Criteria | ICP 1: The Social Fitness Seeker | ICP 2: The Competitive Athlete | ICP 3: The Family-Oriented Facilitator |
|---|---|---|---|
Who they are | Young professionals & college students | Semi-pro/serious sports enthusiasts | Parents booking activities for children |
Name (Persona) | Pankaj | Arjun | Aakansha |
Age | 18–35 | 25–40 | 35–45 |
Demographics | Urban, upper middle class, active | Urban, sports-driven, tech-savvy | Upper middle class, living in housing communities |
Need | To socialize, stay active, reduce stress | Find serious matches & improve skill | Engage kids in safe, structured physical play |
Pain Point | Difficulty coordinating group activities | Hard to find quality, skill-matched games | Hard to find verified, kid-friendly venues |
Solution | Easy discovery of casual group games | Structured leagues, leaderboards, filters | Bookings with verified coaches/venues |
Behavior | Casual gameplay 1–3x/week, mixed gender | Regular weekend gameplay, data-driven | Weekly bookings, high parental involvement |
Perceived Value of Brand | Fun, flexible, dependable | Credible, structured, high-skill | Safe, trusted, child-focused |
Goals | Fitness, socializing, stress relief | Skill-building, ranking, routine, health | Child development, screen-free time |
Frequency of Use Case | Moderate–High (1–3x/week) | High (3-5x/week) | Low–Moderate (weekly or biweekly) |
Avg Spend on Product (₹) | ₹300–₹1200/month | ₹1500–₹2500/month | ₹1000–₹1500/month |
Value Accessibility | High – nearby venues + group invites | Medium – relies on curated match types, has organised groups with fixed invites | Medium – limited kids options |
Value Experience | Moderate–High – ease + repeat fun | High – performance, tracking, opponent levels | High – safety, trust, parent-friendly flow |
Criteria | ICP 1: Social Fitness Seeker | ICP 2: Competitive Athlete | ICP 3: Family-Oriented Facilitator |
|---|---|---|---|
Adoption Rate | High — social + fitness-oriented | Moderate — selective, high expectation | Moderate — onboarding friction, needs trust |
Appetite to Pay | Moderate to High — price-sensitive but consistent | High — pays for leagues, coaching, competition | High — willing to spend for safety, quality |
Frequency of Use | High — 1–3x/week casual play | High — regular bookings, training | Low–Moderate — weekly/biweekly use |
Distribution Potential | High — group invites, friend networks | Moderate — niche communities | Low — mostly parent-driven, less social virality |
TAM Estimate | ~15–20M users (18–35 urban) | ~4–5M users (competitive adult players) | ~3–4M users (urban parents w/ kids 5–15) |
Basis the Table, ICP 1 seems to be the primary target along with ICP 2
A table is shared below for your reference to put down your user goals, respective ICPs, JTBDs and validate your goals.
After analysing user behaviour of the targeted ICps, and use cases across ICPs
"When I want to play a sport, I want to easily find and book games or venues with like-minded people nearby, so I can stay active, social, and consistent."
Goal Priority | Goal Type | ICP | JTBD | Validation approach | Validation |
Primary | Functional + Social | ICP 1: Social Fitness Seeker | Make it easy to discover, join, or organize casual games with nearby friends or people with similar interests | User interviews | “I just want to find a match nearby that works for my schedule and vibe that helps me avoid gym & still keep me in shape” |
Primary | Functional | ICP 2: Competitive Athlete | Provide a structured, reliable way to book skill-matched games and improve performance consistently | User interviews | “I don't want to struggle finding groups of motivated people. I want consistency and a certain sense of competitiveness when it comes to sport” |
*User Interviews were only from an ICP perspective & not from onboarding since they were already onboarded users who had been using the app for months*

*This screen pops up when you click on play at the top*
*This screen pops up when you click on book at the top*
*This screen pops up when you click on Train at the top*


Reasoning:
Completing a booking early demonstrates immediate value realisation from the app. It indicates that the user has understood the core function — booking sports venues — and has overcome any barriers related to timing, trust, or availability. The action typically leads to higher retention, especially when it's a seamless experience. Users who complete a game quickly are more likely to return for more, invite others, or even become recurring users.
Metrics to track:
Reasoning:
Playo is inherently social — players often coordinate in groups. Group participation reflects higher commitment and dramatically increases stickiness. These users are likely to return due to peer accountability and shared schedules. It also unlocks secondary features like recurring bookings or team challenges, further deepening engagement.
Metrics to track:
Reasoning:
This behavior signals intent to play and to do so socially, which aligns closely with core value delivery. It means the user isn't just browsing but is actively trying to organize or join a session. This use of community matchmaking tools also introduces them to new engagement surfaces like chat, notifications, and feedback loops.
Metrics to track:
Reasoning:
If a user selects their preferred sport(s) and location during onboarding, they are more likely to find relevant games and venues faster, leading to increased engagement and eventual conversion.
This setup reduces cognitive load by filtering irrelevant content and provides an early sense of personalization. It signals mild commitment and primes the user to explore nearby activities. While not a strong standalone activation, it creates the groundwork for faster value realization by aligning the app with the user's intent.
Metrics to track:
Reasoning:
Structured formats lock users into routines (e.g., weekly training), increasing long-term engagement. These users are more committed and often have higher LTV due to recurring sessions and higher ARPU products. They also tend to convert into brand advocates or invite other participants.
Metrics to track:
Given we've listed out multiple hypothesis, let's pick/prioritise them on the basis of the fundamental questions on which we judge activation metric for an early stage product:
# | Hypothesis | Demonstrates Commitment? | Realizes Product Value? | Affects Conversion? |
|---|---|---|---|---|
1 | User completes their first game booking within 24–48 hours of installing the app. | ✅ Strong signal of intent and time investment | ✅ Core value (game play, sport activity) is realized | ✅ Directly impacts activation → conversion |
2 | User joins or creates a group/team with at least 3 other members. | ✅ Social commitment, increases long-term stickiness | ⚠️ Partial – value depends on actual game participation | ✅ Increases likelihood of return/conversion |
3 | Users who use the "Find a Player" or send a game invite within their first 3 sessions are activated. | ✅ Shows stickiness and developing habit | ✅ Reinforces product value over time | ⚠️ Indirect – post-activation, supports retention |
4 | User adds a sport preference and location, enabling personalised discovery. | ⚠️ Weak commitment – easy to do | ⚠️ Value not realized until actual booking | ✅ Helps targeting and conversion later |
5 | User enrolls in a structured offering (coaching, league, tournament) within 14 days is activated. | ✅ Social trust + intent to spread usage | ⚠️ Yes, but success depends on the coach | ✅ Can drive new installs + boost conversion funnel |
With this we can conclude that the first hypothesis is the one which we should go for as it ticks all the boxes.
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