Life Science Research Tools: SEO & Portfolio Optimisation

From Invisible Catalogue to Revenue Engine

Client: Life Science Research Tools Provider | Sector: Research Tools / Laboratory Equipment
Services: Product Positioning, Voice of Customer, SEO Strategy

Context

The client was a major life science research tools provider — part of one of the world's largest life sciences groups — with a catalogue of over 5,000 products spanning antibodies, assay kits, reagents, proteins, and instruments. The company had a strong reputation in the research community, decades of scientific credibility, and a product portfolio that included market-leading brands.

But the catalogue had grown organically over many years, through internal development and acquisitions. Product naming conventions varied. Descriptions were written by different teams at different times. Technical specifications followed no consistent format. Some products had been renamed, repackaged, or repositioned — but the digital catalogue still reflected the original structure. The result was a product ecosystem where the science was excellent but the commercial presentation was fragmented.

The Challenge

The core problem was deceptively simple: researchers couldn't find the products.

Products that should have dominated search rankings — well-validated antibodies, established assay kits, instruments with large installed bases — were buried on page three or worse. The company was losing organic traffic to competitors with inferior products but superior digital presence. Conversion rates on product pages were below industry benchmarks, not because the products were wrong but because the pages weren't answering the questions researchers were actually asking.

The root causes ran deeper than SEO:

• Disconnection between search behaviour and product presentation. The company's product naming and categorisation reflected internal logic — how the R&D team thought about the portfolio. But researchers, lab managers, and procurement officers search differently. A researcher searches for "anti-CD20 antibody flow cytometry" not the internal product code. A lab manager searches for "ELISA kit human IL-6" not the brand name. A procurement officer searches for "replacement reagent for [competitor product]" — a query the company's catalogue didn't even acknowledge
• Product cannibalisation. Multiple products in the same category competed with each other for the same search queries. Overlapping product descriptions, duplicated keywords, and unclear differentiation between product variants meant the company's own catalogue was diluting its search authority. Google couldn't determine which product page was the "best" answer for a given query — so it often ranked none of them
• Metadata that didn't match intent. Product titles were technically accurate but commercially invisible. "Recombinant Human Protein X, His-tag, E. coli" is precise. But if nobody searches for that exact string, the precision is worthless. The metadata needed to match what researchers actually type into Google, not what scientists write on the datasheet
• Category architecture that confused rather than guided. The catalogue's category structure had evolved through mergers and product line additions. Some categories contained hundreds of products with no clear hierarchy. Others contained a handful of products buried under three layers of navigation. Researchers who landed on the website through search often couldn't find related products — the internal linking architecture was as fragmented as the naming

The Approach

Customer search behaviour research. Before touching a single product page, I needed to understand how the company's customers actually search for products. This wasn't a keyword research exercise in the traditional sense — it was customer research applied to digital behaviour.

I analysed search data, website analytics, and customer support queries to map how three distinct buyer personas — researchers, lab managers, and procurement officers — find and evaluate life science products. The findings challenged several assumptions the company had held for years:

• Researchers search by application and target, not by product category. "Western blot antibody [target]" outperforms "[brand name] antibody" by an order of magnitude
• Lab managers search for compatibility and workflow fit. "Compatible with [instrument]" and "protocol for [application]" were high-intent queries that the catalogue completely ignored
• Procurement officers search for replacements and alternatives. "[Competitor product] equivalent" and "alternative to [competitor brand]" were significant search patterns — and the company's catalogue didn't address them at all

This research became the foundation for everything that followed. Every subsequent decision — from product titles to category structure to metadata — was grounded in how customers actually behave, not how the company assumed they behave.

Keyword architecture across 5,000+ SKUs. I built a structured keyword framework that mapped every product to its primary search queries, secondary queries, and long-tail variations. This wasn't a spreadsheet of keywords — it was an architecture that defined the relationship between products, categories, and search intent. Products were grouped by target, application, and research area, creating keyword clusters that reinforced each other rather than competing.

Metadata restructuring. Product titles, descriptions, and technical specifications were systematically rewritten to match search intent while maintaining scientific accuracy. Titles were restructured to lead with the terms researchers actually search for. Descriptions were expanded to address the questions buyers ask during evaluation. Technical specifications were reformatted to be both scannable and searchable. This was done across thousands of pages, using the keyword architecture as the guide.

Portfolio rationalisation and cannibalisation fixes. I identified where products were competing with each other in search and consolidated positioning. In some cases, this meant clarifying the differentiation between product variants. In others, it meant implementing canonical URL strategies to concentrate search authority on the right page. The portfolio rationalisation also revealed products that were underperforming not because of weak demand but because of weak presentation — and several of these became growth opportunities once their positioning was corrected.

Technical SEO and site architecture. Schema markup was implemented across the product catalogue to improve search engine understanding. Internal linking architecture was rebuilt to reflect the keyword clusters, ensuring that related products reinforced each other's search authority. Category pages were redesigned as authoritative landing pages for high-volume search queries, rather than simple product lists.

The Results

What Happened Next

The keyword architecture and metadata framework became the standard operating procedure for all new product launches. Instead of each product launch starting with a blank page (or worse, copy-pasting from the nearest existing product), every new product now had a structured process: keyword research, search intent mapping, metadata creation, and category placement — all before the product page went live. This transformed SEO from a reactive optimisation exercise into a proactive part of the product launch process.

The portfolio rationalisation also identified several products that had been underperforming commercially not because of weak science but because of poor digital presentation. When their positioning was corrected and their metadata aligned with actual search behaviour, several of these products saw significant traffic and conversion improvements — revenue that had been sitting there all along, invisible because the catalogue wasn't presenting it properly.

The framework was designed to be scalable. As the company continued to grow through acquisition and new product development, the keyword architecture and metadata standards ensured that new products were discoverable from day one, rather than gradually becoming visible over months of organic search indexing.

Key Insight

In life sciences, the relationship between customers and products is mediated almost entirely through search — whether that's Google, a catalogue search bar, or a distributor's website. If your product can't be found when a researcher searches for it, it effectively doesn't exist. The biggest commercial opportunities in research tools aren't always new products — they're existing products that customers can't find.

This case study also illustrates a broader principle: customer research isn't just for new product development. Understanding how your existing customers search, evaluate, and purchase should inform every aspect of your digital presence — from product naming to category architecture to the technical specifications you choose to highlight. The companies that treat customer insight as a foundation for their entire commercial operation outperform the ones that treat it as a box-ticking exercise before launch.

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