Building a Data-Driven Investment Strategy Across M&A Units

A private equity–backed home services roll-up engaged me to help shift the organization from instinct-driven decision-making to a more structured, data-driven approach to growth. The company had scaled quickly through acquisitions, but lacked a consistent framework for understanding customer value, prioritizing investment, and aligning leadership around a clear path forward.

The immediate need was twofold: provide the board with a high-confidence view into the drivers of performance, and create a model that could be applied consistently across business units.

I started by analyzing historical customer data to better understand lifetime value and identify the attributes of higher-value customers. To deepen that view, we layered in external demographic data—such as household income, home age, and tenure—to identify patterns and define target segments with greater precision.

From there, we translated those insights into a practical growth strategy. Rather than broad, undifferentiated outreach, we developed a targeted engagement approach—prioritizing specific customer segments and aligning outreach efforts with clear revenue and profitability objectives. This included building a structured outreach plan with defined monthly targets and supporting channels such as direct mail and call strategies.

A key focus throughout was making the work actionable for both leadership and operators. We developed a bottoms-up model that connected customer segments to revenue impact, giving the board visibility into where growth would come from and what levers mattered most. At the same time, we established measurable weekly and monthly goals to track performance in real time and ensure accountability across teams.

The work identified three primary levers for growth: increasing new customer penetration, focusing on higher-value segments, and unlocking incremental revenue through more targeted outreach—all without increasing overall spend. Just as importantly, the framework was adopted by corporate finance and extended across the organization, creating a repeatable model for decision-making and ongoing performance management.