Overview: In this episode, we explore strategies for re-engaging lost customers, diving into whether it's worth the effort and cost to win them back. We reference a study by professors from Germany's Freie Universität Berlin, University of Münster, and the SMU Cox School of Business, which analyzed 25,000 former customers of a subscription book service. The discussion includes customer segmentation, targeted marketing messages, and the importance of addressing both economic and emotional costs of returning.

Key Insights:

1. Customer Segmentation:
   • Migrant Birds: medium satisfaction and long-term time absence
   • Committed but Unsure: High satisfaction, medium-term absence.
   • Disillusioned: Low satisfaction, medium-term absence.
   • Remorseful: Medium satisfaction, short-term absence.
2. Findings from the Study:
   • Customers blaming the firm for leaving didn't necessarily reduce their likelihood of returning.
   • Time elapsed since leaving increased the likelihood of return, especially when the company was at fault.
   • High reactivation costs deterred "Committed but Unsure" and "Disillusioned" customers, while "Remorseful" customers were less affected by these costs.
   • Emotional costs of returning were more significant than economic costs, highlighting the importance of personalized re-engagement strategies.
3. Marketing Messages by Segment:
   • Migrant Birds & Committed but Unsure: Emphasize commitment to making the relationship work.
   • Disillusioned: Highlight changes and ease of return.
   • Remorseful: Things have changed and our relationship with you is important

Additional Studies:

1. Online Role-Playing Game in South Korea:
   • Users with high experience scores were less likely to return and stayed for shorter periods.
   • Community engagement (e.g., PC cafes, in-game friends) influenced return and retention.
   • Excessive community size might decrease effectiveness, referencing Robin Dunbar's research on optimal group sizes.
2. French Soccer Club Study:
   • Attendance and spending on single game tickets predicted return to season ticket status.
   • Newsletter engagement was a strong predictor of return.
   • Online social media engagement, particularly likes related to team members, was indicative of return likelihood.
3. General Insights:
   • Referrals and positive service recovery experiences increase the likelihood of return.
   • Tailoring win-back offers to the reason for departure improves retention.
   • Lower subscription prices increase reactivation rates, but higher prices can lead to longer retention.

Discussion Points:

• Is it worth the effort and cost to reacquire lost customers?
• How can businesses lower the emotional and economic costs of re-engagement?
• What role does community play in customer retention and return?
• How should businesses price win-back offers to maximize customer lifetime value?

This episode sheds light on the complexities of customer win-back strategies, offering actionable insights for businesses looking to re-engage lost customers effectively.

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