Analytics

X processes 500 million tweets daily through a two-stage pipeline powered by a Grok-based transformer. The algorithm assigns different weights to different engagement types, heavily favoring replies and retweets over likes. Understanding these mechanics changes strategy.

You spend 20 minutes crafting an original post that gets 47 impressions. A quick reply to someone else's tweet reaches 4,000 people. This isn't luck. The algorithm heavily weights replies compared to likes, and the architecture explains why.

Platform-wide average engagement rate on X is 0.029%. That's not a typo. For every 1,000 impressions, the average post generates fewer than 0.3 engagements. Here's how to interpret your performance against realistic benchmarks.

𝕏 released their full recommendation algorithm source code today. The biggest surprise is that they've thrown out the old system entirely. Here's what the code reveals and what it means for your growth strategy.

Replies are one of the highest-ROI activities on X, but most people don't measure them at all. Time invested feels like it produces no clear output. That's wrong. Reply ROI is absolutely measurable. It just requires a different framework than tracking post performance.

Standard 𝕏 metrics tell you what happened. Cohort analysis tells you why. By grouping followers based on when and how they joined, you can identify which content attracts your best audience, which growth strategies produce lasting engagement, and where your retention breaks down.

Not all tweets are created equal. Some get likes but don't drive profile visits. Some go viral but attract the wrong audience. Understanding what makes a tweet genuinely valuable changes how you create content and how you decide which tweets to engage with.

Impressions down 40% from last week. Posts that used to get thousands now struggle for hundreds. First: don't panic. Second: don't immediately overhaul your strategy. Impressions naturally vary by 20-50% day-to-day. Here's how to diagnose what's actually happening and what to do about it.

Studies saying 'Tuesday at 9 AM' are platform-wide averages. Your audience isn't average. The best time depends on your followers' time zones, habits, and scroll patterns. Generic advice gets generic results. Here's how to find your optimal times through systematic testing.

More data doesn't mean better decisions. Most people track too many metrics and end up overwhelmed, paralyzed, or chasing the wrong things. Five metrics weekly. That's it. Everything else is noise. Here's what deserves attention and what to deliberately ignore.

There's a fine line between using metrics to guide decisions and letting them consume your mental energy. The goal is metric-informed, not metric-obsessed. If checking analytics makes you stressed rather than informed, something's off. Here's how to interpret numbers without letting them run your life.

Intuition only takes you so far. At some point, you need to know, not guess, what works. X doesn't have built-in testing tools, so you have to design experiments yourself. Test one variable, measure results, let data tell you what to do next. Here's how to do it effectively.

Native X analytics are overwhelming. Premium features are gated. You need something simpler. Five metrics, one page, 15 minutes per week. Something that tells you what's working without creating another chore. Here's how to build it.

Profile visits are the bridge between someone seeing your content and someone following you. Without them, followers don't happen. If visits are consistently low, you've identified a critical bottleneck. There are five root causes, and the fix depends on which one applies to you.

Random content produces random results. For most creators, 20% of themes drive 80% of engagement. 20% of topics attract 80% of new followers. Your job is finding your 20%. Most people post whatever comes to mind and wonder why growth is inconsistent. Systematic theme analysis changes that.

The difference between creators who grow slowly and those who grow quickly often isn't talent or luck. It's learning speed. Every post teaches you something. The question is whether you're extracting that lesson systematically or just posting and hoping.

Impressions, engagement rate, algorithmic distribution, shadow banning. 𝕏 has its own vocabulary. Understanding these terms helps you make sense of growth advice and interpret your own analytics. Here's a plain-language glossary of the terms that matter.