Product vision

Decision Build a Gen Z-first wedding-venue discovery platform that replaces hidden pricing and PDF brochures with transparent inventory, aesthetic matching, and self-serve tours. Problem statement The wedding venue booking experience in 2025 is fundamentally broken for Gen Z brides. Research across 13 AI-moderated bride interviews, multi-stage surveys, and behavioral studies revealed a fragmented digital journey: - Gen Z brides plan smaller weddings under $30,000 and operate on mixed funding models. - They are digital-first decision-makers who demand transparency, aesthetic inspiration, and frictionless workflows. - 92% eliminate venues with poor digital interfaces. - 85% demand upfront, transparent pricing the industry refuses to provide. - Venue owners lack the digital capabilities to engage this generation effectively. Opportunity & rationale (TAM / SAM / SOM) TAM: $1.1B — 300,000 US wedding vendors × $3,726 average annual spend on marketing and booking platforms. SAM: $17.5M — ~135,000 digitally-native couples × 5 venue tours each × $26/tour. SOM: $2.5M Y1 → $25M Y3 — addressable via a sales-led motion targeting 1,400 venue partners. 83% of Gen Z couples actively penalize venues for outdated websites and a lack of transparency. The market opening is not a preference shift — it is a generational expectation. Solution overview A two-sided marketplace built around three primitives: 1. Aesthetic discovery — Pinterest-board import → AI-curated venue match. 2. Transparent inventory — real-time availability, all-in pricing, filter by budget / capacity. 3. Self-serve tour booking — a Gen Z bride's journey: discover → tour → contract without phone tag. Customer use case A Gen Z bride discovers the marketplace through a friend's TikTok, uploads her Pinterest board, and instantly sees a curated list of "charming outdoor" venues matching her capacity, budget, and date range. She books three tours in 20 minutes — no cold-emailing, no PDF brochures, no callbacks. Competitive landscape - Incumbent directory marketplaces — pay-to-play SEO, no real inventory data. - Adjacent wedding-planning platforms — weak venue inventory in tier-2 metros. - Social platforms — discovery without booking; high drop-off at the DM step. Unique differentiators: real inventory + transparent pricing + aesthetic-first match. None of the incumbents combine all three. Strategic edge — why now, why us - Gen Z is the dominant wedding-spend cohort by 2026. - Vibe-coded prototype already validates the aesthetic-match flow. - Founder ran 50+ hours of bride interviews; product is grounded in observed pain, not assumed. Business case Y1 target: $2.5M ARR via 2 AEs each carrying $1.25M quota (~700 venue partners per AE). Cost per qualified tour request: $26. North-star: tour-to-contract conversion rate, tracked obsessively by venue and aggregate. Measurement plan (KPIs) - Tour Completion Rate. - Tour-to-Contract Conversion Rate (per venue + aggregate) — north star. - Venue mobile-app adoption. - Cost per qualified tour request (target $26). Implementation plan Q1–Q2: MVP development + launch (2-week sprints, 100-venue pilot cohort). Q3: Onboarding funnel optimization + venue analytics; A/B test premium tiers. Q4: Hit target, prep for scale; revenue model expansion. Governance & operating rhythm Founder + 2 AEs + 4-person engineering team. Weekly exec review on tour-to-contract conversion and pilot venue NPS. Quarterly board review on ARR pacing vs. $2.5M target. Next steps 1. Secure pilot venue partnerships (100 venues). 2. Finalize go-to-market for AE hires. 3. Lock funding round against this vision. Why this matters This is more than a vision document. It is a strategic blueprint that merges product, business case, and metrics into a single artifact a board, an exec team, and an engineering org can all execute against.

Decision Build an AI platform that removes politics from promotions by making invisible work visible. Using daily behavioral signals from workplace tools, the platform generates a real-time contribution-intelligence score that provides objective proof of contribution. Vision & problem Most companies are not meritocracies. They are political theaters with good branding. Promotions often have less to do with performance than with perception. The executive who lunches with the right people gets tagged for "strategic vision." The louder manager is called a "natural leader." Meanwhile, the engineer who shipped the feature that drove 20% revenue growth is still waiting for their "turn." The data confirms it: - Only 2% of CHROs strongly agree their performance-management systems inspire employees to improve (Gallup, 2024). - Only 22% of employees believe reviews are fair and transparent. These are systemic failures, not isolated incompetence. Current systems cannot measure what drives execution velocity — ownership, follow-through, collaboration, alignment — so decisions default to politics. The inevitability analogy Before modern team-messaging tools, managers controlled power through email — gatekeeping inclusion and context. Messaging made transparency the default. Once experienced, defending the old way became impossible — not because executives wanted fairness, but because the efficiency gains were undeniable. This platform stands at the same inflection point. What the contribution-intelligence score reveals - When the "high-potential" manager has a 23% collaboration score. - When the quiet contributor sits in the 97th percentile for ownership. - Which teams resolve dependencies quickly vs. which succeed only on political cover. Trust imperative — proof over promises Modern enterprises are rightfully skeptical: burned by black-box AI, exhausted by surveillance tools, pressured for authentic transparency. The platform flips the traditional sales sequence — deliver behavioral proof during evaluation, turning skeptical buyers into champions before full rollout. During a pilot: - Instead of promising "better alignment," show a team resolving dependencies 3× faster than baseline. - Instead of promising "higher ownership," reveal contributors whose follow-through sits in the 97th percentile within their own org. Competitive landscape Incumbent HR-tech suites remain trapped in cycles of subjective, lagging indicators. The platform measures behavior continuously and passively. Trust comes from recognition of the truth in the data, not from belief. Strategic differentiators - Real-time contribution-intelligence score — daily behavioral signal, not quarterly survey theater. - Pilot-as-proof — evidence inside 30 days, not after a year of rollout. - Manager + employee + executive views — same data, three lenses. Antagonists (named, not hidden) - HR directors who built careers on intuition. - Founders who fear measurement will alter culture. - Politically successful performers who have the most to lose when perception ≠ promotion. Their resistance is not sustainable. Companies that adopt this platform will execute faster, retain talent longer, and outcompete so visibly that resistance evaporates. Business case Goal: $100M ARR in 36 months. Motion: sales-led, mid-market and enterprise. Wedge: radical transparency in the evaluation phase. Primary KPI set - Pilot-to-paid conversion. - Time-to-evidence (target: < 30 days). - Net dollar retention (target: > 130%). - Contribution-intelligence adoption per active employee. Strategic imperative This is not incremental change. It is structural inevitability. The category will exist; the question is who defines it. The vision is to define it before incumbents pivot.