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 2

TPE end-sem mock paper · Paper 2

Duration: 120 min • Max marks: 100

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

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  1. 1.Customer Segments for an MSME Lending Platform A startup is building an AI-driven credit-scoring tool that lets banks underwrite loans for small kirana stores and mid-tier retailers without traditional credit histories. 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 a Mental Health App A startup wants to help working professionals manage everyday anxiety through a guided journaling and breathing-exercise app. a) Who is the primary customer; b) What is the main problem; c) What is one simple MVP they can test first; d) What concern might *users* have that the founders may underestimate?5 m
  3. 3.Idea Hexagon — Climate & Sustainability Tech Using the Idea Hexagon, generate six startup ideas in the climate and sustainability space (e.g., carbon accounting, waste-to-energy, supply-chain ESG tracking, sustainable packaging). Each idea must clearly specify the target user and the core problem being solved.5 m
  4. 4.Business Model Basics — Logistics SaaS A startup is building a SaaS platform that helps mid-size e-commerce sellers automate last-mile shipment tracking and customer notifications across multiple courier partners. Identify: a) One target customer segment; b) The core value proposition for this segment; c) One possible revenue model; 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)

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  1. 1.Case: VoiceMed Diagnostics VoiceMed is building an AI tool that listens to a patient's voice for 30 seconds and detects early signs of respiratory illness (asthma, COPD, lung-fibrosis). Pulmonologists in tier-1 hospitals are intrigued but reluctant to use it without published clinical evidence. Tier-2 city diagnostic chains, however, are willing to deploy it as a triage tool today. A few global incumbents have announced similar features but are not yet shipping in India. Questions: a) Identify the beachhead customer segment (5) b) List two customer pains and two gains the product addresses (5) c) Explain how VoiceMed can differentiate from incumbent global competitors (5) d) Suggest one go-to-market strategy for early adoption (5)20 m
  2. 2.Case: SkillBridge Upskilling SkillBridge is a B2B platform that helps mid-size IT services companies upskill their engineers on new-stack technologies (AI, cloud, security). HR managers love the dashboards, but engineers complete only 18% of the courses they enroll in. Engineering managers say the content is too generic. The founders need to make their next 6 months count before the seed runway runs out. 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 improve course completion (5) d) Propose one revenue model that aligns incentives across HR managers, engineers, and engineering managers (5) ---20 m

