Retail Case Study
Ravenline Retail Group
A demand forecasting model that reduced both stockouts and excess inventory.
+39%Conversion Rate
The Challenge
Where things stood before
Ravenline Retail Group came to us with a problem that had been building for a while: manual processes that couldn't scale with a growing catalog and customer base.
It was the kind of issue that showed up in day-to-day frustration long before it showed up in a report.
The Solution
What we built
We started by getting a clear picture of exactly where things were breaking down before proposing anything.
What we ultimately delivered was a demand forecasting model that reduced both stockouts and excess inventory, built specifically around what Ravenline Retail Group needed.
- Validated thoroughly before deployment to avoid production surprises
- Designed around Ravenline Retail Group's actual data and workflow, not a generic template
- Structured so Ravenline Retail Group's own team could monitor and maintain it going forward
- Delivered within a 5-week timeline without cutting scope
Results
The impact, by the numbers
+39%
Conversion Rate
+28%
Forecast Accuracy
-31%
Manual Review Time
+53%
Revenue Lift
Tech Stack
Built with
PythonProphetscikit-learnSQL
Silvermere Software
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