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E-commerce Case Study

Kettlewell Retail Group

A fine-tuning project that reduced reliance on lengthy, brittle prompts.

+46%Conversion Rate
Kettlewell Retail Group digitallyscaled
ClientKettlewell Retail Group
IndustryRetail / E-commerce
Timeline10 weeks
ServicesLarge Language Model (LLM) Fine-Tuning
The Challenge

Where things stood before

When Kettlewell Retail Group first reached out, manual processes that couldn't scale with a growing catalog and customer base was the issue sitting at the top of their list.

Competitors and peers seemed to have this figured out already, which only made it more frustrating.

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 fine-tuning project that reduced reliance on lengthy, brittle prompts, built specifically around what Kettlewell Retail Group needed.

  • Benchmarked against clear, agreed-upon success metrics from day one
  • Designed around Kettlewell Retail Group's actual data and workflow, not a generic template
  • Validated thoroughly before deployment to avoid production surprises
  • Delivered within a 10-week timeline without cutting scope
Results

The impact, by the numbers

+46%
Conversion Rate
+38%
Forecast Accuracy
-34%
Manual Review Time
+46%
Revenue Lift
Tech Stack

Built with

Hugging FacePyTorchLoRAPython

“I was skeptical this would actually work for us specifically. But +46% conversion rate within a few months, and the process to get there was more thoughtful than I expected.”

OI
Oriana Isaacsen

Founder, Kettlewell Retail Group

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