Kelsey Raymond, COO

Kelsey Raymond is the COO of Intero Digital. Kelsey has over a decade of experience helping businesses achieve their growth goals through digital marketing strategies. She leads a team of experts in content marketing, PR, web design and development, Amazon marketing, social media, video, and graphic design.

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marketer using AI to create a content marketing strategy

AI for Content: How to Build a Content Strategy in the Age of AI

AI for Content: How to Build a Content Strategy in the Age of AI

Kelsey Raymond, COO • Intero Digital • January 25, 2024

marketer using AI to create a content marketing strategy

As the digital landscape evolves, the integration of artificial intelligence (AI) in content marketing is not just transformative; it’s revolutionizing the way we approach content marketing. 

A study by McKinsey & Co. revealed that organizations used an average of 3.8 AI capabilities (like natural language generation) in 2022 — double the 1.9 used in 2018. What’s more, marketing and sales experience some of the biggest reported revenue effects from AI.  

This shift toward effective automation is not merely about embracing new technology; it’s a complete reimagining of how to do business — and how to build a content strategy. With AI’s integration, we’re entering a new era when engagement, personalization, and streamlined processes are redefining digital marketing. 

In fact, McKinsey & Co. also found that 55% of business leaders anticipate AI to have a notable impact on marketing optimization, 53% expect AI to affect personalized outreach, 50% expect an impact on dynamic content, and 45% think marketing analytics will be impacted. 

Let’s dive into several areas where AI can bolster your content marketing efforts and help you build a content strategy that generates results efficiently. 

Personalization at Scale

The advent of AI in content marketing has opened a realm of possibilities for personalization at a scale that was previously unattainable. Personalization, once a manual and time-consuming process, can now be automated and refined, allowing content marketers to deliver highly tailored experiences to their audience. A prime example of this is Netflix’s use of AI and machine learning to personalize viewer recommendations to enhance user engagement and satisfaction. 

To implement AI-driven personalization in content marketing, the first step is data collection and analysis. AI systems thrive on data, and the more relevant data they have, the better they can understand and predict user preferences. Content marketers should focus on gathering data from various touchpoints, such as website interactions, social media engagement, and purchase history. This data can be found in your analytics platform (like Google Analytics or HubSpot, for example), and it provides the foundation for AI algorithms to identify patterns and preferences unique to each user segment. 

Once the data is collected, the next step is to leverage AI algorithms for predictive analysis, such as Salesforce Einstein or IBM Watson. AI algorithms can process the gathered data to predict user behavior and preferences. For example, AI can analyze past interactions of users with different types of content to predict which topics or formats might be more appealing to them in the future. By doing so, content marketers can create a content strategy that aligns with the predicted interests of their audience, ensuring each piece of content has a higher chance of resonating with its intended audience. 

The final step is the actual deployment of personalized content. This involves using AI to automate the distribution of content so that each user receives content that’s tailored to their interests. Personalization can extend beyond just the topics of the content to include personalized email subject lines, recommended articles on a website, or even customized social media messages. This level of personalization ensures each user feels uniquely addressed, significantly enhancing the user experience and deepening their engagement with the brand.

Content Optimization

AI tools for content marketing are revolutionizing content optimization. AI can suggest real-time improvements and predict future content performance. This approach enables data-driven decision-making, ensuring content not only reaches the intended audience, but also resonates with them. 

The first step of using AI for content optimization is leveraging tools that can analyze existing content and identify areas that need improvement. AI tools like Grammarly and Semrush can evaluate factors such as keyword usage, readability, and SEO effectiveness. By analyzing these elements, AI provides actionable insights into how content can be refined to better meet the audience’s needs and preferences. 

AI can play a crucial role in optimizing content for search engines. Tools like MarketMuse and BrightEdge can suggest optimal keywords, analyze the competitive landscape, and even recommend content structures that are more likely to rank higher in search results. This not only increases the visibility of the content, but also ensures it is aligned with what the audience is actively searching for. 

Next, consider AI for predictive analytics. AI’s predictive analytics capabilities are a game changer in content optimization. By analyzing patterns in user engagement and content performance, AI tools can forecast how new content might perform. This predictive insight allows content marketers to fine-tune their strategy, focusing on creating content that is more likely to succeed. Tools that offer AI-driven predictive analytics and analysis, such as Crayon and Cortex, can be particularly useful here, as they can provide forecasts based on vast datasets and sophisticated algorithms. 

Perhaps the most dynamic aspect of AI in content optimization is its ability to suggest real-time adjustments. This could range from tweaking the tone of an article to changing its distribution strategy based on current audience behavior. For example, AI tools for content marketing, like HubSpot Content Strategy and PaveAI, can monitor real-time user interactions and suggest immediate changes to maximize engagement and relevance. And tools like Grammarly can review your in-progress content and offer suggestions to strengthen it.

Automated Content Creation

AI-driven content creation tools can increase content production significantly. A notable example is the Washington Post’s use of its AI technology, Heliograf, to cover nearly 500 races on election day in 2016. However, it’s crucial to maintain a balance between AI-generated content and human creativity. 

