Uploaded byPeter Sobotta
Use Analytics to Prevent Costly Product Returns
The document discusses the challenges of managing online retail returns, highlighting the $26 billion issue faced by U.S. retailers due to customer expectations and lost revenue. It presents a solution that involves automated data collection and advanced analytics to improve the return process and enhance customer experience. ReturnLogic offers a plug-and-play analytics product that requires minimal IT involvement and aims to implement solutions rapidly.
Use Analytics to Prevent Costly Product Returns
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- 2. U.S. Online Retail Returns $26BHeadache
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- 4. Difficult to Avoid CustomerExpectations
- 5. Always Costly Increased Churn,Lost Revenue
- 6. We have lookedat your business
- 7. Today we showyou how to prevent costly product returns…
- 8. …and improve yourbottom line
- 9. The Problem The Solution OurProduct
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- 11. Business managers arenot necessarily data scientists
- 12. There is onlyso much you can do with an Excel pivot table
- 13. Yet you aretasked to solve one of the most difficult problems facing retail today…
- 14. …preserving the customerexperience
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- 23. How can wehelp?
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- 26. Real time trenddetection Monitor Customizable Thresholds Notifications
- 27. Corrective Insights that solvethe problem
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- 29. Data science ishard Automate your tools Plug-and-play analytics Problem Solution Our Product
- 30. How is ReturnLogic different?
- 31. Minimal IT involvement Automaticbenchmarking Implementation in days Matrix organization ready
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