Data Strategy
AI-Powered SaaS Startup
Scalable Market Intelligence Platform
~175%
MRR Growth Contribution
~60%
Data Incident Reduction
~50%
Ad-hoc Reporting Reduction
The Challenge
An AI-powered SaaS startup lacked the data infrastructure, analytics capability, and governance frameworks needed to scale from seed-stage to a data-driven growth engine. Product and usage analytics were non-existent, executive decision-making relied on ad-hoc queries, and data quality issues were eroding stakeholder confidence.
Our Solution
We owned end-to-end data strategy and operating model — including data platform architecture, analytics capabilities, governance frameworks, and executive decision support. An analytics platform and executive portal were launched to standardise commercial and product KPIs, while data governance and quality frameworks with automated monitoring were established.
How We Did It
Data Strategy & Operating Model
Defined end-to-end data strategy covering platform architecture, analytics capabilities, governance frameworks, and executive decision-support requirements. Aligned data initiatives with growth and pricing strategy.
Analytics Platform Build
Architected and launched a scalable analytics platform and executive portal that standardised commercial and product KPIs, reducing ad-hoc reporting by ~50% and providing C-suite visibility into key metrics.
Governance & Quality Frameworks
Established data governance and quality frameworks with automated monitoring and validation — reducing data incidents by ~60% and increasing stakeholder confidence in reporting accuracy.
Product Analytics & Growth
Operationalised product and usage analytics, building pipelines from API telemetry, platform data, and analytics layers to C-suite dashboards informing pricing and growth strategy. Contributed to ~175% MRR growth.
“The data strategy gave us the analytics foundation we needed to scale pricing, measure product-market fit, and grow MRR by 175%.”
CEO
AI-Powered SaaS Startup
Technologies Used