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

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  1. 1.MSME Lending Platform **a) Target customer:** Tier-2 regional cooperative banks or NBFCs underwriting working-capital loans of ₹2–25 lakh to retailers in tier-2/3 cities (not the kirana store itself — the lender is who pays). **b) Key problem:** Their underwriting teams reject 70%+ of MSME applications because traditional bureau scores don't capture MSME cash-flow reality, leading to lost interest income and unmet demand. **c) Why pay:** Each additional approved loan generates ₹20K–₹2L in interest income over its tenure; even a 5% lift in approval rate justifies a SaaS fee of a few hundred rupees per application. **d) Quick interest test:** Run a free 30-day "shadow scoring" pilot with one branch — score 200 of their past rejected applications and show how many would have been good loans in hindsight.
  2. 2.Mental Health App for Working Professionals **a) Primary customer:** Working professionals aged 25–40 in metros, in high-stress roles (tech, consulting, finance), already comfortable with self-help apps. **b) Main problem:** Persistent low-grade anxiety affecting sleep and focus; therapy feels too clinical, social channels feel too public, no acceptable mid-point exists. **c) Simple MVP:** A WhatsApp bot that sends one journaling prompt and one 60-second breathing exercise daily; track engagement and self-reported anxiety changes over 4 weeks across 100 users. **d) Underestimated user concern:** Data privacy and the fear of being identified — journal entries reveal sensitive thoughts about work, relationships, employers. Many will silently churn if they can't trust the app with their thoughts.
  3. 3.Idea Hexagon — Climate & Sustainability 1. **Generalize:** Carbon accounting for SMEs (currently exists for large corps) — target users: mid-size manufacturers; problem: BRSR/ESG reporting compliance. 2. **Fusion:** Carbon tracking + e-commerce checkout → embed a carbon offset purchase at point-of-checkout for D2C brands. 3. **Find the Nails:** Existing remote-sensing satellite imagery → also detects illegal waste dumping, deforestation, methane leaks (multiple end-users: regulators, insurers, NGOs). 4. **Find the Hammers:** Reduce delivery emissions — solutions span EV fleets, shared lockers, drone delivery, micro-fulfilment hubs (target user: D2C brands; problem: emissions reporting + cost). 5. **Add an Adjective:** *Real-time* carbon accounting for textile factories — target: garment exporters; problem: EU CBAM compliance with monthly proof points. 6. **Do the Opposite:** Instead of measuring carbon emitted, measure *carbon avoided* — a marketplace verifying and monetising avoidance credits for industries adopting circular practices.
  4. 4.Logistics SaaS for E-commerce Sellers **a) Target segment:** Mid-size D2C sellers shipping 1,000–10,000 orders/month across 3+ courier partners (Delhivery, Bluedart, Shadowfax, India Post). **b) Value proposition:** One unified dashboard + branded buyer-facing tracking page that cuts "where is my order?" support tickets by 60% and surfaces SLA breaches across courier partners in real time. **c) Revenue model:** Per-shipment SaaS pricing (₹2–4/shipment) with a base subscription, plus a premium tier for branded tracking pages and proactive notifications. **d) Channel:** Integration partnerships with leading D2C ecommerce platforms (Shopify India, Dukaan, BigCommerce) where the founders ride the host platform's user base.
  5. 5.Your TPE Startup Idea (Bonus) *Sample ad-lib in the deck's format:* "For [overworked operations heads at mid-size manufacturing plants] who [struggle to detect machine failures before unplanned downtime], our [predictive-maintenance AI on edge devices] is a [maintenance intelligence platform] that [predicts failures 7 days in advance, cutting downtime by 40%]. Unlike [reactive condition-monitoring vendors], our product [needs no PLC retrofit and pays back in under 6 months]." **a)** Operations head at a mid-size auto-component plant. **b)** Unplanned downtime costs ₹2–8 lakh per shift; current condition monitoring is reactive. **c)** Predicts failures 7 days in advance; cuts downtime by 40%. **d)** Quantifiable monthly savings + a calmer maintenance team.
  6. 6.VoiceMed Diagnostics **a) Beachhead segment:** Tier-2 city diagnostic chains running 2–10 centres each — they want differentiation against tier-1 incumbents, have lower regulatory thresholds for triage tools, and are willing to deploy quickly. The deck's "uncontested market, gain scale, attack later" logic (à la Eventbrite vs Ticketmaster) applies directly. **b) Pains:** (i) Patients waiting weeks for pulmonologist appointments; (ii) Diagnostic centres losing follow-up revenue when patients abandon care. **Gains:** (i) Differentiated AI-powered triage as a customer-facing service; (ii) Higher conversion from screening to full diagnostic packages. **c) Differentiation from global incumbents:** Three vectors — (i) **Indian voice data** (proprietary dataset across dialects, accents, regional respiratory conditions) = Tier-1 USP (cannot imitate); (ii) **Regulatory positioning** as a *triage* tool, not a diagnostic, side-stepping the 24-month clinical-trial path incumbents must take; (iii) **Channel ownership** — direct integration with diagnostic-chain LIMS, which incumbents will not bother with at this market size. **d) GTM strategy:** Build a 5-city, 50-centre beachhead with one diagnostic chain on a revenue-share model (₹50 per screen, no upfront cost). Use the resulting volume to seed clinical evidence for pulmonologist adoption *next*, exactly mirroring HubSpot's "win one segment, then expand."
  7. 7.SkillBridge Upskilling **a) Two hypotheses:** - H1: HR managers will pay for engineer upskilling even without engineer completion (they value the dashboards for compliance reporting). - H2: Engineers will complete more courses if content is project-specific to their current work (vs generic certifications). **b) Classification:** - H1 is a **solution risk** — the solution (dashboards) might not be what the buyer actually values. - H2 is a **problem risk** — the *real* underlying problem may not be "lack of upskilling content" but "no time / no project relevance." **c) MVP experiment:** Pick 100 engineers across two pilot companies. Half receive generic AI/cloud courses, half receive project-specific micro-modules tied to their current sprint backlog (curated weekly by their engineering manager). Compare completion rates and self-reported applied learning at 6 weeks. **d) Revenue model:** Per-completion outcome pricing — companies pay a base subscription plus a fee for every engineer who completes a course *and* applies it on a real project (verified by engineering manager sign-off). This aligns HR (compliance metrics), engineering managers (applied output), and engineers (rewarded effort) — and forces SkillBridge to design completable, relevant content. ### Part 3 — GreenGrid Energy **a) Strategic Evaluation (15 marks)** | Option | PMF | Revenue potential | Sales complexity | Scalability | |---|---|---|---|---| | Mid-market hotels (subscription) | Moderate-Strong — early signal (14–18% savings); low contract resistance is the main risk | Moderate — ₹8–15K/property/month × thousands of properties | **Low** — single GM is buyer; 2–6 week cycles | **High** — replicable playbook, light onboarding | | Large commercial offices (enterprise SaaS) | Strong — 22% savings is a clear ROI story | **High** — ₹3–10 lakh/property/year on long contracts | **High** — 6–9 month procurement, BMS integrations | **Low–Moderate** — each deal is custom, hard to clone | | DISCOM partnership (per-kWh) | Unproven — depends on regulatory tailwind and DISCOM appetite | **Very high** at scale (per kWh × millions of kWh) but slow to mature | **Very high** — multi-stakeholder, regulatory cycles | **Very high** — once one DISCOM works, the model scales across states | **b) Recommendation (10 marks)** With only **15 months of runway**, the path must produce revenue *and* PMF evidence inside that window. Therefore: **start with mid-market hotels**, then layer enterprise offices in month

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