European nutrition brand
Nutrition · eCommerce · Tooling & Implementation
The right tools. Data the team could trust.
Advised one of Europe's largest nutrition eCommerce brands through every stage of standing up their experimentation stack — tool selection, implementation, and validation of the setup.
Client name withheld on request.
Tooling illustration · Client confidential
Engagement outcomes
- An implemented experimentation stack
- Validated experiment data
- A programme live on the new stack
The context
In 2023 we partnered with one of the leading nutrition eCommerce brands in Europe — a high-traffic DTC business in the sports and lifestyle nutrition space. (The client is not named here at their request.) They were ready to make experimentation a core growth capability, but knew the foundation had to be right first: the wrong tooling, or a flawed implementation, would quietly undermine every test that followed.
The challenge
The brand had the traffic and the ambition to run a serious experimentation programme, but no established, validated tooling to run it on. They needed to choose the right platforms, integrate them correctly across a complex eCommerce stack, and — critically — be certain that the data those tools produced could be trusted. A testing tool that silently misfires or mis-tracks is worse than no tool at all: it produces confident, wrong decisions.
What we did
Define the requirements
Mapped requirements against the brand's traffic, tech stack, team capacity, and roadmap to define what the tooling actually needed to do
Select the right tools
Ran a vendor-neutral selection process across A/B testing, feature flagging, and analytics platforms — shortlisting and recommending the right fit
Support the implementation
Consulted throughout implementation: SDK and snippet setup, data layer, event tracking, and integration across the eCommerce stack
Validate before launch
Validated the implementation end to end with QA across devices, A/A tests to confirm the setup introduced no bias, and tracking checks to confirm the data could be trusted
What we learned
Tooling is infrastructure, not a purchase. The selection matters — but the validation matters more. An unvalidated implementation produces confident, wrong decisions, which is worse than running no tests at all.
