Marketplace connecting renters with storage, parking, and RV spaces nationwide
Neighbor operates a two-sided marketplace for storage and parking across the United States, matching renters with hosts in garages, driveways, self-storage facilities, and RV lots. The tech stack skews marketing-heavy (HubSpot, ZoomInfo, Google/Meta/LinkedIn/TikTok Ads, Google Maps) with emerging data infrastructure (ETL/ELT pipelines, semantic layers, predictive modeling), suggesting a shift from acquisition-driven growth toward operational analytics and unit economics optimization. Active hiring in marketing and sales outpaces engineering (1 role), indicating a sales-led company scaling customer acquisition faster than product velocity.
Neighbor is a two-sided marketplace for peer-to-peer and commercial storage and parking. On the renter side, the platform aggregates listings from individual hosts (garage, driveway, basement) and commercial operators (self-storage facilities, parking garages, RV lots), enabling search, comparison, and booking across a single catalog. On the host side, individuals and small businesses list underutilized space and earn recurring rental income with minimal management overhead. The company operates in every U.S. city and serves renters, individual hosts, and businesses seeking to monetize spare capacity. The marketplace model requires balancing supply growth (recruiting hosts), demand generation (acquiring renters), payment processing, and dispute resolution (eviction handling, inventory accuracy).
Neighbor uses HubSpot for CRM, ZoomInfo for lead intelligence, Google Workspace for productivity, and runs advertising across Google Ads, Meta Ads Manager, LinkedIn Ads, and TikTok Ads. Maps integration via Google Maps and Apple Maps supports location-based search and discovery.
Active projects include ETL/ELT pipelines, data modeling layers, semantic layers for self-service analytics, and predictive models for forecasting and automation. Pain points around data integrity, single source of truth, and cloud compute optimization indicate evolving data infrastructure maturity.
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