Intelligent Search - Beckman Coulter
My Role:Overview
Beckman Coulter, a global leader in clinical diagnostics, faced the challenge of providing its customers with efficient access to a vast and diverse repository of information. Customers struggled to navigate disparate data sources, leading to time-consuming searches and frustration. The existing search functionality could not accurately interpret user intent, resulting in irrelevant results and increased search times, negatively impacting customer productivity and satisfaction.
The Challenge
Beckman Coulter's customers needed an enhanced search experience that would improve findability of critical resources while promoting new products and solutions. The existing platform failed to deliver efficient access to safety datasheets and technical specifications, creating significant barriers for laboratory professionals who required quick access to precise information.
Core Issues Identified:
- A search experience that couldn't interpret complex user intent
- Difficult findability of safety datasheets and technical specifications
- Lack of promotion for new products and solutions within search results
- Missing advanced AI features that could improve search relevance
- Low customer satisfaction due to time-consuming and frustrating search process
- Disparate data sources that created fragmented user experiences
The Process
Our user-centered redesign process began with existing Voice of the Customer (VOC) research to identify key pain points, which directly informed the development of sophisticated AI algorithms for improved search relevance. I created a user journey map highlighting each persona's pain points and information needs across the awareness, engagement, and sales stages, revealing difficulties in finding product details and specifications.
In partnership with the customer experience manager, I conducted usability testing with 10 remote participants (internal and external) using UserBrain to validate our design concepts. Key findings highlighted the need for improved filtering using standard categories and industry terms, with more effective display of search results emphasizing technical specifications and product information.
Key Process Elements:
- User Journey Mapping: Visualized customer pain points and information needs across key digital journey stages
- Usability Testing: Moderated user study identifying key enhancements
- Interaction Design: Prioritized findability of technical specifications and relevant filtered search features with customizable display options
- Collaborative Design: Worked with development and technical support to categorize information and define UI elements
The Outcome
The AI-driven search solution significantly improved information retrieval by better understanding complex user intent, resulting in a 50% increase in click-through rates. The redesign provided unified access to all of Beckman Coulter's resources with advanced filtering, intuitive category tabs, and personalized recommendations. This led to improved search efficiency by prioritizing technical specifications and product information in results.
Key Results:
- 50% increase in click-through rates through AI-powered search improvements
- Improved customer satisfaction through streamlined information access
- Integrated new products highlights within search results
- Unified platform that eliminated fragmented user experiences
Design Insights:
Key lessons learned during this project include the importance of creating multiple opportunities to capture customer feedback throughout the user journey. The Voice of the Customer research and usability testing revealed that customers need accessible feedback mechanisms at various touchpoints, not just during formal research sessions. This approach enabled continuous improvement and validated design decisions with real user input.
I also identified critical low points between the sales process and post-purchase stages where users experienced significant friction. These gaps highlighted the need for seamless transitions and better information continuity across different phases of the customer journey. The search functionality became a bridge between these stages, suggesting relevant content and products that supported users throughout their entire experience. This reinforced the value of designing systems that not only solve immediate problems but also anticipate future user needs through intelligent recommendations and progressive disclosure of information.
