Reinventing Search At Abcam
Overview
This project played a key role in the successful redesign of Abcam’s e-commerce platform.
While user journeys at Abcam are often fragmented, they consistently center on a single objective: finding the right product
context & objectives
context
I had noticed in some previous research that with the catalogue increasing very fast, users seem less likely to find the right products for their experiments.
From a business perspective, this is likely to drive conversion as well as the user satisfaction and the customer live time value down.
Problem
Problem
Catalogue expanding rapidly
Lower Filter Engagement (<4% of visitors)
Drop Off at SRP (Search Result Page)
Impact
Harder product discovery
Inefficient search behavior
Loss in conversion
Objective
How might we redesign the search functionality so that all users find the product they need for their experiment?
USER EXPERIENCE
Nass
Lead UX Researcher
Brent
Senior UX Researcher
Meet the Team
For this strategic product for the company the team is composed of 4 UXers (2 researchers and 2 designers) and 1 product manager.
My Role
I led the research strategy, hypotheses workshop, and synthesis. I collaborated with design to translate insights into search flow concepts and prioritised research findings with the PM.
Dan
Head of UX
Andy
Lead UX Designer
Lorenzo
Senior UX Designer
Product
Adam
Lead Product Manager
Research Approach
Pre-existing Data
Data analysis suggested that search was likely to be a problem:
GA data suggested that sessions were dropping off at the SRP level
Low interaction with the filters (less than 4% of users) GA + Hotjar heatmaps
A UX survey realized in early 2020 indicated that overall search was the main concern from our users (chart on the right)
“Abcam’s platform receives millions of searches from scientists globally — but 60% of users dropped off before viewing a product. Finding the right reagent wasn’t just frustrating — it could cost researchers time, grant money, and experiment success.”
Methodology
The methodology chosen is always defined by the type of insights that needs to be uncovered or discovered.
Digital Ethnographic Study:
Allowed to gather both, attitudinal and behavioural insights.
40 interviews split across all the digital personas - users and non users
Diary Study:
Allowed to gather some contextual insights.
12 participants 2 of each main user personas - worldwide
What type of insights
In order to define which type of insight I needed for this research I decided to conduct some hypothesis workshop. The objective was to define what kind of insights we needed to gather in order to answer our design problem.
2 major hypothesis emerged from these sessions:
Users might feel overwhelmed with the number of search results
Users must have a search pattern since the first search terms are only what we scientifically call “targets”
Which led to 3 type of insights:
Attitudinal:
We wanted to understand our users' frustrations and concerns regarding their search journeys
We wanted to get an understanding of what the conscious issues were
Behavioral:
We wanted to observe users pain points during their overall search journeys
Identify any unconscious or nonverbal issues our users were facing (focusing on the findable discoverable understandable)
Contextual:
The objective was to uncover the pain points faced by users offline
We needed to understand the context of their usage
INSIGHT 1:
Researchers struggle to navigate the overwhelming variety of products and find it difficult to identify the right one for their needs
FINDINGS:
Participants were often lost with the variety of products they can find online (not only in our catalogue).
Participants find it difficult to choose the right product even with the information gathered on the product page.
The same pattern is used to search for products – first: target → Application → Species.
Soft criteria to select a product: references (~senior researchers), images (~junior researchers), conjugation.
Design Activation Opportunity:
→ Create intuitive product discovery flows, guided filtering by experiment context, and trust-building signals (peer validation, visuals, expert recommendations).
Execution of the research
findings & Insights
INSIGHT 2:
Scientists’ workflows blend long-term planning with short-term adaptability, requiring efficient tools for both.
FINDINGS:
Scientists plan their experiment ahead (around 1 month) but remain agile, often needing to find products quickly between experiments.
Selecting the right product is crucial as it determines the success of their experiment and their recognition by journals and peers.
Design Activation Opportunity:
→ Design for both planned and spontaneous research needs, enable saving or pre-selecting items for future use, and offer fast reordering or “experiment-ready” suggestions.
Impact
A new search functionality:
A 3 steps search to narrow down the results from the beginning.
Users have the opportunity to narrow down their search from the start by choosing options among 3 of the main research criteria identified during the exploratory research.
The filters displayed will vary depending on the product type the users are searching for.
It is an adapted intuitive search.
Modifying the user journey:
Introducing an additional step in the process, a (purposeful, useful friction)that allows users to select a specific type, enhancing precision compared to the previous experience.
Catering for overwhelming search results:
Results are refined to a manageable selection, preventing users from feeling overwhelmed and enabling them to quickly identify the right product for their experiment.
INSIGHT 3:
Researchers operate in diverse environments and actively share knowledge beyond their immediate teams.
FINDINGS:
They share their knowledge not only with the team but with a wider audience of scientists.
Their environment and comfort vary massively depending on the kind of institution they work in (equipment), which affects their work.
Design Activation Opportunity:
→ Enable community-driven insights and adaptable design experiences that acknowledge varying lab setups, levels of access, and collaboration needs.
Business Outcomes
Increase in revenue by 2.5% after 3 months (vs YoY expected)
Improved search-to-conversion flow by 2.5% after 3 months
10% reduction in search result list size after 2 months, 15% after 3 months
NPS Score increased after 3 months by 10%
Decrease of support calls by 2%
Conclusion
This project transformed Abcam’s search experience from an information-dump into a guided, researcher-centric journey. The redesigned model aligns with real scientific workflows, balancing precision and efficiency. Next, we plan usability testing on the prototype and iterative refinements based on real lab contexts.