Business Idea Analysis · 5 Expert AI Roles
Show HN: I mapped every US golf course
38 out of 100 Risky
✕ STOP

Fundamental market or economic problem — can't be fixed by changing execution. Don't invest further.

5 expert AI roles Critic Market Strategist Trend Hunter Architect Deep Research
Panel lineup: Claude Opus · GPT-5 · Grok · Gemini · Perplexity
This is a well-built free golf course directory that solves a real but minor annoyance — finding accurate course info. The core problem is that it has no revenue model, competes with well-funded incumbents (GolfNow, Google, GolfPass), and the 'browse courses' job is a rare, low-frequency task that doesn't build habits or willingness-to-pay. The genuinely valuable asset is the golfer-verified data, not the consumer directory.
🧠 AI Panel Verdict ?
⚔️ Devil's Advocate
☠ KILL
5 risks identified
🌊 Trend Hunter
🏗️ Solution Arch
Feasibility 0/10
🔍 Deep Research
Complete
Perplexity Sonar
🎯 Synthesizer
✕ STOP
Score: 38/100
Quick Filter ? 1/5
MVP buildable in ≤2 weeks with AI coding tools?
Already built; OSM base + scraped course data + map UI is clonable in under a week.
People ALREADY pay for a solution to this problem?
Golfers pay for booking (GolfNow) and GPS/stats (SwingU), not for browsing a directory — the free directory itself has no paying users.
Gross margin ≥ 60%?
No revenue at all today; free with no ads and rising data-maintenance and hosting costs means negative margin.
Scales without linear cost growth?
Manual verification of ~16,000 US courses plus global expansion is an infinite maintenance treadmill for a solo founder.
Clear competitive advantage vs free alternatives?
Google Maps and GolfPass already index every course for free; the only real edge is verified data quality, which is currently a near-zero network effect.
📋 Score Breakdown ?
Сила боли
3
Платежеспособность ICP
2
Доступность канала
5
Юнит-экономика
1
Конкурентный ров
2
Скорость сборки
9
AI-ускорение
7
Скорость до выручки
2
Регуляторный риск
6
Тайминг тренда
6
⚔️ Devil's Advocate ?
No revenue model, free forever
High
'Free, no ads, no login, no bs' is a feature for users and a death sentence for a business. You're paying hosting and data-maintenance costs with zero monetization path and no plan to build one.
Probability:
90%
💡 Define a specific monetization hypothesis (tee-time booking affiliate, course lead-gen, premium data API) and test willingness-to-pay before building further.
Directory market already crushed
High
GolfNow (NBC Sports), GolfPass, TheGrint, Golf Digest, and Google Maps itself already index every US course and integrate booking. You're competing on 'better browsing' — a nice-to-have nobody switches products for.
Probability:
85%
💡 Identify one specific data category (accurate scorecards/slope) where incumbents are provably worse and own that niche instead of 'every course.'
Data maintenance doesn't scale
High
Golf courses change layouts, close, and update scorecards constantly. Manually verifying and 'fixing' user flags for ~16,000 US courses plus the whole world is an infinite treadmill for a solo maintainer.
Probability:
80%
💡 Automate ingestion and staleness detection; do not promise 'verified' data you cannot sustainably maintain.
Google is the actual competitor
High
You literally built this because Google search was annoying. Google can improve golf course cards in one product cycle and instantly reclaim every user you have.
Probability:
60%
💡 Build a data asset (verified scorecards/ratings) valuable enough to license to others rather than compete on discovery.
No user acquisition beyond HN spike
Medium
A Show HN gives a one-day traffic bump of tech people, not golfers. There is no organic loop, no SEO moat vs incumbents, and no reason for golfers to return.
Probability:
75%
💡 Test one acquisition channel (golf subreddits/local golf FB groups) and measure retention, not just visits.
Hidden Assumptions
Golfers want a better directory badly enough to change habits
Most golfers use Google Maps + the course's own website + GolfNow for booking. 'Browsing courses' is not a recurring painful job — you book the course near you or where you travel, then stop looking.
