Waterplan

Waterplan targeted large multinational corporations with significant water dependencies and regulatory exposure—companies like Coca-Cola, Diageo, Colgate, and AB InBev. These industrial giants faced mounting pressure from investors, regulators, and stakeholders to quantify and manage climate-related water risks across global operations. The founding assumption proved sound: enterprises with complex supply chains and manufacturing footprints in water-stressed regions would pay for continuous risk visibility and mitigation guidance. Early validation came through customer acquisition itself. Landing marquee brands in beverage and consumer goods sectors—industries inherently vulnerable to water scarcity—demonstrated that Waterplan had identified the right pain point. These customers' willingness to adopt the platform suggested the targeting was accurate: large organizations with sufficient budgets, multiple facilities to monitor, and genuine exposure to water risk. The combination of operational data integration with satellite imagery addressed a specific need these enterprises couldn't solve internally, validating both the audience selection and the core value proposition.

Waterplan launched with a deliberately narrow MVP targeting multinational beverage and consumer goods companies facing acute water stress. ​​‌‌‌‌‌‌‌​‌‌​​‌​​​​​​‌‌​‌‌‌​​​‌‌Their first product combined satellite imagery with basic operational water consumption data to generate risk assessments for specific facilities—skipping the broader climate reporting features they envisioned. The team shipped this core capability within six months, deliberately excluding predictive modeling, mitigation recommendations, and multi-site portfolio analysis that would have delayed launch by a year. This constraint forced early conversations with prospects like Coca-Cola and Diageo, who validated the fundamental insight: companies needed immediate visibility into facility-level water risk before considering solutions. These conversations became their strongest early signal—customers began requesting the product before it was fully built, indicating genuine urgency rather than theoretical interest. The stripped-down approach meant faster iteration cycles and clearer product-market fit signals. However, the narrow scope initially limited their addressable market and required rapid feature expansion once enterprise customers demanded more sophisticated capabilities. This execution philosophy—ruthless prioritization over comprehensive features—proved essential for gaining traction in a crowded climate-tech landscape.