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Case Studies

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Create a predictive framework to reduce high attrition

Create a predictive framework to reduce high attrition

Create a predictive framework to reduce high attrition

How targeted retention strategies saved $45MM in revenue

How targeted retention strategies saved $45MM in revenue

$45MM revenue identified

$40MM saved in retention

$5MM saved with focus

Enhanced service

The challenge

Tackling operational inefficiencies and retention challenges

A leading wholesale drug distributor, servicing long-term care facilities, wanted to have competitive edge and foster industry consolidation. Over the past several quarters, the distributor wanted to explore avenues for sustained revenue opportunities. The organization aimed to better understand the reasons behind attrition and implement proactive retention strategies to safeguard its client base.

Key challenges

  • Focus on improving customer experience through faster, more accurate service

  • Increased competition and market consolidation reducing market share

  • Need to identify at-risk accounts and manage retention proactively

  • Need to boost business growth

The solution

Unlocking the drivers of customer attrition

Identification of attrition drivers

Developed churn hypotheses

Analyzed key data

Defined segment attrition

Predictive modelling

Applied predictive models

Focused on profitable facilities

Customized retention strategies

Implementation approach

1

Data gathering

  • Collected facility and service data

  • Identified churn factors

  • Defined attrition metrics

2

Predictive modeling

  • Predicted churn with ML

  • Prioritized profitability and segments

  • Provided retention strategies

3

Retention strategy

  • Targeted satisfied facilities

  • Reduced call abandonment

  • Tailored retention strategies

The impact

Revenue growth through retention

Revenue opportunity

  • $40MM saved from nursing homes

  • $5MM saved from assisted living

  • $45MM retention revenue

Improved service levels

  • Proximity-based pharmacies

  • Monitored supplies

  • Customized kiosks

Retention boost

  • Improved satisfaction

  • Targeted key areas

  • Boosted retention

Looking ahead

Expand retention targeting

  • Focus on additional facility types and service areas

Enhance predictive models

  • Continuously refine models with updated data

Improve customer service

  • Strengthen operational efficiencies to reduce churn