A leading financial firm in the US prioritizes delivering tailored solutions that cater to the diverse needs of employees. With a portfolio of four distinct products for employee benefits, the company recognized the untapped potential for cross-selling and upselling opportunities. To enhance customer intimacy and drive revenue growth, the client sought to leverage machine learning to identify the next best product for each employee, providing personalized recommendations that resonate with their unique requirements.
Untapped potential for cross-selling and upselling opportunities.
Need to deliver tailored solutions catering to diverse employee needs.
Leveraging machine learning to provide personalized recommendations.
Our Solution.
Coforge spearheaded this customer-centric initiative, deploying cutting-edge technologies to unlock the power of data-driven insights:
Azure Data Factory was leveraged to extract and consolidate data from various sources, creating a robust foundation for predictive modeling.
Azure Machine Learning and Azure Databricks provided the ideal platform for data preprocessing, exploratory data analysis, and model development using Python.
AI/ML applications were developed, capable of analyzing and learning from large datasets, enabling accurate predictions and tailored product recommendations for employees.
Handled model training, evaluation, packaging, deployment, testing, validation, monitoring, and maintenance, ensuring optimal performance and accuracy.
The Impact.
90%: Accuracy Achieved on Unseen Data by the Predictive Model.
Personalized Offerings: Highly personalized product recommendations tailored to the unique needs and preferences of each employee.
Revenue Growth: Targeted cross-selling and upselling opportunities contributed to significant revenue growth, fostering customer loyalty and long-term profitability.
