Predictive model to reduce attrition

Goal

To substantially reduce voluntary agent departures, particularly among those who have worked with us for more than 90 days.

Goal

To substantially reduce voluntary agent departures, particularly among those who have worked with us for more than 90 days.

Strategy

Developing a highly effective predictive model that calculates a risk score for each agent and identifies the factors that contribute to their risk of leaving.
Quickly identifying agents who are at high risk of leaving and taking targeted preventative action

Strategy

Developing a highly effective predictive model that calculates a risk score for each agent and identifies the factors that contribute to their risk of leaving.
Quickly identifying agents who are at high risk of leaving and taking targeted preventative action

Highlights

Assigning a unique probability score to each agent, enabling us to manage each agent more effectively.
Categorizing agents into different programs and hierarchical tiers, making it easier to prioritize intervention measures.

Highlights

Assigning a unique probability score to each agent, enabling us to manage each agent more effectively.
Categorizing agents into different programs and hierarchical tiers, making it easier to prioritize intervention measures.

Results

We are proud to report a significant decrease in monthly attrition rates by 0.8 percentage points, which has positively impacted our absenteeism rates. Our proactive approach has proven to be highly effective in retaining valuable agents and improving our overall performance.

Results

Elevating Efficiency and Reducing Costs through Automation

Stress-o-meter: Proactive Complaint Mitigation with Analytics

Payment Data Interchange

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Predictive model to reduce attrition

Goal

Goal

Strategy

Strategy

Highlights

Highlights

Results

Results

Cases

Elevating Efficiency and Reducing Costs through Automation

Stress-o-meter: Proactive Complaint Mitigation with Analytics

Payment Data Interchange