The project involved working with the business SMEs to understand the data and customer usage behavior, support, cases, and external business drivers.

Opportunity/Problem Statement

• Sales conversion ratio is less than 20%
• Pipeline quality is less than optimal
• High sales cost as a % of revenue and stagnant revenue over the past few years

Solution Highlights

• Mirketa built the Salesforce Einstein Prediction model for predicting customer churn for SaaS company.
• Analyze more than 35 variables from CRM and customer data to understand the DNA of winning deals.
• We created derived data to be used for modeling and created AI models with 90+ confidence score to predict the likelihood of a customer leaving beforehand.

The Results

Sales reps now deprioritize deals that have low probability. Sales processes are being enforced using next steps recommendation

Success Stories