'Most complete directory in the world' is achievable in a few months
This is a textbook planning fallacy. Global course data, multi-language, verified scorecards, and constant maintenance is a multi-year, multi-person data operation — GolfNow spent a decade and NBC money on it.
Free with no ads/login can sustain a business
Zero monetization plus rising hosting and verification costs means the project dies the moment the founder's enthusiasm or personal budget runs out. Free directories without a revenue engine become abandonware.
⚠️ Cognitive Bias Check
Оптимизм-предвзятость (Optimism Bias)
Claiming the 'most complete golf directory in the world' is 'attainable in the next few months' while being solo and mostly-US today.
✅ Reality check: Estimate actual hours to verify one course, multiply by 16,000 US courses, then by the global count — the timeline is off by years, not months.
Ошибка планирования (Planning Fallacy)
Roadmap to expand to North America, EU, and 'rest of the world ASAP' as if data acquisition is a linear quick task.
✅ Reality check: Track how many courses you can fully verify per week for one month, then extrapolate honestly.
Предвзятость подтверждения (Confirmation Bias)
'I got tired of Googling' — building a solution to your own annoyance and assuming others share it strongly enough to switch.
✅ Reality check: Ask 20 golfers what tool they actually use to find courses and whether they'd change; measure their real behavior, not polite agreement.
🤖 AI Commoditization Risk
Days to Clone
5
Big Tech Risk
High
The core (OSM data + scraped course sites + a map UI) is clonable in under a week; the only conceivable moat is user-corrected verified data, and that network effect is currently near zero. Google/GolfNow can crush this trivially.
Worst Case
In 18 months the site still exists as a hobby project with a few thousand monthly visitors, mostly the original HN crowd. Data has gone stale because manual verification never scaled, user flags pile up unaddressed, and hosting costs quietly drain the founder's wallet until it's silently shut down. No revenue was ever made and no golfer noticed it was gone.
Minimum Experiment
Before adding a single new feature, spend $0 posting the site in 3–5 active golf communities (r/golf, local golf FB groups) and measure 7-day return visits and flag submissions. If golfers don't come back or contribute, the 'painkiller' thesis is dead — no code needed to learn this.
💡 Alternative Cost
1
License your verified scorecard/slope data to existing golf apps and booking platforms
If your user-corrected data truly beats commercial sources, selling it as a B2B data feed monetizes the one real asset instead of giving it away.
2
Build a narrow tool golfers actually pay for — e.g. accurate handicap/slope tracker for a specific underserved region
Solves a recurring, emotional golfer job (score/handicap) with real willingness-to-pay, rather than a one-off discovery task.
3
Contribute the data back to OpenStreetMap and monetize consulting/integrations on top
Turns unpaid maintenance labor into either community leverage or paid integration work, avoiding a solo unmaintainable directory.
📊 Market & Competition ?
⚠️ This expert was temporarily unavailable — the verdict is based on the remaining experts
🔍 Deep Research ?
