 — Deep-Dive Case Study (40 Marks)

0 marks
  1. 1.D2C Returns Platform **a) Target customer:** D2C and mid-size e-commerce brands shipping >5,000 orders/month with return rates above 15% (apparel and footwear, primarily). **b) Key problem:** Reverse logistics for online orders costs them ₹80–₹150 per pickup, and customers churn when pickups fail or get delayed by 5–7 days. **c) Why pay:** A drop-off network reduces reverse-logistics cost by 40–60% per return *and* improves NPS because customers prefer immediate drop-off over waiting at home for a pickup. **d) Quick test:** Run a 30-day pilot in two pin codes with one D2C brand; offer their customers the drop-off option alongside the regular pickup option; measure adoption rate, cost saved, and NPS lift.
  2. 2.Construction Site Safety AI **a) Customer:** EHS (Environment, Health, Safety) heads at large infrastructure or real-estate developers running multi-site projects worth ₹500+ Cr. **b) Main problem:** Each site safety incident costs ₹5–50 lakh in penalties, project delays, and reputation damage; existing manual safety audits miss 40%+ of near-misses. **c) Simple MVP:** Install 4 cameras on one floor of one active site; run AI detection for 30 days; produce a weekly safety-incident report for the EHS head; compare with manual audit findings. **d) Underestimated concern by *site supervisors*:** They worry the system will be used to *blame them personally* when violations are flagged — even if leadership intends it for systemic improvement. Without their cooperation, the supervisors will train workers to hide violations from cameras, defeating the system. Founders need to think about how reporting protects supervisors, not exposes them.
  3. 3.Idea Hexagon — Electric Mobility 1. **Generalize:** Battery-management AI built for two-wheelers → generalize to three-wheelers, light commercial vehicles, marine, and even drones. Target: fleet operators across vehicle types; problem: range and battery lifespan optimisation. 2. **Fusion:** EV charging + lounge cafe → "charging destination" venues where users spend the 30–45 minutes productively. Target: long-distance EV drivers; problem: charging downtime. 3. **Find the Nails:** A high-precision motor-controller IP → apply to e-bikes, e-rickshaws, exoskeletons, robotics, agri-equipment. 4. **Find the Hammers:** Range anxiety problem → solutions include battery-swap stations, fast-charging networks, on-demand mobile chargers, in-vehicle range-extender packs, smart route planning. 5. **Add an Adjective:** *Modular* batteries — owners buy a base unit and add capacity packs as needed. Target: gig-economy drivers; problem: fixed battery costs don't match variable daily usage. 6. **Do the Opposite:** Instead of selling EVs to consumers, sell *vehicle-as-a-service* with a flat per-km fee that bundles vehicle, battery, charging, and insurance. Target: gig drivers who can't afford upfront vehicle cost; problem: capital intensity of going electric.
  4. 4.D2C Foodtech (Diabetic Meals) **a) Target segment:** Diagnosed Type-2 diabetics aged 35–60 in metros, in dual-income households where one person manages cooking, with monthly household income ₹1.5L+. **b) Value proposition:** Doctor- and dietitian-certified daily meals that maintain HbA1c targets without the family member having to plan, source, or cook — solving both the *health* job and the *labour* job. **c) Revenue model beyond subscription:** A *clinical outcomes* add-on — charge a premium tier where the platform tracks HbA1c quarterly (with a tied-up lab) and refunds part of the fee if targets aren't met. Drives adherence + creates defensible clinical data. **d) Channel:** Endocrinologist referrals — a one-time "diabetes diet starter pack" offered as a 7-day free trial through the doctor's clinic; the prescription pad doubles as the marketing channel.
  5. 5.Your TPE Startup Idea (Bonus) — sample *Ad-lib:* "For [solo founders running pre-seed deeptech startups] who [struggle to convert technical breakthroughs into clear investor narratives], our [AI-powered pitch architect] is a [strategic storytelling tool] that [generates investor-grade pitch decks from technical interview transcripts in 48 hours]. Unlike [generic deck templates], our product [is trained on funded deeptech pitches and outputs investor-specific narrative arcs]." **a)** Pre-seed deeptech solo founders. **b)** Translating technical depth into investor language. **c)** Investor-grade decks generated from a single technical conversation. **d)** Faster investor meetings booked, higher conversion to first cheque.
