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.
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
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 Ignoring this context feels outdated.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.
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Who Should Target r/analytics
Frequently Asked Questions
Common questions about marketing on r/analytics
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