Auditing PLP Relevance at Scale for Virgin Experience Days
Virgin Experience Days
How we helped Virgin audit 2000+ product categories with ML & LLMs
What Virgin Experience Days faced
Virgin Experience Days has one of the UK’s largest catalogues of experiential gifts, spanning hundreds of product-listing pages (PLPs) and thousands of individual experiences. Over time, category relevance had become blurred – products were being surfaced under loosely related or duplicate PLPs, while genuinely relevant items were often buried deep within the site.
This made internal linking inconsistent, diluted topical authority, and risked poor user journeys across both organic and on-site search.
How we solved it
SILO conducted a large-scale PLP Relevance Audit, analysing over 430,000 product–category relationships to assess how well each product aligned with its assigned listing pages.
Using custom Python tooling, we embedded and scored every product and category title for semantic similarity, creating a scalable model of PLP relevance. This approach revealed mismatched placements, missing opportunities, and structural inconsistencies invisible through manual review.
The audit was accompanied by a detailed Excel data model and a written report explaining category-level insights, prioritised recommendations, and a framework for ongoing maintenance.
We also ran a live session with the VED team to walk through the outputs and demonstrate how AI-driven models could be applied to query tracking and future site optimisation.
The impact we delivered
- Analysed over 430k product–PLP relationships to map relevance with precision.
- Identified redundant and underperforming PLPs, helping streamline the taxonomy.
- Provided a clear framework for product-to-category optimisation, improving crawl efficiency and internal linking logic.
- Equipped the VED SEO team with a scalable dataset to monitor and maintain category quality over time.
This audit gave Virgin Experience Days the data intelligence needed to refine how experiences are organised, ensuring users and search engines find the right products faster – and that every category page works harder to drive organic growth.
I contacted SILO to support a bespoke analysis project focused on scoring the relevance and optimisation of thousands of PLPs and PDPs across our category inventory. He immediately understood what we were trying to achieve and quickly proposed a scalable, practical solution leveraging AI, Python, and APIs to assess relevancy and surface problem areas. The turnaround time was extremely fast, the approach was robust, and the project was delivered in a highly cost-effective way. I wouldn’t hesitate to recommend SILO for complex, data-driven SEO and analytics work.
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