BrilliantsIT

E-Commerce 📍 Adelaide, SA

eCommerce Store Grows Revenue 3.4x in 6 Months

An Adelaide online store needed better product visibility. We optimised category structure, product SEO, and the shopping feed — here's exactly what changed, and why it worked.

Industry
eCommerce / Retail
Location
Adelaide, SA
Services
E-Commerce SEO, Shopping Feed
Timeframe
6 Months
3.4x
Revenue Growth
+95%
Organic Sessions
-22%
Cost Per Acquisition
Adelaide eCommerce store dashboard showing revenue growth after category and shopping feed optimization

The Challenge

This Adelaide online store had a solid product range and reasonable traffic, but revenue wasn't reflecting either. A messy category structure buried best-selling products several clicks deep, individual product pages were thin on content and missing basic SEO fundamentals, and the Google Merchant Center shopping feed was riddled with errors — meaning a large share of products weren't even eligible to appear in Shopping ads or free listings.

The store was effectively invisible for a large portion of relevant product searches, both organically and in paid shopping placements.

The Strategy

We treated this as three connected problems — structure, content, and feed data — rather than isolated fixes.

🗂️

Category Structure Rebuild

Reorganised categories and subcategories around how customers actually search and browse, surfacing best-sellers and reducing clicks-to-purchase.

📝

Product Page SEO

Rewrote titles, descriptions, and metadata across key product pages, adding the specific, descriptive detail search engines and shoppers were both missing.

🛍️

Shopping Feed Cleanup

Corrected missing GTINs, mismatched categories, and disapproved listings in the Merchant Center feed, restoring full product eligibility.

🔗

Internal Linking

Added strategic internal links between related products and categories, spreading authority to previously buried product pages.

Timeline: Month by Month

M1

Audit

Full audit of category structure, product page SEO, and Merchant Center feed health, identifying the highest-impact fixes first.

M2

Feed Cleanup

Corrected feed errors and disapproved listings, restoring eligibility for a significant share of the product catalogue.

M3

Category Restructure

Rebuilt category and navigation structure around actual customer search and browsing behaviour.

M4

Product Page Rewrites

Rewrote titles, descriptions, and metadata across priority product pages.

M5

Growth Phase

Organic sessions and shopping impressions climbing consistently as changes compounded.

M6

Results Confirmed

Revenue growth reached 3.4x baseline, with cost per acquisition down 22% as feed and page quality improved match relevance.

The Results

Metric Before After (6 Months)
RevenueBaseline3.4x increase
Organic SessionsBaseline+95%
Cost Per AcquisitionBaseline-22%
★★★★★

"We assumed we just needed more traffic. Turns out half our products weren't even showing up properly in Shopping. Fixing that alone changed everything."

Store Owner
Adelaide, SA

Key Takeaways

Feed health is often invisible, and often the bottleneck.Disapproved or miscategorised products silently cap revenue regardless of how good your traffic looks.

Structure affects both SEO and conversion.A clearer category structure helped search engines and customers find products faster.

Better relevance lowers acquisition cost.Fixing feed and page quality improved ad match relevance, not just organic rankings.

Growth compounded, not spiked.The biggest gains built steadily from month 3 onward as fixes layered on top of each other.

Frequently Asked Questions

How did this eCommerce store grow revenue 3.4x?

Through a combination of restructured product categories, optimized product page SEO, and a cleaned-up Google Merchant Center shopping feed, which together increased both organic sessions and shopping ad performance.

What is a shopping feed and why does it matter?

A shopping feed is the product data file that powers Google Shopping ads and free listings. Errors or missing data in the feed directly limit how many products are eligible to show, and how well they match relevant searches.

Why did cost per acquisition drop while revenue grew?

Improved product-category matching and feed quality meant shopping ads were shown against more relevant searches, improving conversion rate and lowering wasted ad spend at the same time.

Want your product catalogue actually visible?

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