Subreddit Marketing Guide

How to Market on r/analytics

A community for data and web analytics professionals. Discussions on Google Analytics, attribution, data visualization, A/B testing, and turning data into insights. From marketing analysts to data scientists.

140Ksubscribers
400active now
Moderate Self-Promo Policy
Subscribers
140K
Total community members
Active Now
400
Users currently online
Post Lifespan
24-48 hours
How long posts stay relevant
Peak Times
weekday morning-est
Best time to post

r/analytics Rules & Self-Promotion Policy

Understanding the rules is critical for successful marketing. Here's what you need to know about r/analytics.

Moderate Self-Promotion Policy

Self-promotion is allowed in context. Lead with value, not your product. Promotional posts may be removed.

Community Rules

  • 1No job postings or recruitment
  • 2Include context in questions
  • 3No tool spam or affiliate links
  • 4Be respectful and constructive
  • 5Stay on topic for analytics

How to Write for r/analytics

Data-driven and precise. The community values accurate methodology and honest interpretation. Acknowledge limitations in data. Share both what worked and what the data couldn't tell you.

Best Practices for r/analytics

Maximize your impact by understanding when, what, and how to post.

Best Times to Post

  • Weekday Morning Est
  • Tuesday Wednesday Est
  • Thursday Afternoon Est

Posts stay relevant for about 24-48 hours

Content That Works

  • Tool comparisons with real data
  • Implementation case studies
  • GA4 migration experiences
  • Attribution methodology deep-dives

Common Flairs

DiscussionQuestionGoogle AnalyticsCareerTutorial

Who's Here

Marketing analysts, data analysts, growth marketers, and data scientists. Many work with Google Analytics, Mixpanel, Amplitude, or similar tools. Value accuracy and actionable insights over vanity metrics.

Common Mistakes on r/analytics

Avoid these pitfalls that get marketers banned or ignored.

Claiming perfect attribution

Analytics professionals know attribution is hard. Anyone claiming to have solved it perfectly loses credibility.

Instead

Acknowledge complexity: "Our model captures ~70% of conversions. Here's how we handle the gaps."

Ignoring privacy changes

iOS 14, cookie deprecation, and privacy regulations have disrupted analytics. Ignoring this context feels outdated.

Instead

Address the current landscape: "Post-iOS 14, our approach is... Here's how we're adapting to cookie changes."

Promoting tools without methodology discussion

Tools are only as good as how you use them. The community cares about methodology, not feature lists.

Instead

Lead with approach: "Here's our attribution methodology. This tool supports it by..."

Focusing on vanity metrics

Page views and sessions without context don't impress analysts. They want to see impact on decisions.

Instead

Connect to outcomes: "This analysis changed our budget allocation by 20%, resulting in..."

GA4 complaints without solutions

Everyone knows GA4 has a learning curve. Pure complaint posts without insights add no value.

Instead

Share solutions: "GA4 was frustrating until we figured out [technique]. Here's our setup."

Post Formats That Work on r/analytics

These content formats consistently perform well in this community.

Migration Case Study

Example Format

""Our GA4 migration: timeline, challenges, surprises, and what we'd do differently. Data continuity approach included.""

Why It Works

Timely and relevant. Honest about challenges. Practical advice for others migrating.

Attribution Analysis

Example Format

""How we approach attribution in [industry]. Models we tested, what we landed on, and how it changed our marketing mix.""

Why It Works

Methodology focus. Real decision impact. Industry context helps others evaluate fit.

Tool Comparison

Example Format

""[Tool A] vs [Tool B] for [use case]. Our evaluation criteria, testing approach, and decision rationale.""

Why It Works

Practical comparison. Clear criteria. Helps others making similar decisions.

Related Communities & Use Cases

Expand your reach with similar subreddits and see who uses r/analytics for marketing.

Frequently Asked Questions

Common questions about marketing on r/analytics

With methodology context, yes. Don't just announce features—explain how your tool supports better analytics practice. Case studies showing real analysis using your tool resonate better than feature lists.
GA4 migration experiences, attribution methodology, privacy-first analytics approaches, and tool comparisons. The community is navigating significant industry changes and values practical guidance.
If your product serves analysts, yes. The audience includes marketing analytics professionals who influence tool decisions. Build credibility through valuable content before promotional posts.
Moderately technical. Include methodology and reasoning, but remember the audience spans marketing analysts to data scientists. Make content accessible while respecting analytical depth.
Very much so. The community is navigating privacy changes actively. Tools that solve privacy challenges while maintaining analytical value get positive attention.
Yes, if they demonstrate good practice. Share the reasoning behind metric selection and visualization choices. Dashboards that tell a story get more engagement than pretty charts.

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