Groww is one of India’s leading digital investment platforms that allows users to invest in mutual funds, stocks, exchange-traded funds (ETFs) and more — all through a simple and intuitive mobile app and website. It was founded in 2016 with the vision of democratizing investing for millennials and first-time investors.
Groww simplifies investing by making it:
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B2C Table ⤵️
Criteria | User 1 | User 2 | User 3 | User 4 | User 5 |
Name | College Investor | Aspiring Middle-Class Earner | Busy Professional | Homemaker Saver | Young Salaried Investor |
Age | 18–23 | 24–30 | 30–38 | 28–40 | 25–30 |
Demographics | Tier 1/Tier 2 students, hostelers | Tier 2 salaried individuals | Tier 1 urban cities, metro crowd | Tier 2, Tier 3, household users | Tier 1/2, working professionals |
Need | Learn and experiment with investing | Start SIPs, save tax, build corpus | Maximize returns, save time | Safe savings and monthly planning | Invest salary savings systematically |
Pain Point | Low capital, lack of financial literacy | Complex onboarding, low trust | Time constraints, analysis overload | App complexity, fear of online scams | Too many options, unsure where to start |
Solution | Simplified learning tools, goal-based investing | Simple UI, vernacular onboarding | Auto-invest features, AI nudges | Safe, secure, easy walkthroughs | Goal-based onboarding, SIP suggestions |
Behavior | Curious, experimental | Cautious but regular | Impatient, task-oriented | Risk-averse, repeatable habits | Enthusiastic, data-driven |
Perceived Value of Brand | Youth-friendly, cool, trending | Trust-building, practical | Smart, credible, fast | Reliable, family-safe | Aspirational, smart choice |
Marketing Pitch | "Start small, learn big" | "Grow your money the smart way" | "Your time is money—invest wisely" | "Secure your future, one step at a time" | "Let your salary work for you" |
Goals | Learn investing, gain confidence | Start SIPs, save tax, learn basics | Set-and-forget investing | Regular, safe savings, small returns | Grow savings, beat inflation |
Frequency of use case | Low | High | Moderate | High | High |
Average Spend on the product | ₹500–1,000/month | ₹2,000–5,000/month | ₹5,000–10,000/month | ₹500–2,000/month | ₹3,000–6,000/month |
Value Accessibility to product | Very High | High | High | Moderate | High |
Value Experience of the product | Moderate | High | Very High | Low | High |
| Criteria | ICP 1 | ICP 2 | ICP 3 | ICP 4 | ICP 5 |
|---|---|---|---|---|---|
Adoption Rate | High | Moderate | Low | Moderate | High |
Appetite to Pay | Low | High | High | Low | High |
Frequency of Use Case | Low | High | Low | High | High |
Distribution Potential | High | High | Moderate | High | Moderate |
TAM (Users) | 1,000 | 1,400 | 1,100 | 1,500 | 1,200 |
Conclusion & Strategy Focus
Based on the prioritization table, ICP 2 (Aspiring Middle-Class Earner) and ICP 5 (Young Salaried Investor) show high value in use case frequency, payment appetite, and market size.
ICP 2: Aspiring Middle-Class User (e.g., Driver, Assistant, Entry-level Staff)
Demographics: Age 25–40, Tier 2/3 cities, mobile-first but low financial literacy
Psychographics: Wants safe savings, doesn’t trust market products yet, cautious and cost-sensitive
Goal Type | Ranking | JTBD | Validation Approach | Validation (Anecdotes & Insights) |
Functional | Primary | To open an account and start saving small amounts (₹100–₹500/month) with zero confusion | 1-on-1 interviews + prototype testing | “I want something simple to start saving. No big words. Just show me where to click and what I’ll get.” |
Financial | Primary | To protect money while still earning more than a savings account | Voice-of-customer + WhatsApp groups | “I don’t want to lose my money, but if it grows even a little more than the bank, I’ll try it.” |
Functional | Secondary | To onboard with zero dependency on documents beyond Aadhaar/PAN | Journey testing | “I don’t have my salary slip or rent proof. If it’s asking too much, I’ll just leave.” |
Financial | Secondary | To set a clear monthly goal (e.g., save for Diwali or school fees) | Observational + contextual feedback | “Tell me how much to save each month if I want ₹10,000 in 10 months.” |
ICP 5: Salaried Professional (e.g., Engineer, Analyst, Corporate Worker)
Demographics: Age 25–30, Tier 1/2 cities, steady income, digitally confident
Psychographics: Wants to optimize returns, save tax, automate wealth building, values UI/UX efficiency
| Goal Type | Ranking | JTBD | Validation Approach | Validation (Anecdotes & Insights) |
|---|---|---|---|---|
Functional | Primary | To get a fund suggestion based on salary/income and risk profile instantly | Funnel analytics + interviews | “Don’t make me choose from 50 options — just recommend based on what I earn and how aggressive I want to be.” |
Financial | Primary | To automate investments via SIP and track portfolio in a dashboard | In-app behavior + usability testing | “I want to set up ₹5000 SIPs and forget it. I’ll check my dashboard on weekends or during salary week.” |
Functional | Secondary | To complete KYC and onboarding in <5 mins (integrated via Digilocker, etc.) | Session replay + A/B testing | “Why do I need to upload everything manually? Can’t you just pull from Digilocker and auto-fill?” |
Financial | Secondary | To plan for tax-saving ELSS or salary-linked goals during onboarding | Feature prototyping + email surveys | “If you told me in Jan what to do for 80C, I’d plan SIPs better. I hate last-minute LIC investments.” |
Upon talking to active users & following a pattern amongst them, these are the major hypothesis written.