Competitive Intelligence

# Competitive Landscape, Pricing Benchmarks, and Market Gaps For A Global Golf Course Directory The golfcoursebrowser.com concept positions itself as a neutral, ad‑free, user‑maintained directory built on OpenStreetMap data, aiming to map and enrich every golf course in the world with verified, up‑to‑date factual information such as scorecards, slope/rating, and public/private status, and to do so without requiring login, payment, or engagement with a booking marketplace.[3] This vision sits at the intersection of several adjacent markets: consumer tee‑time marketplaces, golf membership programs, golf GPS and stat‑tracking apps, and B2B golf data APIs, each of which already monetizes golf course data in different ways and at different price points.[1][4][5][7][8][9][10][11][14][15][16

Market & Risks

# Market Size and Risk Analysis for a Global Golf Course Directory Platform The proposed business, exemplified by golfcoursebrowser.com, aims to become the most complete, current, and golfer‑verified directory of golf courses worldwide, starting from a comprehensive mapping of every U.S. course using OpenStreetMap (OSM) as the backbone and augmenting that with scorecards, USGA ratings, and public/private status.[25][40] This report evaluates the market size and key risks for such a platform across four dimensions: total addressable, serviceable, and obtainable markets; historical failures and pivots among comparable golf technology businesses; regulatory and legal constraints, particularly around data licensing and geolocation privacy; and recent funding activity that signals investor sentiment toward the broader golf tech ecosystem.[3][5][12] While the core directory is currently free, ad‑free, and login‑free, and thus does not yet monetize users, the underlying value proposition—high‑quality, structured golf‑course data maintained by engaged golfers—intersects with sizable and growing markets for tee time booking platforms, golf course management software, golf GPS and data APIs, and golf tourism.[3][5][12][14] At the same time, the space is characterized by consolidation, sunsetted products, and changing regulations around location data and database licensing, implying that both strategic positioning and legal compliance will be critical to sustaining any commercial model built on this directory.[23][41][42] The analysis concludes that the market opportunity is meaningful but niche, best understood as a data and infrastructure play within an expanding digital golf ecosystem, and that the primary risks arise less from a lack of demand than from competitive dynamics, regulatory developments, and the operational burden of maintaining a globally accurate dataset at consumer‑grade quality.[5][25][42] ## 1. Business Concept and Industry Context ### 1.1 The Golfcoursebrowser Concept The business idea under examination originated from a developer who became frustrated with the difficulty of finding basic golf course information via general search engines.[25] In a discussion on Hacker News, the creator explained that Google’s filters for golf course results were “terrible,” motivating the construction of “a better way to browse courses” built atop OpenStreetMap data.[25][40] The live site, golfcoursebrowser.com, is described as a free directory covering every U.S. golf course, with expansion plans to the rest of North America, the European Union, and ultimately the world, all offered with “no ads, no login, no bs.”[25] The data stack is explicitly outlined: OSM provides the base spatial layer, which is then cross‑checked against course websites and enriched with scorecards, USGA rating/slope, and public/private status, while user corrections from local golfers are incorporated to refine accuracy and currency.[25][40] The creator emphasizes a commitment to factual data and claims that community corrections have “beaten every commercial data source” checked against, suggesting an emergent crowdsourced quality assurance loop akin to Wikipedia or OSM itself but focused on golf.[25] In essence, the product is not a tee time booking engine, GPS rangefinder, or social network; instead, it is a structured, queryable database of golf facilities, their attributes, and their layout metadata, surfaced through a consumer‑friendly discovery interface.[25] This positioning differentiates it from dominant tee time marketplaces like GolfNow, which emphasize booking and promotional offers, and from golf GPS apps such as Golf Pad, Golf Frontier, and Golfshot, which focus on in‑round navigation and scoring.[18][22][49] The value lies in accurate, up‑to‑date course discovery and canonical reference information, which in turn can support other applications via APIs, power analytics, or feed simulators and training systems that need course data.