Problem Statement
A leading SaaS company, specializing in cloud-based solutions for enterprise clients, sought to optimize its marketing strategy.
The company was investing in various channels—digital advertising, Newspapers, physical banner ads, TV ads, and partner events—but faced challenges in forecasting the ROI of each channel and identifying whitespace opportunities for growth.
They were struggling to reduce High CAC, which was higher than industry standard.
A higher share of spend going to less productive channels was one of the key reasons for it.
They were spending almost 35% of their revenue on marketing with unpredictable MROI.
Solution Implemented
- Data collected from multiple sources, cleaned, and normalized.
- Regression models quantified marketing channels' impact on revenue and acquisition.
- Optimization algorithms maximized ROI and identified growth opportunities.
- Time series and scenario analysis enhanced forecasting and decision-making.
- Continuous model updates and multi-touch attribution improved accuracy and channel insights.
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