The SPARK Doctrine
View section →The founding principle that governs every decision in this playbook.
Attention vs. Action
The global dating app industry is built on a single business model: maximise time-in-app. Every swipe, every notification, every algorithmic nudge is designed to keep users scrolling. This model is profitable because it sells advertising and premium subscriptions to people who never actually meet.
SPARK is built on the opposite principle.
| Traditional Apps | SPARK |
|---|---|
| Optimise for attention | Optimise for action |
| Measure success by time-in-app | Measure success by real-world meetings |
| Revenue from engagement | Revenue from outcomes |
| Infinite scroll, infinite swipes | Scarcity mechanics, intentional choices |
| Algorithm decides who you see | Algorithm + events + curation |
| Success = user stays on app | Success = user meets someone and returns |
Why This Distinction Wins
Attention-based apps create a paradox: the more successful they are at keeping users engaged, the less likely those users are to meet anyone. Users who meet people and form relationships leave the app. So attention-based apps are financially incentivised to prevent real connection.
SPARK breaks this model. Our business succeeds only when users succeed. A user who meets someone great, has a wonderful experience, and tells five friends — that is our growth engine. That is our product-market fit signal. That is our North Star.
THE SPARK DOCTRINE: Every product decision, growth tactic, and operational system must move users from Match to Meet faster. If a feature increases time-in-app without increasing meetings, it is the wrong feature. If an acquisition channel brings users who never meet anyone, it is the wrong channel.
The Three Strategic Bets
SPARK is built on three bets that traditional apps have not made:
Bet 1 — Real-world events are a competitive moat. No app at scale has made offline events the core product. Events create stories, stories create referrals, referrals create density. This loop cannot be replicated by a competitor who adds an "events" tab to their app.
Bet 2 — Female supply is the entire business. Every marketplace that has cracked female-first acquisition has won. Tinder won campuses because sororities joined before fraternities. Bumble won because women felt safe. SPARK wins because women have the best experience of any dating platform they have ever used.
Bet 3 — Bangkok is the perfect first city. Dense, young, international, social, underserved by quality dating products. Bangkok is not a test market — it is the proof of concept for a global rollout.
1.1 CEO Mission & North Star
View section →North Star Metric: Weekly Real-World Meetings
Every product, growth, and operational decision must increase this number.
SPARK exists to move people from Match → Chat → Book → Meet. The core objective is real-world meetings between users. Every decision in product, growth, and operations should increase the number of successful real-world meetings per week.
Supporting Metrics
| Metric | Target | Description |
|---|---|---|
| Female Referral Rate | ≥35% | Primary organic growth signal |
| Match → Meeting Rate | ≥15% | Core product health metric |
| Active Users in Dense Districts | ≥3,200 | Thonglor + Ekkamai + Asoke target |
| Event Attendance | ≥85% | Fill rate target per event |
What SPARK Is — And Is Not
| SPARK IS | SPARK IS NOT |
|---|---|
| A real-world interaction network | An events company |
| A mobile-first dating platform | A social club or nightlife brand |
| An intent-based matching system | A matchmaking service |
| A scalable global consumer platform | A local Bangkok-only product |
CEO MANDATE: Every meeting must generate content or referral. If a user meets someone on SPARK and doesn't post about it, that is a missed acquisition event.
1.2 CEO Dashboard (Daily Metrics)
View section →The CEO reviews this dashboard every morning. Total review time: under 10 minutes. Any metric in the red zone triggers an immediate action.
Daily Metrics
| Metric | Target | Warning | Red Flag → Action |
|---|---|---|---|
| New installs | 30+/day | 15–30 | <15 → boost paid social + connector outreach |
| Female signups | ≥50% of installs | 45–50% | <45% → pause male onboarding, activate female channels |
| Profile completions | ≥65% | 55–65% | <55% → simplify onboarding flow |
| Sparks sent | 2+ per user/week | 0.5–2 | <0.5 → run manual match curation |
| Matches created | ≥2 per active user | 1–2 | <1 → manually curate matches |
| Meetings scheduled | 10+/week (Phase 1) | 5–10 | <5 → push experience suggestions |
| Meetings completed | ≥70% of scheduled | 50–70% | <50% → add event invitations, reduce friction |
Weekly Metrics
| Metric | Target | Warning | Red Flag → Action |
|---|---|---|---|
| Active users | See war plan | Below target | → review acquisition channels |
| District density | 800+ per Tier 1 district | 400–800 | <400 → concentrate all acquisition in core districts |
| Female referral rate | ≥20% | 10–20% | <10% → activate WOM mechanics, NPS loop |
| Event attendance | ≥85% | 70–85% | <70% → improve targeting and confirmation systems |
DASHBOARD RULE: If any red flag appears, that metric becomes the single priority for the day. Do not work on anything else until it is resolved.
