How to Do Content Analysis in the Age of AI

Analyzing content performance used to be much simpler. Did it rank, get traffic, and convert? If yes, great. If not, onto the next.

Today? Not so simple.

Artificial intelligence (AI) makes it easier and faster than ever to crank out content. However, audiences expect smarter and more unique insights from voices they actually trust. At the same time, search is evolving. Rankings can vanish behind AI-generated answers, Search Generative Experience (SGE) pulls from and synthesizes multiple sources, and zero-click results mean users get what they need without ever visiting your site.

So, content performance is harder to judge. Pages can lose traffic and still influence decisions or rank well but fail to earn trust and engagement. In other words: visibility no longer equals value.

AI makes content easier to create but harder to differentiate. Content analysis in marketing helps you understand what’s working, what’s not, and what to do next. Without it, teams rely on assumptions instead of evidence and often invest in seemingly productive content that ultimately fails to drive meaningful outcomes.

In this guide, we’ll break down why content analysis is important, how to do content analysis in an AI-influenced landscape, content analysis steps to evaluate performance and decide what to improve, expand, or retire — plus some great tools for content analysis.

What is Content Analysis?

Here’s the short version: Content analysis is how you evaluate content performance and quality to understand what’s doing well and why.

Effective content performance analysis combines both qualitative vs quantitative content analysis to paint a complete picture. Quantitative analysis revolves around measurable performance signals like traffic, impressions, rankings, and click-through and conversion rates. Qualitative research methods for content analysis look at the usefulness, clarity, accuracy, credibility, fit, and POV strength of the content itself.

Many stop at the numbers, but today’s winning brands don’t. They blend data signals with audience insight and a clear POV. Numbers show what’s happening, but qualitative insights explain why, providing much-needed context that allows for decisions that pay off.

How AI is Changing the Content Analysis Process

AI has changed how content is created, and it’s more important than ever to understand how to analyze content performance. With AI, the barrier to content creation is low. What was once time-consuming and resource-intensive can now be generated in minutes.

That’s why the internet is flooded with identical blog posts, regurgitated summaries, and surface-level answers. It’s a saturated landscape where publishing more isn’t the answer.

SEO is shifting from volume toward value. Today’s algorithms reward:

• Experience: Content rooted in firsthand knowledge and real-world application performs best. Examples and practical insights build trust in ways that theory and AI can’t.
• Expertise: Depth beats surface-level takes. Clear explanations, accurate details, and credible sources show you know what you’re talking about.
• Trust signals: You wouldn’t buy anything from someone you don’t trust, and neither will your audience. Author credibility, up-to-date information, transparent sourcing, and consistency give readers and algorithms the confidence that your content (and brand) is worth engaging with, leading to more visibility.
• Real POV and synthesis: Algorithms increasingly favor content that makes sense of complexity, has original thinking, interprets information clearly, and offers a clear POV.

As SEO shifts toward value, teams must rethink content analysis methods. It’s one thing for people to see your work, but it’s more meaningful when they read, save, share, and return to your content over time. These signals give a far clearer picture of long-term impact than impressions alone.

AI still plays an important role, but it’s not the decision-maker. It’s great for clustering content, tagging themes and thematic analysis, summarizing libraries, and detecting patterns, but it shouldn’t judge quality, relevance, impact, or priority. That requires a human touch.

That’s why modern growth teams track metrics like save and share intent, scroll depth, and completion rates. Together, they show not just what content is visible but also what’s resonating and influencing decisions.

The takeaway is simple: AI won’t replace content strategy, but it will replace content waste. Teams that solely rely on publishing high volumes of content will struggle. Those that pair thoughtful content analysis with a clear strategy will know what works, why it works, and what to do next.

Content Audit vs Content Analysis

People often confuse content audit vs content analysis, so let’s take a look at their differences.

A content audit is about improving visibility. It helps you take stock of what you have, where it lives, and its basic health. (Think checking URLs, formats, publish dates, broken pages, and duplicates.) An audit provides a baseline but not direction.

Content analysis goes deeper, focusing on interpretation and insight. Analysis can shed light on message clarity, audience fit and resonance, intent alignment, and more. You can determine what’s working, what’s falling flat, and why, make informed decisions about what to optimize, expand, or retire, and focus your efforts on content that actually pays off.