[20] The use of OSM’s `leisure=golf_course` tagging scheme, including tags such as `golf=hole`, `golf=fairway`, `golf=green`, and `golf=bunker`, indicates alignment with an established open geodata standard for representing golf courses, making interoperability with external tools and editors like FairwayMapper straightforward.[7][40] By building in public on an open backbone, the project positions itself both as a consumer utility and as a foundational data service for the broader golf tech ecosystem. ### 1.2 Position Within the Digital Golf Ecosystem The broader digital golf ecosystem already includes several categories of products that depend on structured golf course data, each of which forms part of the addressable market for the directory’s eventual monetization. Golf course management software platforms, such as GolfNow’s business offerings and foreUP’s tee time management tools, enable operators to manage tee sheets, point‑of‑sale, marketing, and agronomy while often needing accurate facility and course layout information.[5][18] Golf GPS and scoring applications, including Golf Pad, Golf Frontier, Golfshot, and SwingU (formerly Swing By Swing), rely on precise hole maps and landmarks to provide distance readings, automatic shot tracking, and analytical insights for players.[22][49] Tee time booking platforms like GolfNow, Teeoff.com (now consolidated under the same corporate umbrella), Loop Golf, Noteefy, GolfZing, and Golf Pipeline aggregate course inventory and present it to consumers, needing standardized facility data to synchronize listings, filter by location, and integrate with course websites.[13][21][39][43] Additionally, golf data API providers such as Golf Intelligence, golfcourseapi.com, Zylalabs’ Golf Data API, and broader sports API integrators like SportsFirst offer structured course datasets to developers, simulators, and analytics firms, indicating a nascent but real B2B market for golf‑course information.[20] Golf tourism platforms and travel advisors, such as GolfPass’s course reviews and ratings, depend on accurate directories to guide golfers to venues worldwide, and the golf tourism market itself is sizeable and growing.[14][15] Even disc golf, although a different sport, demonstrates a parallel trend: UDisc reports 17,287 disc golf courses across 99 countries, with 89% free to play, implying a globally distributed, map‑driven leisure infrastructure where course data is central to participation. Within this landscape, a high‑quality, open or semi‑open directory of golf courses becomes a shared resource that can reduce redundancy, improve data quality, and power a range of applications that currently maintain their own proprietary course lists. ### 1.3 Data as Infrastructure and Potential Monetization Paths Although golfcoursebrowser is currently non‑commercial, its long‑term economic potential logically stems from the value of its data rather than from direct consumer fees for browsing. Golf Intelligence, for example, markets a “Golf Course Database” with details including location, 3D course layouts, GPS data, and professional reviews, and positions this database as part of a larger “Golf Intelligence Universe” of analytics and APIs for simulators, apps, and AI tools.[20] Golfcourseapi.com similarly advertises itself as “the one and only completely free golf course API on the internet,” offering access to data for almost 30,000 courses worldwide with tiered pricing plans for higher request volumes, implying that developers are willing to pay recurring fees for reliable course data in API form. Zylalabs’ Golf Data API is pitched as a “powerful tool” granting developers programmatic access to course locations, details, ratings, and more, again reinforcing the notion that course data is a monetizable asset when packaged and delivered via modern APIs. In this sense, the directory resembles infrastructure more than a consumer app: it is a canonical registry of golf courses, their attributes, and spatial layouts, which can be monetized indirectly through licensing, API subscriptions, partnerships with tee time platforms, or integration with hardware and simulator ecosystems that need course mapping.[20] The HN creator’s insistence on publishing only “facts, which are not copyrightable in the US,” and reliance on OSM’s open license suggests an attempt to sidestep some intellectual property concerns while building a clean foundation to support future commercial use.[23][25] However, as will be discussed in the regulatory section, open data licenses such as ODbL impose specific obligations around attribution and share‑alike, and geolocation and profile data associated with users may trigger GDPR and CCPA requirements even if the course locations themselves are not personal data.