First things first, it’s important to choose the right AI tools for content creation. The tools you choose should align with your specific content creation needs. For example, for news or data-driven content, tools that can process and convert data into readable formats (like Wordsmith) are ideal. For more creative content, look for AI that can generate drafts based on given themes or keywords (like ChatGPT or Articoolo). 

Next, think through the parameters and guidelines you’ll need to set to improve the likelihood that the AI tool will generate content that aligns with your needs. This involves defining the tone, style, and format you want the AI to follow. For example, with ChatGPT’s enterprise version, you can create custom GPTs for specific authors or about specific topics that are tailored to the guidelines you input for that specific GPT to follow. Providing detailed guidelines helps ensure the AI-generated content will align with your brand voice and content standards.  

Last but certainly not least, make sure an actual human is involved in your content creation process and content strategy planning. Human oversight is critical to make sure your content is accurate, aligned with your brand and goals, and, well, human. A person should review and edit every single piece of AI-generated content to add the human touch and maintain quality and authenticity. 

By leveraging these tools, content marketers can boost their content production without sacrificing quality. The key is to use AI as a tool to augment the content-creation process, allowing humans to focus on creativity and strategy while AI handles the heavy lifting of initial content generation. This synergy between AI capabilities and human creativity can lead to a more efficient, dynamic, and scalable content-creation process. 

Predictive Analysis

AI’s predictive capabilities are a game changer. The ability to anticipate and adapt to emerging trends is crucial for staying ahead in content marketing. 

First, you’ll need to gather data for the AI to analyze. The foundation of predictive analytics is robust historical data. Start by using tools like Google Analytics and BuzzSumo to collect data from your existing content, including user engagement metrics, conversion rates, and social media interactions. This data will serve as the learning material for AI algorithms. 

Next, select the right predictive analysis tool for you. It should be capable of processing your historical data and providing insight into potential future trends, user behavior, and content preferences. A couple tools to consider include Crimson Hexagon and IBM Watson. 

Then, get to work integrating predictive insights into your content planning. This might include identifying upcoming topics of interest, determining the best formats for future content, or predicting the best times to publish content for maximum engagement. A couple tools to consider are Sprout Social and MarketMuse. 

And keep in mind that once you’ve implemented AI for predictive analytics and insights, you’re not done. This is not a set-it-and-forget-it endeavor. Regularly update your AI models with new data and refine your strategies based on the latest insights. This will allow you to make sure your content strategy remains dynamic and aligned with evolving trends and audience preferences.

Efficiency in Content Distribution

Utilizing AI for content distribution can be incredibly effective if you have the right tools at your disposal. 

For example, Sprout Social’s publishing, response management, and productivity tools and analytics save one marketer at least 20 hours of work per month and helped him increase his company’s LinkedIn following by 60% over the course of a year. 

The first step is to gain a deep understanding of your audience’s behavior online. This includes knowing when they are most active, which platforms they frequent, and what kind of content they engage with. Hootsuite Insights can provide comprehensive analytics on audience behavior across multiple social platforms, and Sprout Social offers detailed reports on audience engagement and preferences. Then, AI tools (such as Tableau) can analyze this data to help you create a detailed profile of your audience’s online habits.  

You can also use AI to choose when and where to share your content. For example, Buffer and Sprout Social analyze past engagement data to suggest the optimal times for posting on social media, and CoSchedule uses AI to determine the best times to publish content for maximum reach and engagement. 

Once you’ve nailed down the “when” and “where” of sharing your content, you can then automate some of the distribution process. AI-driven tools can schedule and publish content across various social platforms at the most effective times, ensuring the consistent and timely delivery of your content. For example, Zapier can automate content posting across different web applications and platforms, while Sprout Social and Hootsuite allow for scheduling posts on multiple platforms and provide insights on content performance. 

By leveraging the right tools, content marketers can improve the efficiency and effectiveness of their content distribution. An AI-driven approach ensures that content not only reaches its intended audience, but does so at the most opportune times, maximizing visibility, engagement, and impact. 

Integrating AI Into Your Strategy

When integrating AI into your content strategy, it’s crucial to align tools with your objectives. Whether you’re aiming for improved relevance, efficiency, or personalization, selecting the right AI tools for content is key. 

And remember: This isn’t something you can just implement once and let it be. The evolving nature of AI models means they continually improve. That means you have to regularly reevaluate your AI tool stack and strategies to make sure your efforts are effective. 

The fusion of AI with human insight in content strategy is not just a technological upgrade; it’s a strategic revolution. By combining the analytical strengths of AI with human creativity, content creators can develop more resonant, dynamic, and successful strategies, navigating the complexities of the digital landscape with finesse and insight. 

This approach to AI-generated content marketing and website content AI is about finding the perfect synergy between technology and human creativity. With this balance, you can create content that sets new standards in engagement, relevance, and satisfaction. 

Want to learn more about how you can strengthen your digital marketing with AI?

Kelsey Raymond, COO

Kelsey Raymond is the COO of Intero Digital. Kelsey has over a decade of experience helping businesses achieve their growth goals through digital marketing strategies. She leads a team of experts in content marketing, PR, web design and development, Amazon marketing, social media, video, and graphic design.