Both matter. While content audits offer a clear picture of where you are, content analysis informs you where to go next.

Why Content Analysis is Important

Content analysis is how modern teams make smarter decisions and can mean the difference between blending in and breaking through. Content analysis methods help you:

• Prioritize content that drives pipelines and trust: Instead of treating all content equally, analysis shows which pieces are influencing decisions, supporting sales conversations, and building credibility, so you can double down on what works.
• Sharpen POV and messaging: It also helps you determine what’s resonating and what’s falling flat, allowing you to refine your voice, move away from generic messaging, and consistently adopt perspectives that your audience cares about.
• Eliminate bloat: Analysis can expose outdated, duplicative, low-impact, or otherwise underperforming content, so you focus your efforts on assets that are worth your time and money.
• Protect resources in a content-saturated world: With content analysis, your team can adopt smarter, more sustainable, and more effective content strategies that justify the time, budget, and effort required in today’s increasingly saturated landscape.
• Feed distribution across social, email, and sales enablement: When you know how content performs across formats, you can prioritize what to amplify, tailor it to each channel, and effectively repurpose assets.
• Future-proof content against AI-generated competition: Content analysis can help you identify what sets your brand apart in the wave of AI-generated content and keep your content relevant and trusted — even as algorithms evolve.

A Proven 7-Step Content Analysis Framework

Ready to dive in? Here’s how to do content analysis, step by step:

1. Define Goals & Success Metrics

The first step to analyzing content performance is defining success. After all, how can you evaluate how your content is doing if you don’t know what it’s meant to do? When you define goals and success metrics at the funnel level, you can evaluate content based on the outcomes it’s meant to deliver rather than resorting to judging everything with the same yardstick.

Tie each piece of content to its role in the marketing funnel and the audience’s intent at that stage.

At the top of the funnel (TOFU), it’s about awareness and education. Your goal is to get eyes on content and gain new audiences who are actively seeking information or answers. Strong engagement, solid scroll depth, repeat visits, and growing reach, saves, and shares are signs you’re headed in the right direction.

In the middle of the funnel (MOFU), the goal is to support consideration and build credibility. MOFU content helps audiences evaluate options, understand tradeoffs, and see why you’re a trusted option. Success at this stage reflects growing confidence and shows up as deeper engagement, longer time on page, return visits, email sign-ups, and assisted conversions.

At the bottom of the funnel (BOFU), content is focused on conversions, sales conversations, and decision-making. BOFU content answers specific questions and removes friction to help prospects feel comfortable and confident taking the next step. This is where results get more direct. Think demo requests, contact form submissions, and conversion rates.

2. Build Your Content Inventory

Create a centralized content inventory with:

• Channels: Content often performs differently depending on channel, so note where your content lives. Common locations include blogs, landing pages, social media platforms, emails, and sales assets.
• Formats: Articles, social media posts, videos, guides, webinars, carousels, and one-pagers all serve different purposes and engagement styles. Knowing the format helps you spot repurposing opportunities.
• Funnel stage: Is your content aiming to educate or grab attention (TOFU) or help the audience evaluate their options and develop trust (MOFU)? Or is it there to help seal the deal (BOFU)? Clearly labeling the funnel stage prevents mismatched expectations when you analyze performance.
• Publish and update date: Record when an asset was published and last updated. If it has been a while, there’s a good chance the information, examples, or framing are outdated.
• POV category: Also, consider the type of content you have. Is it a thought leadership piece, product page, or educational resource?

Many people skip this step and don’t even know what they have! Often, building a content inventory immediately reveals duplication, gaps, and untapped opportunities already sitting in your library.

3. Pull Quantitative Performance Metrics

Find quantitative metrics to anchor your analysis in performance data. Dive into:

• Traffic, impressions, and keyword rankings: These show how discoverable your content is — how many eyes are on it, where it appears in search, and whether it’s continually entering the conversation or losing ground.
• CTR, bounce, dwell time, and scroll depth: If your audience is spending lots of time on your content, they’re paying attention. Congrats, you’re doing something right! If they bounce or don’t click at all, there’s likely a mismatch between intent and content.
• Shares, saves, and comments: These signal trust and deeper engagement. They’re signs of useful content that is sparking conversations, influencing readers, and deserving of wider distribution.
• Conversions and assisted conversions: Conversions show you which assets directly drive action, while assisted conversions reveal how content supports decision-making along the way.
• Content decay tracking: Content decay tracking shows when once-strong content is losing traction, helping you proactively refresh, consolidate, or retire assets.

