RevOps and Churn Prediction for SaaS Organisation

Problem Statement

Our client, a fast-growing SaaS company offering a suite of CRM tools, had seen a steady influx of leads, averaging 2,500 new leads per month, and maintained a customer base of over 10,000 users. However, despite this growth, they struggled to optimize their lead conversion rate, which hovered around 12%, far below the industry benchmark of 20%.

Additionally, their average Customer Lifetime Value (CLTV) remained at $1,200, with significant room for improvement given their pricing structure and market potential. A major challenge had been accurately predicting churn, with their models only achieving 60-65% accuracy, leading to reactive rather than proactive retention strategies.

Key Challenges

• Low Lead Conversion Rates lacked the ability to analyze historical lead data.
• Limited Upselling and CrossSelling struggled to identify the right opportunities.
• Churn Prediction was difficult to predict which customers were at risk of churning.

Solution Implemented

• Lead Conversion Optimisation
• Upselling and Cross-Selling Enhancement
• Churn Prediction and Prevention