Retail Case Study
Kestrelworks Commerce
A delay-prediction system that flagged supplier risk weeks before shipment dates.
+26%Conversion Rate
The Challenge
Where things stood before
Kestrelworks Commerce's biggest obstacle was manual processes that couldn't scale with a growing catalog and customer base — something their team had tried to patch more than once without lasting success.
Competitors and peers seemed to have this figured out already, which only made it more frustrating.
The Solution
What we built
Our approach focused on the root cause rather than the most visible symptom.
The result was straightforward: a delay-prediction system that flagged supplier risk weeks before shipment dates, built specifically around what Kestrelworks Commerce needed.
- Validated thoroughly before deployment to avoid production surprises
- Structured so Kestrelworks Commerce's own team could monitor and maintain it going forward
- Built using Python and Prophet for a stable, maintainable foundation
- Designed around Kestrelworks Commerce's actual data and workflow, not a generic template
Results
The impact, by the numbers
+26%
Conversion Rate
+30%
Forecast Accuracy
-21%
Manual Review Time
+32%
Revenue Lift
Tech Stack
Built with
PythonProphetOR-ToolsSQL
Lumenary Technologies
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