Want to improve your marketing content? Wish you could more easily extract meaningful insights from your analytics? Learn step-by-step how to use AI tools to analyze your marketing data and content, helping you make data-driven decisions that improve your content performance across all channels.
How to Conduct Content Analysis with AI
Now in its 11th year, AI adoption among bloggers has doubled in the past year alone. Only 20% of bloggers reported not using AI, down from 40% the previous year. This remarkable increase indicates a growing trend within the digital marketing community where AI tools are embraced for their efficiency and effectiveness in content analysis.
You can use AI to help you analyze and optimize any public-facing content, such as an ad, a social post, an email subject line, an article, your homepage, etc. Such versatility allows marketers to cover a wide range of areas where their content appears to ensure consistency and relevance across all channels. By integrating AI into your workflow, you can extract data-driven insights that were previously cumbersome or even impossible to obtain without specialized expertise.
First, you need a validated customer persona. This persona acts as a critical foundation for all subsequent AI analyses, ensuring that your evaluations are consistently aligned with your target audience’s needs and preferences. Without a solid persona, your analysis may be directionless, leading to suboptimal marketing strategies.
How to Develop a Valid Customer Persona to Assist in AI Analysis
These personas become the basis for all subsequent AI analyses, ensuring consistency and relevance. Drawing from the insights of persona expert Ardith Albee, Andy says a well-crafted persona should focus on making your audience intelligence actionable. While ChatGPT or Claude can quickly generate a basic persona using specific prompts, the first iteration may not be accurate and should only be used as a starting point. An effective persona requires more detailed and iterative refinement to truly represent your target audience.
To create an effective persona using AI, provide specific details about job title, industry, company size, geography, responsibilities and goals, and challenges. These attributes form the core components that the AI uses to generate a persona that mirrors your ideal customer. For instance, if you are targeting coders in the app development industry at a company of 50 people in North America, your persona should reflect the unique attributes and challenges faced by this demographic.
Demographic information is often less crucial in B2B marketing than many assume. Who cares whether this person is 42 years old and drives a Volvo if you’re trying to sell them some enterprise software? Instead, focus on their professional attributes and pain points directly related to your products or services. Once the initial persona is generated, review the AI’s output to identify inaccuracies or omissions. To refine the persona, have a back-and-forth conversation with the AI, instructing it to remove irrelevant details or add missing elements.
Repeat this iterative process until the persona aligns closely with your understanding of the target audience, then save and share it with your team to ensure consistency in future AI interactions. Pro Tip: If you’re using an open AI model, remove your brand name from your training data to prevent any unintended biases or misuse of proprietary information during the persona creation process.
How to Utilize AI to Examine and Enhance Your Content
Once you have a solid persona, you can analyze your content for gaps and opportunities. This process works for various content types, including sales pages, blog posts, social media content, email campaigns, landing pages, video scripts, marketing presentations, and more. For instance, if you want to improve the performance of your sales pages, AI can help identify key areas that need enhancement to boost conversion rates.
First, take a full-page screenshot of the sales page rather than just copying text. The visual allows the AI to analyze the visual hierarchy and conversion elements like logos and awards. You can use tools like Go Full Page, Awesome Screenshot, or Snagit to capture these full-page screenshots. Next, upload your persona along with your screenshot and a prompt that positions the AI as a conversion optimization expert. This setup allows the AI to assess the landing page’s use of best practices for high-converting pages.
The AI will analyze various elements, including the header clearly indicating the topic, copy addressing visitor questions and objections, message order aligning with prioritized information needs, supportive evidence backing marketing claims, personal connection through human elements, appropriate use of cognitive biases, and compelling calls to action. The goal isn’t just to find deficiencies; you want the AI to find weaknesses you can correct to make a more impactful, stronger landing page.
For example, implementing cognitive biases to incorporate psychological triggers can improve conversion rates ethically. Because people tend to expend more energy avoiding losses than seeking gains, highlighting registration deadlines or limited-time opportunities should be subtly incorporated into marketing messages when appropriate. One of Andy’s clients wanted to improve its landing page conversion rates. By prompting the AI to evaluate the page against conversion optimization best practices, he identified key deficiencies, such as lack of urgency and scarcity triggers, failure to address common objections, and missing emotional appeals like testimonials or success stories.
