3,289
Active products with weak or missing SEO metadata
Titles, descriptions, and on-page signals that could be improved without changing product range.
Flagship project
Diagnosing SEO for a 17,000+ Product Shopify Catalogue
How we connected Search Console and Shopify data, identified thousands of opportunities, and prioritised what to fix first across a large ecommerce catalogue.
Industry:EcommercePlatform:ShopifyProducts Analysed:17,640+Project Status:ActiveMethodology:Large-catalogue diagnosis
Challenge
Large Shopify catalogues rarely have one obvious SEO issue. They have thousands of small gaps spread across products, collections, and historical content. The challenge is less about “fixing SEO” and more about building a repeatable workflow that can identify, prioritise, and execute improvements.
Catalogue reality
- 17,640 products
- Thousands of collections
- Historical content
- Thin product descriptions
- Weak metadata
- Imported HTML clutter
- Large catalogue management challenges
Discovery
What the data revealed
We connected live platform data with Search Console performance to move from guesswork to an opportunity map. The goal was to surface actionable work across the catalogue without turning the programme into an endless spreadsheet.
Connected data sources
ShopifyGoogle Search Console
649
Active products with imported HTML clutter
Legacy markup and formatting noise that obscures content and creates inconsistent templates.
1,725
Active in-stock products identified as actionable opportunities
Products where demand, availability, and ranking signals suggested prioritised updates.
What we found
Most large ecommerce sites do not have a single SEO problem. They have thousands of small opportunities hidden across products, collections and content.
17,640
Products analysed
3,289
Products with weak or missing metadata
649
Products with imported HTML clutter
1,725
Active in-stock optimisation opportunities
Approach
The fix sequence
Rather than treating SEO as a one-off project, we designed a phased approach that can be applied across a large catalogue and keep learning from live data.
- 1
Collection layer first
We started at the collection layer to strengthen category-level relevance and internal linking, then used that structure to support product-level work.
InisSeasaltWhite StuffBarbourClogau - 2
Product template improvements
Product improvements were designed to work across many URLs: repeatable template rules, structured metadata patterns, and clean content blocks that can be rolled out in batches.
- 3
Opportunity batches
Search Console performance data was used to build work queues and prioritise changes based on real demand and visibility signals.
CTR opportunitiesRanking opportunitiesContent opportunitiesCollection opportunities - 4
Continuous iteration
The workflow continues to learn from live data, feeding new opportunities back into the work queue so the catalogue keeps improving over time.
Timeline
Project timeline
- 1
Discovery
Connected Shopify and Search Console
- 2
Collection Optimisation
Priority commercial collections updated
- 3
Product Optimisation
High-opportunity product batches updated
- 4
Opportunity batches
Search Console opportunities prioritised and shipped
- 5
Measurement
Monitoring visibility, clicks and rankings
Working concept
What is an opportunity batch?
An opportunity batch is a set of targeted SEO improvements based on real search data. Instead of rebuilding the entire catalogue, batches let you make continuous improvements across products, collections and content while learning what works.
CTR improvementsCollection enhancementsProduct optimisationInternal linking improvementsContent adjustments
Example opportunity
Collection
Clogau
Search Console visibility
10,300+ impressions
Average position
22.8
Action taken
167 product pages updated
Status
Monitoring impact
Execution
Changes implemented
Execution focused on shipping real catalogue updates in measurable batches, while keeping the system flexible enough to expand across new priority categories.
167
Clogau products updated
51
Lunar Shoes products updated
52
Brakeburn products updated
14
Shepherd of Sweden products updated
10
Bridge Bags products updated
6
Elizabeth Scarlett products updated
Catalogue workstream
Additional collection improvements
Updates shipped across priority commercial categories.
Status
Current status
Foundation
Foundation phase complete
- Collection optimisation completed
- Product template improvements deployed
- Opportunity discovery workflow active
- Batch update workflow active
Current phase
Opportunity batches and measurement
The catalogue is now moving from broad optimisation into continuous improvement driven by Search Console data.
The programme is currently active. Google is still processing many of the catalogue and collection changes. Early indicators suggest positive movement across impressions, clicks and average position, but the project remains in the measurement phase.
Methodology
How Better Ranking works
Step 1
Connect data
Combine Search Console signals with platform data so decisions are driven by what is searchable and what is sellable.
Step 2
Identify opportunities
Surface and cluster opportunities across products, collections, and content — then prioritise by impact and feasibility.
Step 3
Prioritise fixes
Turn the opportunity map into a fix sequence: page groups, templates, and tasks your team can ship in the right order.
Step 4
Ship changes in batches
Ship changes in batches, validate templates, and expand across the catalogue once patterns prove out.
Step 5
Measure outcomes
Track movement via live data, then feed learnings back into the workflow so iteration becomes the default.
Large websites don't usually have one SEO problem. They have thousands of small opportunities.
This project demonstrates how a repeatable workflow can identify, prioritise and execute those opportunities across a large catalogue.
Need a clear fix sequence?
Connect your data and we’ll identify which page groups are failing, where the opportunity is, and what to fix first.
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