Remember: AI makes impressions cheap. You can generate countless pieces of content per day and get thousands of impressions fast, but earning real attention and trust is expensive and requires hard work.

4. Evaluate Content Quality

Once you’ve got a good handle on your quantitative data, do a qualitative review. Assess:

• Clarity and usefulness: Does your content clearly answer the question it promises to solve? Is it easy to understand and genuinely helpful?
• Accuracy and source quality: Even the smallest inaccuracies can damage trust or prevent it from forming in the first place, so carefully review data and sources to ensure your content has current, reliable information.
• Narrative structure: Just like a good book or movie, strong content has a clear beginning, middle, and end, thoughtful transitions, and careful pacing to keep the audience engaged from start to finish.
• POV strength: Does your content offer a clear POV or opinion? Does it synthesize different information, showcase original thinking, or take a strong stance? Or does it repeat what’s already out there?
• E-E-A-T signals: Readers judge content credibility on Experience, Expertise, Authoritativeness, Trust (E-E-A-T), so clearly signal who your content is from, why they’re qualified, and why the information can be trusted.
• UX readability and accessibility: Short paragraphs, clear headings, readable fonts, and accessible design make content easier for people to consume, helping you reach more people.
• Value and uniqueness: Ask the most important question: Does this content say something only you could say? If an asset doesn’t add new insight, perspective, or value and could easily be replaced by a generic AI summary, rethink it.

5. Assess Audience Fit & Intent Match

Even strong content can flop if it doesn’t mesh with your audience. That’s why assessing audience fit matters.

Start by clarifying intent. Put yourself in your audience’s shoes. Are they trying to learn something, compare options, or take action? Match your format, depth, messaging, and CTA to that mindset to improve engagement and performance.

Next, review query alignment and the current SERP landscape. See what sorts of content are being rewarded for your target queries. You’ll probably notice AI-search previews, quick comparisons, expert synthesis, or featured snippets. If content doesn’t align with what search engines prioritize and users expect to see, performance may suffer.

Finally, watch user behavior signals. Scroll depth, dwell time, repeat visits, and bounce patterns reveal whether your content is landing or if you have a content messaging or audience misalignment problem.

6. Identify Patterns & Insights

Here, you zoom out from individual pieces to see the full story your content tells, shifting from what happened to patterns that inform a strategy that pays off.

To do that:

• Spot messaging wins and gaps: Find themes, ideas, phrases, narratives, or angles that consistently perform well. Also, notice what’s missing. Unanswered questions, underrepresented perspectives, and generic or underdeveloped content highlight your next opportunities.
• Evaluate topic clusters with momentum: If multiple related pieces are gaining attention, deepen coverage, strengthen internal linking, or add a stronger POV.
• Fix underperforming SEO pages: If you have pages that are ranking but failing to engage, you likely have an intent or value problem. But hope is not lost! Refining your message, reworking your content, strengthening the POV, or consolidating overlapping content can quickly boost performance.
• Find content that influences decisions: You’ll likely find the opposite, too: content that doesn’t generate much traffic but delivers significant value elsewhere. For example, some guides and comparison pages aren’t major traffic drivers but consistently influence sales conversions, deals, sales cycles, and customer follow-ups. So, update, protect, and even repurpose this content!
• Review audience and POV: Look for comments, search, and social engagement trends. The language people use, the objections they raise, and the topics they react to most can reveal how your audience is thinking and how your messaging and content need to evolve to stay relevant and understood.
• Track AI-search appearance trends: These can add another layer of insight for advanced teams. With AI-generated answers becoming more prominent in search, understanding when and how your content is being cited, summarized, or referenced can show topics you’re seen as an authority on and where you need to improve.

7. Prioritize Actions & Next Steps

Finally, it’s time to take everything you’ve learned about your content and put it to use.

First, decide the right next move for each asset. Some content may need to be expanded or reimagined in new formats to better match search or social intent. Other pieces may be duplicative, outdated, or irrelevant and are better consolidated or retired.

