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Optimizing Customer Support

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You know that outstanding customer support increases customer loyalty, but how do you know exactly what's working? That's the subject of our latest webinar around support center metrics and how they're used to uncover actionable insights.
Kerri Nunnamaker and Taryn Cooper will explain why analyzing simple response efficiency can only get you so far, and why more in-depth analysis and complex metrics actually leads to increased repeat purchase rates and customer retention.

Published in: Data & Analytics
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Optimizing Customer Support

  1. 1. Optimizing Customer Support
  2. 2. 3 Correlation between support usage and user transactions Identify at-risk, high LTV customers Products that create support volume What you’re going to learn 2 1
  3. 3. Case Study
  4. 4. Harris Farm Markets
  5. 5. Harris Farm Markets
  6. 6. Harris Farm Markets Resolving individual customer issue Making ongoing operational improvements
  7. 7. The Results
  8. 8. RJMetrics Demo
  9. 9. Number of tickets
  10. 10. Number of tickets
  11. 11. Number of tickets
  12. 12. Tickets by status
  13. 13. Average time to resolution
  14. 14. Average time to resolution
  15. 15. Peak ticket days and hours
  16. 16. Who is filing tickets?
  17. 17. Correlation between support usage and LTV
  18. 18. Identify at-risk, high LTV customers
  19. 19. Products that create support volume

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