How to Employ AI to Assess Your Content Strategy
This process highlights potential content gaps by comparing the inferred meanings of covered topics. It enables you to craft articles that strategically fill those voids in your content strategy by focusing on high-potential topics. You can utilize AI exports from any social media platform, email service provider, or analytic tool, but you’ll need to clean the data before uploading it to your AI tool for effective analysis.
Start by viewing 12 months of your Pages Report data from Google Analytics 4 (GA4). Change the first column from “page path” to “page title” and add a secondary dimension of “source medium.” This will help you and the AI understand how content performs differently across channels. The report should show title tags in the first column, source and mediums in the second column (LinkedIn, social, Google search, email campaigns), and metrics in the following columns (engagement rate, total sessions, key conversion rates, etc.). Click the export button in the top right and download the data as a CSV file.
Next, open the export and clean the data manually; Crestodina strongly advises against using AI for this step due to potential issues. Remove any extraneous information, such as the first rows of comments, and eliminate rows with minimal data and non-relevant language versions of your content. Pro Tip: Consider adding topic tags to your content data before analysis. Spending about an hour manually adding topics to your top 50-100 posts (such as “AI content strategy” and “SEO content strategy”) will significantly improve the AI’s ability to identify patterns and make recommendations.
After cleaning your data, upload it to your preferred AI platform and begin the analysis process. For example, you can find out which topics work best in which channels or perform a semantic distance (gap) analysis to see which articles you should write next. Use specific analytical terms in your prompts to trigger more sophisticated analysis, such as semantic distance analysis, topic-channel correlation analysis, normalized engagement metrics, and counter-narrative identification.
How to Use AI to Visualize Your Content Performance
One of the most powerful capabilities of modern AI tools is their ability to create visual representations of data analysis. These visualizations can be particularly valuable for presentations and team meetings. For instance, if you have a GA4 export of your website data, including article topics and key performance metrics such as page views, average session duration, bounce rate, conversions, and engagement rate over the past 12 months, you can use AI to create a color-coded heat map.
The heat map can visualize correlations between these metrics and your article topics to identify patterns in performance. To do this, use the exported data to group rows by article topic. For each topic, calculate averages or medians for metrics like pageviews, engagement rate, conversions, etc. Apply color coding to indicate performance: green for high-performing topics, yellow for moderate performance, and red for low-performing topics.
Creating a heat map helps visually compare how different topics perform across metrics. Use the heat map to suggest content opportunities, such as expanding high-performing topics, improving underperforming topics with high potential (e.g., those with strong engagement but low conversions), and identifying which topics resonate with your audience. This visualization will also help you prioritize content updates or new article ideas accordingly.
Implementation Tips for Using AI in Content Marketing Analysis
Do you want to elevate the quality of your marketing content? Are you looking for ways to more effectively generate valuable insights from your analytics? Discover a step-by-step guide on how to utilize AI tools to examine your marketing data and content, enabling you to make informed, data-driven decisions that enhance your content performance across all platforms.
The evolution of digital marketing has placed a premium on data analysis and content quality. With the rise of AI technology, businesses now have powerful tools at their disposal to dive deep into their analytics. These tools not only help in understanding consumer behavior but also in refining content strategies to better engage your audience.
By leveraging AI, you can sift through vast amounts of data to identify trends, measure content effectiveness, and uncover insights that were previously difficult to detect. AI tools can automate the analysis of metrics such as click-through rates, engagement levels, and conversion rates, providing a comprehensive overview of what’s working and what needs improvement.
Adopting AI-driven analysis in your marketing strategy allows you to create more targeted and personalized content, leading to higher engagement and better ROI. Whether you are a seasoned marketer or new to the digital landscape, learning to integrate AI tools into your workflow can be a game-changer. Start your journey toward data-driven marketing success today and see the difference it can make in achieving your business goals.