A leading life insurance provider, headquartered in Mumbai, was aiming to shift away from its traditional way of driving sales that was formed on a Broadcast-based incentive scheme. The customer wanted to empower its Front Line Sales (FLS) executives with a mobility-based solution to realize its incentive aspirations and track incentive accruals. Blazeclan helped the customer by developing a serverless stack of service on the AWS cloud for data-driven predictive analysis of FLS. This is done by feeding real-time data generated from complex business transformations to a stack of algorithms.

Requirements Put Forth by the Customer

 

The company’s operations are driven through various sales channels. It aims to change its traditional way of steering the sales force based on Broadcast based incentive scheme. The company wants to empower its Front Line Sales (a.k.a. FLS) executives with a mobility based solution to view their personalized tasks which can help them to meet their incentive aspirations and track their Incentive accruals.

The FLS Incentive & Task Mobile App will predict the prioritized tasks which are personalized to improve incentives, past behavior, and business objectives. The backend of this App drives through multi-layered complex data transformation of front line sales information captured through various existing/external systems and running them through a stack of Algorithms. The program is designed to address productivity and attrition challenges at an FLS level. The objective is to maximize incentives to kickstart the virtuous cycle of productivity.

Blazeclan’s Solution to Help Customer Enhance its Front Line Sales

Blazeclan helped the customer by creating a unique system that will reshape their sales process completely. The approach followed includes key steps as described below.

  1. Microsegmentation of the FLS

Based on the demographics data and performance, the front line sales has been branched into 80 distinct fragments. This pushed the relevant tasks to FLS and identified the incentive ranges for every task.

  1. Task Allocation