How can Glean enhance its search relevance to better prioritize the most important information for each user?

Introduction

To enhance Glean's search relevance and better prioritize the most important information for each user, we need to dive deep into user behavior, pain points, and potential solutions. I'll approach this challenge by first clarifying our understanding of the product context, then segmenting users, analyzing pain points, generating solutions, and finally evaluating and prioritizing those solutions. Let's begin with some clarifying questions to ensure we're aligned on the problem space.

Step 1

Clarifying Questions (5 mins)

• Looking at Glean's position in the enterprise search market, I'm curious about the primary use cases driving adoption. Could you share the top 2-3 scenarios where users find Glean most valuable?

Why it matters: Helps focus our relevance improvements on the most critical user needs. Expected answer: Document search, people finder, and knowledge base queries. Impact on approach: Would prioritize algorithms and features specific to these use cases.

• Considering the importance of personalization in search relevance, I'm wondering about the data sources Glean currently integrates with. What types of user data and content repositories are we currently leveraging?

Why it matters: Determines the scope of information we can use to improve relevance. Expected answer: Integration with email, calendar, cloud storage, and internal wikis. Impact on approach: Would explore ways to better utilize existing data sources or identify new ones.

• Given the rapid pace of change in enterprise environments, I'm interested in understanding how frequently user search patterns evolve. Do we have data on how often search queries or topics trend and change within organizations?

Why it matters: Influences the agility required in our relevance algorithms. Expected answer: Significant shifts observed quarterly, with minor changes weekly. Impact on approach: Would focus on building adaptive models that can quickly adjust to changing patterns.

• Thinking about the competitive landscape, I'm curious about where users perceive Glean's strengths and weaknesses in search relevance compared to alternatives. Do we have recent user feedback or competitive analysis on this?

Why it matters: Helps identify specific areas where relevance improvements are most needed. Expected answer: Strong in document search, weaker in contextual understanding of queries. Impact on approach: Would prioritize improvements in natural language processing and context awareness.