  6. 6.DriveSafe Telematics **a) Beachhead:** Small-to-mid fleet operators with **5–25 vehicles** running last-mile delivery for D2C brands. The deck's logic: avoid head-on combat with incumbents owning the >500-vehicle enterprise segment (the Eventbrite-vs-Ticketmaster pattern). These small fleets are price-sensitive but underserved, and they have less driver bargaining power so resistance can be managed differently. **b) Pains:** (i) Fuel pilferage and route deviation that erode already-thin margins; (ii) Constant disputes with brand customers over delayed deliveries with no objective data to back claims. **Gains:** (i) 10–15% fuel cost reduction; (ii) Verifiable, brand-customer-shareable delivery proof that wins more contracts. **c) Differentiation from large incumbents:** - *Pricing model* — pay-as-you-save (a % of verified fuel savings) instead of upfront hardware + monthly fee. - *Driver-friendly framing* — the device's interface gives drivers a "score" with weekly cash bonuses for good driving, flipping the surveillance narrative into a rewards narrative. - *Channel* — direct sales to small fleet WhatsApp networks via D2C-brand referrals, which the incumbents (selling to enterprise) cannot economically reach. **d) GTM that handles driver resistance:** Co-create a **driver bonus pool**: 50% of verified fuel savings go to a monthly pool distributed among top-driving drivers as cash bonuses. This (i) flips the narrative from "boss watching me" to "I earn more when I drive well", (ii) makes drivers internal advocates rather than blockers, and (iii) creates social proof — top-earning drivers attract better drivers to the fleet.
  7. 7.FarmFresh D2C **a) Two hypotheses:** - H1: Customers churn because the assortment is narrow (problem identified by users). - H2: Customers churn because the delivery windows are too rigid relative to their schedules. **b) Classification:** - H1 is partly a **solution risk** — customers may say "variety" but the *real* problem is the scheduling mismatch making the subscription feel like work. - H2 is a **problem risk** — the actual problem may not be "rigid windows" but a deeper retention issue (e.g., the wife/cook left, the household stopped cooking on weekdays, etc.). **c) MVP experiment to reduce month-4 churn:** Take the 200 most engaged month-3 customers; split into three cells of ~65 each. *Cell A:* offer them flexible delivery windows (4 slots, swap up to night before). *Cell B:* keep windows fixed but expand assortment by 50%. *Cell C:* keep windows fixed, assortment unchanged, but add a personal "produce assistant" on WhatsApp who suggests weekly meal ideas. Compare month-5 retention across cells. The result reveals whether the underlying problem is schedule, variety, or engagement. **d) Revenue model adjustment:** Move from a flat monthly subscription to a **credits-based** model — customers pre-buy ₹5,000 of credits that don't expire and unlock 10% extra value. This (i) fixes the rigid weekly-window problem (customers spend credits whenever they want), (ii) improves working capital, (iii) creates a sunk-cost bias that improves retention, and (iv) lets the brand layer premium SKUs without changing core pricing. ### Part 3 — MediSphere Telehealth **a) Strategic Evaluation (15 marks)** | Option | PMF | Revenue potential | Sales complexity | Scalability | |---|---|---|---|---| | Direct consumer (freemium app) | Strong in tier-1, weak in tier-2 | Moderate per user (₹500–₹800/consult); high CAC erodes margins | Low (no enterprise selling) but high marketing spend | **High** (purely digital) but CAC + churn cap growth | | Corporate employer (B2B2C) | Strong — HR has budget and pain (employee wellness mandates) | **High** — ₹500–₹1,000/employee/year × 5K–50K employees per deal | **High** — 4–6 month enterprise cycles, RFPs, HRIS integration | Moderate — sales cycle slows, but per-deal volume large | | Insurance partnership | Unproven — value depends on insurer regulation and member engagement | **Very high** at scale (per-active-user fee × millions of members) | **Very high** — multi-quarter cycles, IRDAI considerations | **Very high** — once one insu

Track your attempt locally — score and time are recorded in your browser. (Coming soon: timed-attempt mode.)