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Everyone knows that AI is changing every industry. But a lot of marketers don’t see the full vision of how they could be using it. They’re getting comfortable using AI to generate draft text but not realizing the full potential of everything else AI could do for them.
That’s why it’s useful to rely on models created by industry experts to better understand the full potential of AI. Professor Thomas H. Davenport and Deloitte Consulting principal Rajeev Ronanki outline a full model for understanding the business applications of AI in this article in the Harvard Business Review.
The Davenport-Ronanki model outlining AI describes not just what kinds of business applications it has but also how to apply them. Many marketing leaders aren’t using this type of structured thinking to build their AI content strategies, so let’s dive in to give it a better look!
The Three Types of AI in the Davenport-Ronanki Model
Even though Davenport and Ronanki outlined their model in 2018, its validity is proven by how much it’s still relevant even after all the recent advances in AI we’ve seen. Here are the three types of AI they describe:
Process Automation
Process automation AI, also known as Robotic Process Automation (RPA), refers to the automation of digital and physical tasks, primarily back-office administrative and financial activities, using software robots or AI workers. It differs from the other types of AI—cognitive insights and cognitive engagement—because it focuses on executing tasks and processes rather than analyzing data or interacting with users.
RPA is especially useful because of its immediate impact on efficiency and cost reduction, as it can quickly take over repetitive, rule-based tasks that don’t require complex decision-making or learning. It’s the least expensive and easiest to implement among the AI types discussed in the article and typically brings a quick and high return on investment. However, it’s also noted as the least “smart” in terms of cognitive abilities, as these systems are initially not programmed to learn and improve, although they are gradually being enhanced with more intelligence.
Examples of how companies use process automation AI for content marketing include:
- SEO Management: AI can automatically update meta-tags, track and fix broken links, and adjust content to align with the latest SEO trends and analytics insights. Depending on your needs, these boring, repetitive tasks can save you hours while improving your content’s performance.
- Automated Content Distribution: AI can automate the process of content distribution across multiple platforms. It can schedule and post content on social media, update website content, and ensure that new articles or posts are shared with relevant stakeholders and syndicated on appropriate channels at optimal times.
- Dynamic Content Optimization: RPA systems can continuously A/B test different headlines, images, and calls to action in content pieces to determine which combinations perform the best, automatically implementing the most successful elements in real time to improve engagement and conversion rates.
These applications are particularly well-suited to working across multiple back-end systems, allowing companies to streamline processes that are essential to their content creation and distribution.
Cognitive Insight
Cognitive insight AI refers to applications that employ algorithms to parse large data sets and identify patterns, providing interpretations that can be used for more accurate predictions, personalized experiences, and strategic decision-making. This type of AI differs from process automation in that it goes beyond executing pre-programmed tasks to actively learning and improving from data over time, often using machine learning or deep learning.
In content marketing, companies can harness cognitive insight AI in several ways:
- Predictive Analytics for Content Trends: Cognitive insight AI can analyze consumer behavior and social media trends to predict upcoming content trends. This helps you create content that aligns with future interests, staying ahead of the curve.
- Sentiment Analysis: AI tools can assess social media and other content for sentiment, providing insights into how audiences feel about a brand or topic. This can inform the tone and direction of new marketing content to better resonate with the audience.
- Content Performance Forecasting: By analyzing historical content performance data, cognitive insight AI can forecast the potential success of future content pieces, helping you to invest efforts in the most promising topics and formats.
These cognitive insight applications enable content marketers to leverage deep data-driven insights, enhancing the strategic aspects of content creation and distribution for more targeted, relevant, and effective marketing efforts.
Cognitive Engagement
Cognitive engagement AI involves technologies that interact with users in a natural, human-like way. This type differs from both process automation and cognitive insight because it focuses on direct interaction with customers or employees, providing services like answering questions, offering recommendations, or providing other forms of assistance.
