Retail Case Study
Wavelength Commerce
A dynamic pricing model that improved revenue without hurting occupancy.
+51%Conversion Rate
The Challenge
Where things stood before
Before working with us, Wavelength Commerce was dealing with manual processes that couldn't scale with a growing catalog and customer base, and it was starting to cost them real business.
Their team suspected AI could help but weren't sure where to actually start.
The Solution
What we built
Rather than jumping straight to a model, we spent time understanding the specific shape of the problem first.
The result was straightforward: a dynamic pricing model that improved revenue without hurting occupancy, built specifically around what Wavelength Commerce needed.
- Designed around Wavelength Commerce's actual data and workflow, not a generic template
- Benchmarked against clear, agreed-upon success metrics from day one
- Delivered within a 7-week timeline without cutting scope
- Validated thoroughly before deployment to avoid production surprises
Results
The impact, by the numbers
+51%
Conversion Rate
+35%
Forecast Accuracy
-46%
Manual Review Time
+30%
Revenue Lift
Tech Stack
Built with
PythonPyTorchPMS APIsSQL
Yonderfield Technologies
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