Hypothesis:
Users who create a watchlist within 3 days of onboarding are more likely to become active investors within 14 days.
Reason:
Creating a watchlist shows investment intent and product engagement. It indicates the user is exploring investment options and planning for the future. This step also helps the app personalize recommendations, increasing stickiness.
Hypothesis:
Users who invest once in the first week demonstrate strong intent-action consistency and have higher 30-day retention rates.
Reason:
Consistent browsing followed by investment shows progressive trust building and value realization.
Hypothesis:
Users who explore at least 4 unique screens during their first session post-onboarding are more likely to complete their first investment within 10 days.
Reason:
Exploration indicates curiosity and product interest. The more areas a user touches (e.g., “Mutual Funds,” “Stocks,” “Learn,” “Portfolio”), the more they're learning the value Groww can deliver.
Hypothesis:
Users who personalize their account (e.g., by adding nominees, customizing investment goals) show higher retention over 30 days.
Reason:
Customization increases a sense of ownership and perceived value. It shows the user is setting up for the long-term.
Activation Metrics Framework
| Metric | Why It's Important | Target Context for Groww App |
|---|---|---|
D1, D7, D30 Retention | Measures how many users return to the app after 1, 7, and 30 days. Key to identifying stickiness of onboarding experience. | D1: Completed onboarding D7: Started SIP or browsed fund D30: Portfolio active or referral made |
DAU / MAU (Stickiness) | Indicates how often users engage with the product monthly. A DAU/MAU > 0.2 usually suggests high engagement. | Daily app opens, investment dashboard views, or checking returns |
Subscription Rate vs Retention | Tracks how many users complete goal-based SIPs vs how long they stay. Higher this delta, stronger your activation funnel. | % of users who set up SIP within 7 days, and how many are still active by D30 |
Average TAT (Time to Activation) | Measures average time taken from sign-up to first meaningful action (e.g. SIP started). | Benchmark: < 5 minutes from install to KYC complete; < 30 minutes to first SIP |
User Cohorts | Understand how different user segments behave over time. Can help detect what’s working for ICP 2 vs ICP 5. | Cohort by: city, acquisition channel, profession (student vs salaried), app version |
Acquisition Source | Helps identify the best-performing channels for users who activate and retain. | e.g., WhatsApp group vs referral vs Facebook ad vs app store vs offline sales |
Product Reviews & CSAT | Track user sentiment to identify friction points in onboarding or first-use. | Review keywords: “easy to use,” “confusing,” “quick KYC,” “trustworthy,” etc. |
Feature Adoption | Tracks which onboarding or investment features users actually use. | e.g., % who used KYC via Digilocker, % who clicked “Auto-Suggest SIP” |
Drop-off Analysis (Funnel) | Identify where users leave during onboarding or first fund purchase. | Example funnel: App Install → Sign Up → KYC → Add Bank → Browse Funds → Invest → Setup SIP |
Goal Completion Rate | How many users complete financial goals or set milestones during onboarding. | e.g., % who select a financial goal (like “Buy a Bike”) → invest accordingly |
NPS (after activation) | Collect feedback from users 7–14 days post-activation to measure advocacy. | Ask: “How likely are you to recommend Groww to a friend?” and collect feedback |
Session Duration & Depth | How long and how deep users engage in their initial sessions — indicates quality of onboarding experience. | e.g., Avg time spent on onboarding flow, number of screens visited, or tutorial watched |
Support Tickets/FAQ views (early stage) | Indicates onboarding friction — high support volume signals issues in flow or clarity. | Look at spikes in questions around “KYC stuck,” “what is SIP,” or “how to withdraw money” |
Reminder: This is not the only format to follow, feel free to edit it as you wish!
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