Building an Open Data Portal for Municipal Government

El Desafío

The company had a good product but was stuck. Customer acquisition costs climbed each quarter, organic growth had flatlined, and the sales team spent too much time on leads that went nowhere. They knew the product worked -- they just had no repeatable way to get it in front of the right people.

Nuestro Enfoque

Investigación, Análisis y Fundamentos Estratégicos

• Pulled user behavior data from every touchpoint and found where people were leaving and why
• Benchmarked against five competitors to see what was working in the market and what was not
• Set up a measurement framework tied to actual business outcomes, not vanity metrics

Diseño, Desarrollo e Implementación

• Built the core platform features, prioritizing the ones users asked for most
• Set up analytics so the team could see what was happening in real time instead of waiting for monthly reports
• Automated the repetitive workflows that were eating 15+ hours per week
• Connected the separate systems into one data pipeline so every team worked from the same numbers

Lanzamiento, Optimización y Escalabilidad

• Escaladas las campañas que funcionaban y cerradas las que no
• Expansión a dos segmentos de mercado adyacentes que los datos iniciales sugerían que convertirían bien
• Firmados acuerdos de partnership con tres empresas complementarias para llegar a nuevas audiencias
• Construidos programas de retención enfocados en los primeros 90 días, donde ocurría la mayor parte del churn

Lo Que Aprendimos

1. Los atajos en el código del primer año nos costaron tres meses de retrabajo en el segundo año. Dedicar una semana extra a la arquitectura al inicio habría ahorrado mucho más tiempo.
2. Starting in one market segment instead of three kept the budget focused and gave us real data to work with before expanding. The temptation to go broad early is strong, but the results argue against it.
3. Shipping a visible win in the first 60 days changed the internal conversation. Stakeholders who were skeptical about the project became its biggest advocates.
4. Reducing monthly churn by 2 percentage points had the same revenue impact as increasing new signups by 15%. Retention math is unforgiving.
5. Automating the repetitive work freed up time for the decisions that actually required judgment. The key was knowing which decisions to automate and which to keep manual.

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