Synthesizing all research, personas, empathy maps, and journey maps into structured problem definitions — using POV Statements, Jobs To Be Done (JTBD), and a Refined Problem Statement to guide the design phase.
Format: [User] needs [need] because [insight]
Mani, a 24-year-old tech-savvy software engineer who shops online 4-6 times per month, needs a single, authoritative platform where every review is from a verified purchaser with proven usage duration because despite having the technical skills to spot fake reviews, he still spends 20-30 minutes per purchase cross-checking 3-4 platforms, and even then makes decisions based on "least suspicious" rather than "most trusted" — revealing that individual skill cannot compensate for a structurally broken review ecosystem.
| Component | Detail |
|---|---|
| User | Tech-savvy young professional, frequent online shopper |
| Need | Single trusted review source with verified purchase proof and usage context |
| Insight | Even the most skilled users cannot overcome a systemically broken system through individual effort alone. The problem is architectural, not educational. |
Kirana, a 26-year-old teacher and mother who shops online for her family including her 2-year-old daughter, needs a review platform that guarantees authenticity without requiring her to have technical detection skills because she cannot distinguish genuine from fake reviews, has suffered real consequences (allergic reaction from a fake-reviewed skincare product), and currently relies on slow WhatsApp verification from friends — representing the vulnerable majority of consumers who trust what they read and have no fallback when that trust is exploited.
| Component | Detail |
|---|---|
| User | Moderate-tech-literacy mother, shops for family, high-stakes categories (baby, skincare) |
| Need | Built-in trust that doesn't require user verification skills |
| Insight | The majority of consumers lack the ability to detect fake reviews. When the platform doesn't protect them, the consequences can be physical (health), not just financial. The burden of trust should be on the platform, not the user. |
Ravi, a 30-year-old small business owner who sells quality electronics accessories on Amazon India, needs a marketplace where product reviews can only come from verified purchasers and where competitor-planted fake reviews are structurally impossible because his genuine products with 50 honest reviews are systematically outranked by competitors with 500 fake reviews, and fake 1-star attacks cost him ₹1-1.5 lakh per incident while platform reporting takes 4-6 weeks — creating a system that actively punishes honesty and rewards manipulation.
| Component | Detail |
|---|---|
| User | Small business owner, honest seller, both buyer and seller perspective |
| Need | Level playing field where genuine product quality determines success |
| Insight | The fake review problem is two-sided — it hurts buyers AND honest sellers. Sellers face an ethical dilemma where staying honest has direct financial consequences. A prevention-first system protects both sides simultaneously. |
Online consumers and honest sellers in India need a review ecosystem where authenticity is structurally guaranteed through purchase verification, not retrospectively detected through AI because the current detection-based approach catches only 40-60% of fake reviews, costs consumers $770.7B globally, forces users to spend 23+ minutes cross-checking per purchase, causes health risks from fake-reviewed products, and punishes honest sellers who refuse to buy fake reviews — while no existing platform among 12 competitors enforces mandatory purchase verification, leaving a fundamental gap between what 85% of consumers demand and what any platform currently delivers.