SPARK Red-Flag Monitor
Check this weekly. If any metric falls into the Warning or Red Flag zone, take the prescribed action immediately. If two or more red flags appear simultaneously, the marketplace is entering a liquidity danger zone — escalate all four priority actions at once.
OPERATOR RULE: Two or more simultaneous red flags = liquidity danger zone. Immediate priority actions: (1) increase curated matches, (2) improve female acquisition, (3) boost event energy, (4) stimulate referrals.
1. Liquidity Health
| Metric | Healthy | Warning | Red Flag | Action |
|---|---|---|---|---|
| Matches per user | 2–5 per active user | 1–2 matches | Below 1 match | Manually curate matches and adjust algorithm prioritisation |
| Time-to-first-match | < 24 hours | 24–48 hours | 48+ hours | Increase curated matches and highlight active profiles |
2. Gender Balance
| Metric | Healthy | Warning | Red Flag | Action |
|---|---|---|---|---|
| Platform female ratio | 50–60% | 45–50% | Below 45% | Pause male onboarding and accelerate female acquisition |
| Event gender balance | 55% women / 45% men | 50/50 | Below 45% women | Invite additional female attendees from waitlist |
3. Meeting Conversion
| Metric | Healthy | Warning | Red Flag | Action |
|---|---|---|---|---|
| Match → Meeting rate | 15–25% | 10–15% | Below 10% | Increase experience suggestions and reduce chat friction |
4. Engagement Health
| Metric | Healthy | Warning | Red Flag | Action |
|---|---|---|---|---|
| Sparks sent per user | 3–6 per week | 1–3 | Below 1 | Improve match quality, add ice-breakers, push Spark prompts |
| Chat start rate | 60–70% | 40–60% | Below 40% | Add conversation starters, review match quality |
Monthly KPI Targets (April → September)
| KPI | Apr | May | Jun | Jul | Aug | Sep |
|---|---|---|---|---|---|---|
| Total Users | 1K–2K | 3K–5K | 5K–8K | 7K–12K | 10K–16K | 14K–22K |
| D30 Retention | 18–22% | 20–25% | 22–28% | 24–30% | 25–32% | 26–33% |
| Premium CVR | 5–8% | 8–12% | 10–15% | 12–18% | 14–20% | 15–22% |
| Referral Rate | 15–20% | 20–30% | 28–38% | 30–40% | 32–42% | 35–45% |
| MRR | $1K–3K | $3K–8K | $6K–18K | $10K–28K | $16K–42K | $22K–60K |
| Events/Month | 0 | 0 | 4–6 | 8–12 | 10–16 | 12–20 |
| Event NPS | N/A | N/A | 45–55 | 50–60 | 52–62 | 55–65 |
| CAC (install) | $8–20 | $5–12 | $4–10 | $3–8 | $3–7 | $2–6 |
1.3 Founder Operating System
View section →Marketplace companies require founder-led execution during early stages. The founder is not just a strategist — they are the chief matchmaker, community builder, and marketplace engineer during the launch phase.
FOUNDER RULE: The founder should be the most active user on the platform during the first 90 days. Personally introduce users. Personally recruit connectors. Be at every event.
Daily Rhythm
| Time | Focus | Key Actions |
|---|---|---|
| Morning | Metrics & Curation | Check installs (target: 10+ female, 5 male waitlist); check gender ratio (must be ≥50% female); check Spark → meet conversion rate; review 5 new user profiles; manually curate 3 matches for new users |
| Afternoon | Outreach | Connector outreach: 3–5 DMs daily; influencer conversations (1–2 per day); community partnership follow-ups; 3 community partnership outreach messages; respond to all user feedback |
| Evening | Community Building | Attend 1 social venue in Thonglor/Ekkamai; recruit 2–3 connectors in person; observe user behaviour at venue; introduce SPARK to 3–5 people; capture 1 piece of social content |
Weekly Rhythm
| Day | Focus | Key Actions |
|---|---|---|
| Monday | Marketplace Health Review | Review all 10–15 dashboard metrics; check gender ratio — intervene if female < 50%; review match quality and time-to-first-match; set 3 priorities for the week |
| Tuesday | Influencer Outreach & Partnerships | Review influencer content pipeline; brief creators for upcoming posts; identify new nano-influencer candidates; respond to partnership enquiries |
| Wednesday | Product Feedback & User Interviews | Review app feedback and support tickets; conduct 2–3 user interviews; prioritise product improvements; review onboarding funnel drop-off |
| Thursday | Community Outreach & Connector Meetings | Meet 2–3 super-connectors or ambassadors; review ambassador pipeline; attend community events or networking; identify new female acquisition channels |
| Friday | Strategic Partnerships & PR | Venue relationship management; press and media outreach; corporate partnership conversations; review weekly metrics vs. targets |
