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Product Management Improvement Question: Redesigning Medium's commenting system for meaningful reader-writer discussions

In what ways can Medium's commenting system be redesigned to foster more meaningful discussions between readers and writers?

Product Improvement Hard Member-only
User Experience Design Feature Prioritization Metrics Analysis Digital Publishing Social Media Content Creation
User Engagement Community Building Content Platforms Product Redesign Medium

Introduction

Redesigning Medium's commenting system to foster more meaningful discussions between readers and writers is a critical challenge that could significantly enhance the platform's value proposition. As we explore this opportunity, we'll need to consider the diverse needs of Medium's user base, the current limitations of the commenting system, and innovative approaches to encourage high-quality interactions. I'll structure my response to address key aspects of this product improvement challenge.

Step 1

Clarifying Questions

  • Looking at Medium's position in the content creation ecosystem, I'm curious about the current engagement metrics for the commenting system. Could you share some insights on the average number of comments per article and the percentage of readers who engage with comments?

Why it matters: This will help us understand the baseline engagement and identify improvement opportunities. Expected answer: Low engagement, with only 5% of readers leaving comments and an average of 3-5 comments per article. Impact on approach: If engagement is low, we'll focus on increasing participation; if it's high, we'll prioritize quality improvements.

  • Considering Medium's diverse content categories, I'm wondering about the variation in commenting behavior across different topics. Are there specific content areas where discussions are particularly vibrant or notably lacking?

Why it matters: This information will guide us in tailoring solutions to different content types and user segments. Expected answer: Tech and politics articles generate more comments, while creative writing pieces see less engagement. Impact on approach: We might develop category-specific features or focus on boosting engagement in underperforming areas.

  • Given the platform's focus on quality content, I'm interested in understanding how writers currently perceive and interact with the commenting system. What percentage of writers actively engage with commenters, and what feedback have they provided about the current system?

Why it matters: Writer engagement is crucial for fostering meaningful discussions. Expected answer: Only 30% of writers regularly respond to comments, citing time constraints and low-quality interactions as barriers. Impact on approach: We'll need to address both reader and writer pain points to improve overall engagement.

  • Considering the evolving landscape of online discussions, I'm curious about Medium's stance on AI-assisted moderation or content enhancement for comments. Has the platform explored or implemented any AI technologies in this area?

Why it matters: AI could potentially help scale quality control and enhance discussions. Expected answer: Limited exploration so far, open to considering AI solutions that align with Medium's quality standards. Impact on approach: We might investigate AI-powered features to complement human-driven interactions.

Pause for Reflection

Before we dive into user segmentation, let's take a moment to reflect on these insights and how they might shape our approach to redesigning the commenting system.

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