How can Elsevier enhance its ScienceDirect platform to improve literature discovery for researchers?

Introduction

To enhance Elsevier's ScienceDirect platform for improved literature discovery, we need to analyze the current user experience, identify pain points, and develop innovative solutions. I'll approach this by examining user segments, analyzing their journey, and proposing targeted improvements that align with Elsevier's goals and the evolving needs of researchers.

Step 1

Clarifying Questions (5 mins)

• Looking at the product context, I'm thinking ScienceDirect might be facing challenges in user retention and engagement. Could you share some insights on the current user retention rates and average session duration?

Why it matters: Helps determine if we should focus on improving onboarding or enhancing the core search experience. Expected answer: Retention rates are steady but session duration has been declining. Impact on approach: Would prioritize improving the search and discovery process to increase engagement.

• Considering the competitive landscape, I'm curious about how researchers are currently discovering literature across different platforms. Can you provide information on the most common user flows for literature discovery, both on ScienceDirect and competitor platforms?

Why it matters: Identifies potential areas where ScienceDirect can differentiate or improve its offering. Expected answer: Users often start with Google Scholar and then move to specific platforms like ScienceDirect for full-text access. Impact on approach: Would focus on improving integration with external search engines and enhancing the transition from search results to full-text articles.

• Given the rapid advancements in AI and machine learning, I'm wondering about Elsevier's current implementation of these technologies in ScienceDirect. Could you elaborate on any AI-driven features currently in use or planned for the near future?

Why it matters: Determines the potential for leveraging AI to enhance literature discovery. Expected answer: Basic AI implementation for search relevance, with plans to expand into personalized recommendations. Impact on approach: Would prioritize advanced AI integration for improved search accuracy and personalized content suggestions.

• Considering the diverse needs of researchers across different fields, I'm interested in understanding the current level of customization available on ScienceDirect. Can you share information on any field-specific features or personalization options currently offered?

Why it matters: Helps identify opportunities for tailoring the platform to specific research domains. Expected answer: Limited field-specific customization, mainly through saved searches and alerts. Impact on approach: Would explore more advanced personalization options based on user behavior and research interests.