So you’ve got your content calendar in place. You’ve written blog posts, turned them into social media snippets, emailers, and maybe even a few videos. You’re showing up consistently.

But now comes the tricky part:
Is any of this actually working?

For most businesses, this is where momentum slows. Either you don’t have time to track performance, or you don’t know what to look for. Even if you pull the numbers from LinkedIn, Google Analytics, or email reports—you’re left staring at dashboards, unsure of what to do next.

This is exactly where Generative AI can step in—not to give you more data, but to help you understand what the data is saying and guide you on what to do next.

Let’s break this down into a simple, repeatable process.

Step 1: Gather the Right Data

Before you can ask AI to analyze anything, you need to gather the right inputs.

You don’t need fancy tools. Just export or copy:

  • Social media engagement metrics (likes, comments, shares, reach)
  • Blog traffic data (page views, bounce rate, time on page)
  • Email performance (open rate, click-through rate, unsubscribe rate)

Example Prompt:
“Summarize the performance of these 10 LinkedIn posts. Here’s the data for each post including likes, comments, reach, and impressions. Help identify which types of posts performed best and why.”

Paste the data in a table format. AI will do the analysis.

Step 2: Identify What’s Working (and What’s Not)

Once you have your data, AI can help spot patterns you might miss.

You can ask:

  • What kind of posts get the most engagement?
  • Do posts with certain headlines or formats (e.g., carousels, questions, stories) perform better?
  • Which blog topics brought in the most traffic?

Example Prompt:
“Review the blog traffic data and highlight what themes or formats are drawing the most visitors. Suggest what topics we should do more of.”

This gives you a feedback loop. You start creating content based on actual performance—not just gut feel.

Step 3: Improve What’s Not Working

The beauty of AI isn’t just in showing what didn’t perform—it’s in helping you fix it.

Let’s say some of your LinkedIn posts had great content but low reach. You can ask AI to:

  • Rewrite those posts with better hooks
  • Suggest new formats (e.g., turning a post into a carousel or poll)
  • Improve the call-to-action

Example Prompt:
“Here are 3 LinkedIn posts that didn’t do well. Rewrite each one with a stronger hook and more engaging CTA for founders in the B2B SaaS space.”

Or for emails:
“Open rate for this email was low. Suggest better subject lines and preview text to improve open rates.”

Over time, you’ll not only fix underperformers—you’ll start creating better content from the start.

Step 4: Plan What to Do Next

Once you know what’s working, and what isn’t, AI can help build an action plan.

You can ask:

  • What should we post more of next month?
  • What topics should we avoid?
  • How should we tweak our email schedule?
  • Should we shift from long blogs to short ones?

Example Prompt:
“Based on the content performance from last month, suggest a weekly content plan for LinkedIn and blog posts for the next 4 weeks.”

Think of AI as your strategist—not just your assistant.

Step 5: Turn Learning Into Collaboration

If you’re working in a team, you’ll want everyone to learn from this.

With a multi-model AI platform like Chaturji, your team can:

  • Share these prompts and results in a shared space
  • Review and comment on analysis together
  • Build a feedback library of what works (and what to avoid)
  • Reuse and repurpose successful content formats

Chaturji makes it easy to loop in your content writer, marketing lead, and even your founder—so you’re not the only one with insights. Everyone sees what works, and the entire team gets sharper.

Final Thoughts

Measuring your content doesn’t have to be a boring numbers exercise.

With Generative AI, you get quick, actionable insights that tell you where to double down—and where to rethink. You stop guessing and start evolving.

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With tools like Chaturji, it’s not just possible—it’s practical.
You don’t need to be a data nerd or a strategist. You just need to ask the right questions.

And now, you know how.