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Product Management Analytics Question: Evaluating Slack's channel threading feature success using key performance indicators

Asked at Slack

15 mins

how would you measure the success of slack's channel threading feature?

Product Success Metrics Medium Member-only
Metric Definition Data Analysis Product Strategy SaaS Enterprise Software Collaboration Tools
User Engagement Product Analytics Communication Tools Feature Success

Introduction

Measuring the success of Slack's channel threading feature requires a comprehensive approach that considers multiple stakeholders and metrics. To effectively evaluate this product feature, I'll follow a structured framework covering core metrics, supporting indicators, and risk factors while considering all key stakeholders.

Framework Overview

I'll follow a simple success metrics framework covering product context, success metrics hierarchy, and strategic initiatives.

Step 1

Product Context

Slack's channel threading feature allows users to create organized, focused conversations within a channel by replying to specific messages. This feature aims to reduce clutter in busy channels and improve information discovery.

Key stakeholders include:

  • End users (employees in organizations using Slack)
  • IT administrators
  • Slack's product team
  • Slack's business leadership

User flow:

  1. User sees a message they want to reply to in a channel
  2. User clicks the "Start a thread" option
  3. User types their reply in the thread sidebar
  4. Other users can view and contribute to the thread

This feature aligns with Slack's broader strategy of improving workplace communication and reducing information overload. Compared to competitors like Microsoft Teams, Slack's threading implementation is more intuitive and user-friendly.

Product Lifecycle Stage: Mature - the feature has been widely adopted and is now a core part of the Slack experience.

Software-specific context:

  • Platform: Web, desktop, and mobile apps
  • Integration points: API for third-party app interactions with threads
  • Deployment model: Cloud-based, with updates rolled out gradually to users

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