Building Trust in Online Marketplace
Our client is one of the leading online marketplaces. A substantial proportion of transactions on client’s marketplaces received poor ratings. It brought down their credibility and started affecting buyer as well seller loyalty. Our team developed an analytical model, that recognized patterns behind poor rated transactions. Looking at these patterns and taking proactive action identified cases helped the client improve satisfaction among buyers as well as sellers.
Managing High Customer Churn
The client is a rapidly growing telecom service provider in the Middle East. They were experiencing high customer churn rate which was negatively impacting the company's bottom line. By integrating various statistical modeling techniques, our team developed a predictive model that could accurately identify the customers with higher probability to churn so that client could take corrective action in order to retain them.
Service Forecasting Model
The client is one of the most recognizable automobile brands in the world. They were facing challenges related to the accuracy of the internal forecasting of service volumes. Our team developed a more accurate, automated, and robust forecast model for the client’s service team which resulted into improved customer experience and increased service revenue.
Indentifying Potential Customers
The client is one of the leading travel & tourism agencies in Costa Rica. They were facing challenges related to identifying the potential customers to follow-up. Our team developed an efficient prediction mechanism to identify potential customers where they can provide larger attention. It had helped in improving the conversion ratio with reduced effort & time.