[23][41] Understanding these constraints is essential to framing the market correctly and to assessing how far a free, open directory can be pushed toward commercial models without undermining its core community-driven ethos. ## 2. Market Size: TAM, SAM, SOM, and Growth Dynamics ### 2.1 Defining the Relevant Market To size the market for a global golf course directory, it is necessary to distinguish between the broader golf economy and the narrower set of segments that directly depend on structured course data. The total golf economy includes equipment, apparel, tourism, course operations, instruction, and media, collectively amounting to tens of billions of dollars annually across regions.[3][14] However, a directory such as golfcoursebrowser is not selling clubs or greens fees; it is offering information and infrastructure: course locations, attributes, layouts, and ratings for use by

Demand Signals

# Organic Demand Signals For A Global Golf Course Directory: Evidence From 2024–2025 The business idea under examination is a free, map-based directory of every golf course, starting with the United States and aiming to expand globally, built on OpenStreetMap data and enriched with structured course information such as scorecards, USGA rating and slope, public/private status, and verified user corrections.[7][2] The core pain point it addresses is the difficulty of discovering accurate, comprehensive, and user-friendly information about golf courses through general-purpose search engines, particularly Google, whose filters and fragmented results make it hard for golfers to compare courses, find basic details, or verify data in a single place.[7][2] This report systematically examines organic demand signals for this idea across six channels—Reddit, Hacker News, Product Hunt, X/Twitter, SEO data, and broader trends—focusing exclusively on real signals from 2024–2025 where dates can be verified. The evidence shows that while explicit Reddit threads asking for exactly such a directory are not readily identifiable in the provided sources, there are strong adjacent signals in hacker communities, product launch ecosystems, app marketplaces, and social media discussions about golf courses, tee times, and course information tools.[2][4][9][11][13] These signals collectively suggest that the market window for a structured, global golf course browser remains open and may even be expanding, driven by increasing digitalization of golf, growth in tee-time alert and booking tools, and rising interest in data-rich course rankings and discovery content.[5][11][13] However, important limitations remain: precise Reddit thread-level demand,

⚙️ Technical Feasibility ?
⚠️ This expert was temporarily unavailable — the verdict is based on the remaining experts
🛠️ MVP Build Plan ?
Days to MVP
17
solo dev
Infra Cost
$40
/month
Invest to Breakeven
$1500
P50 realistic
Tech Stack
Next.js PostgreSQL + PostGIS MapLibre GL Overpass API (OSM) Vercel Cloudflare
MVP Features
MUST
Directory de búsqueda y navegación de campos
Es el núcleo de validación: la queja original es que Google filtra mal los campos de golf. Sin una búsqueda mejor que Google (por estado, ciudad, público/privado, cercanía) no hay razón para volver. Esto es lo que se debe validar antes que nada.
⏱ ~30h
MUST
Ficha de campo con datos enriquecidos
El valor real está en agregar scorecard, USGA rating/slope y estado público/privado sobre la base de OSM. Es lo que diferencia frente a resultados genéricos. Sin ficha rica, es solo un mapa más.
⏱ ~24h
MUST
Ingesta y normalización de datos OSM
OSM es el backbone. Extraer, limpiar y geolocalizar todos los campos de EE.UU. es la barrera de entrada que ningún competidor rápido puede copiar en un día. Determina la completitud, el principal argumento de venta.
⏱ ~28h
MUST
Sistema de reporte/corrección en la ficha
El foso defensivo es 'verificado por golfistas reales'. El botón de flag genera el flujo de correcciones que ya supera a fuentes comerciales. Crítico para validar el ciclo de mejora continua y la comunidad.
⏱ ~12h
MUST
Mapa interactivo con clustering
Navegar visualmente miles de campos requiere un mapa con agrupación por zoom, si no se rompe la UX. Es la forma natural de explorar 'campos cerca de mí', el caso de uso más frecuente.
⏱ ~16h
MUST
SEO técnico por página de campo
Sin login ni ads, el único canal de captación viable es orgánico. Cada campo debe ser una landing indexable (slug, meta, schema.org LocalBusiness/GolfCourse) para captar las búsquedas '[nombre campo] scorecard' que Google resuelve mal hoy.
⏱ ~14h
SHOULD
Panel admin de revisión de flags
El fundador 'lee y arregla' las correcciones. Sin una cola de revisión mínima, el proceso no escala más allá de decenas de reportes y se vuelve inmanejable. Habilita el bucle de calidad.
⏱ ~10h
🗺️ First Customer Journey ?
