Case Studies5 min read7 April 2024

How a Gym Equipment Brand Used Shopify Analytics to Grow

Sarah Patel

CRO Specialist

A gym equipment retailer was making decisions based on gut feel. We set up a proper analytics stack and surfaced insights that drove a 33% increase in revenue within a quarter.

A gym equipment retailer with a growing Shopify store had never properly looked at their analytics. They knew their monthly revenue figure from Shopify's dashboard, but had no visibility into which products were driving margin, which traffic sources were converting, or why their ROAS had been declining. When we started working together, the first question we asked was: 'What decisions do you wish you could make faster?' The answers shaped the entire analytics project.

Setting Up the Foundation

Their GA4 implementation was broken — a developer had incorrectly installed the tag, meaning purchase events were double-firing and the data was unusable. We rebuilt the GA4 implementation via Google Tag Manager, set up Shopify's server-side pixel for improved iOS tracking, and configured a clean attribution model agreed with the marketing team.

Rebuilt GA4 via GTM with correct e-commerce event schema
Implemented Shopify's Web Pixels API for first-party data capture
Created a Looker Studio dashboard pulling from GA4, Shopify, and Meta Ads API
Set up cohort reporting to track customer LTV by acquisition channel

The Insights That Changed Their Strategy

Within three weeks of clean data, several patterns emerged that directly contradicted the team's assumptions.

Discovery 1: Their Best-Seller Was Their Worst Margin Product

Their most-promoted product — a 20kg barbell — was their highest-revenue SKU but had a gross margin of 11% after fulfilment. Their adjustable dumbbell set, which received a fraction of promotional budget, had a 38% margin and a repurchase rate of 22%. We reallocated promotional activity accordingly.

Discovery 2: Email Was Massively Under-Attributed

Their previous attribution model was last-click. Under a data-driven model, email marketing was contributing to 34% of purchases in an assist role — but receiving zero credit and therefore zero budget discussion. We restructured the team's attribution conversation around assisted conversions, leading to increased investment in email content.

Key insightWithin one quarter of data-led decision-making, revenue grew 33% with only a 9% increase in marketing spend.