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Company focus

SeekOut
Product Improvement Medium Member-only

How might SeekOut enhance its sourcing tools to help users find passive candidates more effectively?

Prepared by NextSprints

15 mins
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Product Strategy User Research Data Analysis HR Tech SaaS Recruiting User Experience Product Improvement Data Analytics Talent Acquisition AI Recruiting
Product Management Improvement Question: Enhancing SeekOut's sourcing tools for passive candidate discovery

Introduction

To enhance SeekOut's sourcing tools for finding passive candidates more effectively, 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 SeekOut's strategic goals.

Step 1

Clarifying Questions

  • Looking at SeekOut's position in the market, I'm curious about our competitive advantage. Could you share insights on what sets SeekOut apart from other sourcing tools like LinkedIn Recruiter or Entelo?

Why it matters: Helps focus on unique strengths to leverage in our solution Expected answer: AI-powered matching algorithms and extensive data sources Impact on approach: Would emphasize enhancing AI capabilities and data integration

  • Considering the evolving nature of passive candidate engagement, I'm wondering about our users' current success rates. What percentage of outreach to passive candidates typically results in positive responses?

Why it matters: Identifies the scale of the problem and potential for improvement Expected answer: Around 10-15% positive response rate Impact on approach: Would focus on improving candidate targeting and personalization

  • Given the importance of user adoption for any new feature, I'm interested in understanding our user base. What's the breakdown of our user types (e.g., corporate recruiters, agency recruiters, hiring managers)?

Why it matters: Ensures solutions cater to the needs of our primary user groups Expected answer: 60% corporate recruiters, 30% agency recruiters, 10% hiring managers Impact on approach: Would tailor solutions to corporate recruiter workflows primarily

  • Considering the potential for AI and machine learning in sourcing, I'm curious about our current data capabilities. What types of data do we currently collect and analyze about candidate behavior and preferences?

Why it matters: Determines the feasibility of advanced predictive features Expected answer: Basic profile data, job history, and some social media activity Impact on approach: Would explore ways to ethically expand data collection and analysis

Tip

At this point, I'd like to take a 1-minute break to organize my thoughts before diving into the next step.

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Updated Jan 22, 2025