| Saturday | Attend Events & Observe | Attend SPARK event (Phase 3+); observe user interactions directly; collect qualitative feedback; identify product improvement opportunities |
| Sunday | Strategy Review & Planning | Weekly retrospective: what worked, what failed; plan next week's priorities; review cohort data and retention indicators; update war plan if any red flags detected |
Founder Responsibilities Summary
| Daily | Weekly | Monthly |
|---|---|---|
| Check gender ratio | Review all dashboard metrics | Full PMF gate review |
| Review new user profiles | Update 90-day calendar | Connector network audit |
| Seed 3+ curated matches | Debrief last event | Budget vs. actual review |
| Contact 5 connectors | Plan next event | User interview (5 users) |
| Monitor Spark→Meet conversion | Review influencer content | Check CAC by channel |
Founder Decision Framework
| Trigger Condition | Immediate Action | Priority |
|---|---|---|
| Female ratio < 45% | Pause male signups immediately. Activate all female acquisition channels. | CRITICAL |
| Spark→Meet < 15% | Manual match seeding. Direct user introductions. Review algorithm. | CRITICAL |
| Daily installs < 20 | Double connector outreach. Review paid social creative. Activate ambassadors. | HIGH |
| Event NPS < 7 | Debrief within 24 hours. Identify root cause. Change 3 things for next event. | HIGH |
| WOM referrals < 20% | Activate story prompt mechanic. Review referral incentive. | HIGH |
| Any metric in red for 7 days | Activate Pivot Decision Tree. Do not wait. | CRITICAL |
1.4 Daily Founder Execution Checklist
View section →Daily Founder Targets
| Target | Goal |
|---|---|
| Female users recruited | 10 per day, in person or DM |
| Male waitlist signups | 5 premium waitlist only |
| Community partnerships | 3 outreach messages per day |
| Connectors recruited | 2–3 in person, per evening |
SPARK Loop Metrics Dashboard — 7 Daily Metrics
| Stage | Metric | Target | Red Flag | Action |
|---|---|---|---|---|
| Installs | Daily installs | 30+/day | <15/day | Boost paid social + connector outreach |
| Gender | Female % | ≥50% | <45% | Pause male onboarding, activate female channels |
| Winks | Winks per user/week | 5+ | <2 | Push notification + profile curation |
| Sparks | Sparks per user/week | 2+ | <0.5 | Reduce Spark cost or run manual match |
| Chat start rate | Sparks → chat | ≥70% | <50% | Improve match quality, add ice-breakers |
| Meeting rate | Chats → meeting | ≥20% | <10% | Add event invitations, reduce friction |
| Referral | % installs from referral | ≥30% | <15% | Activate WOM mechanics, NPS loop |
Weekly Execution Dashboard — 9 Metrics (Review Every Monday)
MOST IMPORTANT METRIC → Real-World Meetings Per Week. A match that never meets is worthless. This number tells you if the product is actually working.
| Metric | Target | Week 1 Goal | Week 4 Goal | Month 3 Goal |
|---|---|---|---|---|
| New Installs | 50+/wk | 30 | 80 | 300 |
| Female Ratio | ≥50% | 55% | 52% | 50% |
| Active Chats | 40%+ of users | 25% | 40% | 45% |
| Sparks Sent | 3+/user/wk | 2 | 4 | 5 |
| Matches Created | 60%+ of Sparks | 45% | 60% | 65% |
| Meetings Booked | 30%+ of matches | 15% | 30% | 35% |
| Meetings Completed | 70%+ of booked | 60% | 70% | 75% |
| Event Attendance | 30+ per event | 20 | 40 | 60 |
| Referral Installs | ≥25% of installs | 10% | 25% | 35% |
MONDAY RULE: If Real-World Meetings Per Week is not growing week-on-week by Week 4, activate the Liquidity Control Protocol immediately. Do not wait for Month 3.
Real-World Meetings Per Week Milestones
| Milestone | Target |
|---|---|
| Week 1 | 10 meetings/week (manually seeded) |
| Week 4 | 50 meetings/week (organic + events) |
| Month 3 | 200 meetings/week (self-sustaining) |
Monthly Review Template
Complete at the end of each month. Review actual vs. target for all metrics, document what worked and what failed, and commit to 3 specific changes for next month.
| Metric | Target | Actual | Status |
|---|---|---|---|
| New Installs | See War Plan | — | — |
| WAU (Weekly Active Users) | See War Plan | — | — |
| Female Ratio | 50–60% | — | — |
| Matches per User | 2–5 | — | — |
| Sparks Sent per User | 3–6/week | — | — |
| Chat Start Rate | 60–70% | — | — |
| Match → Meeting Rate | 15–25% | — | — |
| Meetings per Week | See War Plan | — | — |
| Referral Installs % | 20–30% | — | — |
| Event Attendance Rate | 85–95% | — | — |
| Event No-Show Rate | < 10% | — | — |
| NPS Score | ≥ 60 | — | — |