Luckily, you don’t have to start from scratch. If you’ve discovered you have ineffective, outdated content, updating and optimizing existing assets with a stronger POV, additional clarity, a more logical structure, and real examples may be the fastest way to improve. You can even repurpose content into other formats like videos, carousels, sales enablement materials, and influencer collabs to extend lifespan and reach.

With so many options, deciding next steps can be tough. An impact vs effort matrix helps you focus on changes that deliver the biggest results and best ROI.

Best Tools for Content Analysis

Tools for content analysis won’t replace a thorough analysis and solid judgment, but they do speed things up. Options include:

Technical & SEO

• GA4: Google Analytics 4 helps you understand how users interact with your content, from engagement and scroll depth to conversions and assisted conversions.
• Google Search Console: GSC provides several tools and reports to help measure search traffic and performance. You can then discover visibility issues and spot opportunities to improve performance.
• Ahrefs, Semrush, and Moz: These SEO tools provide deeper insight into keyword rankings, backlinks, competitive gaps, and content decay, helping you identify low-hanging fruit keywords, underperforming SEO assets, track your authority, and spot content opportunities.

Content Scoring & Research

• Clearscope and Surfer SEO: Clearscope and Surfer provide feedback on your pages and content, assigning scores or grades to help you determine how well your content covers a topic and where to focus your efforts.
• SparkToro: SparkToro and other audience insight tools tell you where your audience spends time online, which keywords they’re searching for, their demographics, and more, providing valuable context for content planning and distribution.
• AnswerThePublic and AlsoAsked: There are two powerful search listening tools that can help you find untapped keywords and content ideas that people are actually interested in.

User Behavior

• Hotjar: Hotjar provides heatmaps, session replays, and surveys that shed light on how users interact with content, letting you see movements, clicks, scrolls, and drop-offs.

AI Support

AI can be a powerful data collection tool and content analysis accelerator, but shouldn’t be the end-all and be-all. The key is a human-in-the-loop approach, where AI supports analysis and unearths patterns, while people make the strategic decisions.

• ChatGPT and Claude: AI tools like these can summarize libraries, tag themes, cluster content, spot patterns, and repurpose assets.
• Notion AI: Notion AI revises landing pages, researches competitors, uncovers market trends, translates content, organizes inventories, and drafts outlines.
• Excel or Sheets and GPT formulas: Combining spreadsheets with GPT-powered formulas helps scale tagging, scoring, and pattern detection across your content library.

Check out our guide for more tools and best practices when integrating AI in digital marketing strategies.

Ready to Start Understanding Your Content?

Content analysis is all about understanding what works, why it works, and where to focus next to stand out, but it isn’t easy, especially in the age of AI. If you’re feeling overwhelmed by data, short on time, or unsure how to analyze content performance, don’t panic.

At Terra, we help teams build powerful content marketing strategies, discover gaps and opportunities, and put all that insight into action.

Ready to learn more? Explore our marketing services or chat with our team today!

Content Analysis FAQs

How often should you analyze content?

Think of content analysis like a health check. A quick pulse check every quarter keeps things on track, while a deeper review once or twice a year helps catch bigger issues. High-impact or high-traffic content may need more check-ins, especially as search behavior and algorithms change.

What metrics matter most?

There’s no one-size-fits-all answer! Awareness pieces care about reach and engagement. Conversion-focused content cares about actions. In general, metrics like time on page, scroll depth, saves, shares, and traffic can tell you a lot.

How does AI change content analysis?

AI makes content easier to create, which means standing out matters more than ever. But AI also simplifies and accelerates analysis by helping summarize valuable insights, understand audience behaviors, spot gaps, and more.

What are some content analysis examples?

If you have a blog with posts that rank well but have low engagement rates and update your posts to have clearer messages and a stronger POV, that’s a form of content analysis. Or, if you spot topic clusters gaining momentum and decide to go all in with deeper coverage, that’s also content analysis. There are so many different forms of content analysis, and each looks different. But the goal is the same: turning insight into smarter action.

Do I need expensive tools for content analysis?

Not necessarily! Many teams can get actionable insights using free tools for content analysis like Google Analytics, Search Console, and spreadsheets. Paid solutions can speed up analysis and add depth, but you don’t need a massive tech stack to analyze content well.

How do I know if my content resonates?

When people linger, come back, and save, share, or reference it later, you’re onto something. Real resonance shows up in behavior, engagement patterns, and qualitative feedback, not just rankings.