1
Descubrimiento
👤 Busca en Google '[nombre del campo] scorecard' o ve el Show HN / post en r/golf
👁 Resultado orgánico o titular 'Mapé todos los campos de golf de EE.UU., gratis, sin ads' ⚙️ SEO técnico por campo + lanzamiento en HN/Reddit
2
Aterrizaje en la ficha del campo ⚠️ DROP RISK
👤 Llega directo a la página del campo que buscaba
👁 Nombre, mapa, público/privado, scorecard, USGA rating/slope, contacto ⚙️ Ficha rica y completa; si faltan datos aquí, se pierde la confianza
3
Exploración
👤 Navega el mapa, busca otros campos cercanos
👁 Mapa con clustering, filtros público/privado, resultados por zona ⚙️ Mapa fluido + buena cobertura de datos
4
Contribución / conversión
👤 Reporta un error de su campo local o hace clic en 'reservar tee-time'
👁 Botón de flag simple + enlace de reserva (afiliado) ⚙️ Flujo de flag sin fricción + link de afiliado que monetiza
5
Retención
👤 Vuelve la próxima vez que planea jugar en un campo nuevo
👁 Directorio ya conocido y fiable, sin login ni ads ⚙️ Mantener datos actuales; sin login, la retención depende 100% de que vuelvan por SEO/memoria
💡 Dropout mitigation: El mayor riesgo es aterrizar en una ficha con datos incompletos: el usuario que buscó el scorecard y no lo encuentra se va a Google y no vuelve. Mitigación: priorizar la completitud de datos en los 500-1000 campos más buscados (los que reciben tráfico SEO real) antes que la cobertura total. Cuando falte un dato, mostrar explícitamente 'Falta el scorecard — ¿lo conoces? Ayúdanos a completarlo' convirtiendo el hueco en una llamada a la contribución en lugar de un callejón sin salida. Medir por analítica qué fichas reciben tráfico y cerrar esas primero.
💰 Financial Sketch (Realistic) ?
Investment Needed
$3000
until breakeven
Breakeven
М13
month of payback
MRR М12
$600
at month 12
LTV/CAC
1.5×
target ≥ 3
Unit Economics — Margin per Sale ?
Price per unit
$49.0
Cost per unit (COGS)
$8.0
Platform fee
0%
Margin per unit
$41.0
Min. price to break even: $8.0
Reflects a hypothetical B2B data-API subscription at $49/mo; margin is healthy per unit but irrelevant while the product is free with zero paying customers — the entire economics depend on a pivot that hasn't been tested.
Month MRR
M1 $0
M3 $0
M6 $150
M12 $600
🟥 burning cash · 🟩 cash positive · ✅ BREAKEVEN = investment fully recovered
📈 Three Scenarios (P20 / P50 / P80) ?
P20 — Cauteloso
MRR М12
$600
CAC
$90
Churn/mo
18%
To Breakeven
$3500
Producto gratis sin login: monetizar es el problema real. Sin modelo claro (afiliados de tee-times, patrocinio de campos o donaciones), el MRR llega tarde. SEO tarda 6+ meses en madurar. Sin retorno del hype inicial de HN.
P50 — Realista
MRR М12
$600
CAC
$30
Churn/mo
8%
To Breakeven
$1500
Monetización vía afiliados de reserva de tee-times (GolfNow, tee-off) + fichas premium de campos/pro shops. Tráfico SEO creciente sobre las páginas de campo. CAC bajo porque el canal es orgánico; el coste es contenido y mantenimiento de datos. Sin coste variable por usuario (todo estático/cache).
P80 — Optimista
MRR М12
$12000
CAC
$6
Churn/mo
4%
To Breakeven
$500
Show HN pega fuerte + comunidades r/golf. SEO domina long-tail '[campo] scorecard/slope'. Monetización mixta: afiliados tee-time (comisión ~15-25% del green fee), listados patrocinados de campos y venta de acceso a la base de datos vía API a apps de golf. Activo propio: tráfico SEO orgánico, coste de mantenimiento ~$300/mes en contenido y curación.
Month P20 P50 realistic P80
M1 $0 $0 $100
M3 $0 $200 $800
M6 $150 $150 $3000
M12 $600 $600 $12000
🧪 Hypotheses to Validate ?
