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ascarza_jmr_18_783d54d4-e548-41ed-b1d7-8a180f1ae85a.pdf
Preview of https://www.hbs.edu/ faculty/Publication% 20Files/ascarza_jmr_ 18_783d54d4-e548-41e d-b1d7-8a180f1ae85a. pdf
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📊 Size: 320 KB
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Summary

Companies often manage customer churn by targeting those at highest risk, but research shows this may not be optimal. Combining field experiments with machine learning, it's found that customers with the highest risk of churning aren't necessarily the best targets for retention efforts. Instead, firms should focus on identifying customers sensitive to interventions, regardless of their churn risk. This approach is more effective, with one study showing an additional 4.1-8.7% reduction in churn rate.

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Companies often manage customer churn by targeting those at highest risk, but research shows this may not be optimal.

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  • File Size: 320 KB
  • Pages: 20
  • Language: EN
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  • Last Updated: 5 months ago

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