Introduction

Our Predictive Analytics model is unique in that it not only predicts which agents at a given company are at the highest risk of leaving in the next month, but also pairs those agents with the most likely reason why the agent is leaving based on the behavior they are exhibiting AND how to save the agent before they leave the company. This system not only provides invaluable information into the attitudes and job satisfaction of agents, but also provides managers with the tools and insight they need to intervene with their highest risk agents before it is too late.

Throughout AnswerOn’s years of modeling on agent behavior and attrition, we have found that attrition-likely agents are heavily influenced by a change in policy. We quantify the impact of a policy or decision, model its specific influence in the agents’ lives, and create a solution to mitigate risk that still holds true to the company’s corporate goals. By pairing the agent’s perception of the issue with the numbers in the data – we have a 360-degree view of the problem, so we’re equipped to solve it with the correctly prescribed intervention. Our end-to-end solution has a true bottom line impact, returning an average 251% ROI in the first six months.

This Case Study highlights an AO customer who had previously implemented a performance improvement plan with the goal of improving agent efficiency. However, the policy, once in effect, ended up increasing agent attrition. Read specific details on how AnswerOn partnered with this customer to meet their corporate goals of increasing agent efficiency, while also understanding the needs of the agents and reversing this detrimental policy change.

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