H1
If golfers are posted the directory in active golf communities, then a meaningful share will return within 7 days and submit corrections — proving the verified-data flywheel.
🔬 Post in r/golf and 3-5 local golf FB groups; track 7-day return visits and flag submissions with analytics. ⏱ 10 days
H2
If the verified course data is offered as a B2B API, then golf app/simulator developers will pay for it because their in-house data is worse.
🔬 Email 15 golf app and simulator companies offering API access; measure how many take a paid trial call. ⏱ 21 days
H3
If the data quality genuinely beats commercial sources, then a blind comparison on 50 courses will show measurably fewer errors.
🔬 Sample 50 courses, compare scorecard/slope accuracy against GolfNow/GolfPass, document error rates. ⏱ 14 days
🛑 Kill Criteria ?
Fewer than 10% of new visitors return within 7 days and under 20 correction flags submitted after seeding 5 golf communities — the verified-data flywheel is dead.
Zero of 15 contacted golf app/simulator/analytics companies agree to a paid data-API trial within 3 weeks — no B2B willingness-to-pay.
Monthly hosting + tooling costs exceed founder's willingness to fund with no revenue signal for 3 consecutive months.
⚖️ Risks & Opportunities ?
Top Risks
No revenue model — 'free, no ads, no login' means costs grow while income stays at zero until enthusiasm or budget runs out.
Incumbents (Google Maps, GolfNow, GolfPass) already index every course for free and integrate booking; 'better browsing' isn't a switching reason.
Data maintenance doesn't scale — verifying and updating ~16,000 US courses plus global expansion is an infinite treadmill for a solo maintainer.
Top Opportunities
The golfer-verified data asset (accurate scorecards, USGA slope/rating) could be licensed as a B2B API — golfcourseapi.com and Zylalabs prove developers pay for this.
Pivot to a narrow paid tool (handicap/slope tracker for an underserved region) that solves a recurring, emotional golfer job with real willingness-to-pay.
Golf digitalization tailwind — simulators, GPS apps, and analytics firms all need clean course data and currently maintain their own lists.
Next 48 Hours ?
1
Post the directory in r/golf and 3-5 local golf Facebook groups with a direct ask: 'check your home course and flag anything wrong' — measure return visits and flags.
2
Run a blind data-quality comparison on 20 courses vs GolfNow and GolfPass to concretely quantify the 'we beat commercial sources' claim.
3
Draft and send a one-paragraph B2B pitch email to 10 golf app / simulator / GPS companies offering API access to the verified dataset.
📅 30-Day Action Plan ?
W1
Week 1
Test whether the consumer directory has any real pull or retention before investing further.
Seed the site in 5 active golf communities and instrument analytics for 7-day return rate and flag-submission count.
Run the blind data-quality audit on 20-50 courses vs GolfNow/GolfPass and document the error-rate delta.
Interview 15 golfers on what tool they actually use to find courses and whether they'd switch — measure behavior, not politeness.
W2
Week 2
Probe B2B willingness-to-pay for the data asset — the only viable revenue path.
Email 15 golf app/simulator/analytics companies offering a paid API trial; book calls with anyone interested.
Build a simple API spec and sample dataset (100 courses) to show prospects concrete data quality.
Compare pricing against golfcourseapi.com and Zylalabs to anchor a realistic subscription price.
W3
Week 3
Follow the signal — double down on B2B if it responds, otherwise conclude the thesis is dead.
If ≥2 companies want a trial, ship a minimal authenticated API endpoint with the verified dataset.
If B2B is silent and consumer retention is low, stop new feature work and document learnings before spending more.
W4
Week 4
Decide: commit to the data-infrastructure pivot or shut down gracefully.
Tally return visits, flags, and B2B trial commitments against kill criteria to make a go/no-go call.
If pivoting, rewrite positioning around 'the most accurate golf course data API' and line up the first paying design partner; if not, contribute the data back to OSM and wind down hosting costs.