Companies can use cognitive engagement AI to improve their content marketing in a few ways:
- Chatbots and Virtual Assistants: Cognitive engagement AI can be used to deploy AI-powered chatbots on websites and social media platforms to provide instant, interactive communication with customers. These can deliver personalized content recommendations, answer FAQs, or guide users through the marketing funnel.
- Interactive Content: AI can be used to create quizzes, polls, or interactive videos that adapt to user inputs, which can increase engagement and time spent with the brand while also collecting user preferences and feedback.
- Customer Feedback Analysis: AI can analyze customer feedback across various channels to understand sentiments, extract key themes, and identify content gaps that need to be filled to improve customer satisfaction and engagement.
Cognitive engagement AI tools help brands foster a more personalized and interactive relationship with their audience, enhancing the customer experience and improving the effectiveness of content marketing strategies.
How to Use Process Automation AI for Content Creation
Process automation AI can significantly streamline SEO management by automating repetitive and labor-intensive tasks. You can use that technology to improve your content optimization and distribution, saving you time and making sure you get consistent results. Here are a few ways you can use it:
SEO Management
With process automation AI, you can manage the SEO side of your content production with a lot less hassle. For example, automation can conduct keyword research at scale. By crawling through vast datasets, AI can identify trending keywords, long-tail phrases, and semantic variations that are relevant to your niche.
Similarly, AI-powered tools can automate on-page SEO tasks. They can scan your website’s content to ensure that it aligns with best practices for keyword density, meta tags, and header tags. They can also suggest improvements and even implement them on CMS platforms that support automation.
Another critical area is backlink analysis. AI can continuously monitor your backlink profile, alerting you to any changes, such as new backlinks or the loss of existing ones, and can assess the quality of these links to manage your link-building efforts effectively.
Lastly, process automation tools can track your rankings across different search engines and generate detailed reports, highlighting progress and identifying areas that require attention, thus allowing you to make data-driven decisions quickly.
By automating these processes, SEO professionals can focus on strategic planning and creative aspects of SEO that require human insight, thus improving overall SEO performance and efficiency.
Content Distribution
Content distribution is one of the most powerful applications of process automation AI. That’s because content distribution is one of the most important parts of the content creation process. Previously, we’ve been known to make some pretty bold statements about how much time and money you should spend on content distribution. But what if we’re wrong?
Just look at this chart below.
Do you really need to be spending 75% of your budget on content distribution?
Maybe not.
That’s because process automation AI can significantly reduce the amount of time (and, therefore, budget) you need to spend distributing your content. Starting with content scheduling, AI tools can automatically post content at the optimal times for engagement across different platforms, learning from past performance data to improve timing strategies. These tools can also dynamically adjust posting schedules based on audience behavior changes or trending topics.
For multi-channel distribution, AI can identify the best platforms for each piece of content based on the target audience and content format. It can then auto-format and publish content across these channels, whether it be social media, blogs, email newsletters, or other digital outlets, ensuring consistency and maximizing reach.
Personalization is another area where AI shines. It can segment audiences and distribute personalized content tailored to the interests and behaviors of different user groups. This approach increases relevance and engagement, driving better campaign results.
In terms of performance tracking, AI can continuously monitor engagement metrics and interactions across all distribution channels. It can provide insights into what content performs best, where, and why, enabling you to fine-tune your content strategy.
Lastly, AI-powered tools can manage and optimize paid advertising campaigns, adjusting bids and real-time targeting based on performance data, ensuring the best ROI for content promotion budgets.
By automating these aspects of content distribution, you can ensure your content reaches the right audience at the right time, with analytics that help refine strategies for maximum impact.
Dynamic Content Optimization
Dynamic content optimization using process automation AI is akin to having a diligent, tireless team working around the clock to ensure your content remains fresh, relevant, and engaging. It’s an ongoing process of testing and tailoring content that can dramatically enhance user experience and conversion rates.
With AI, A/B testing becomes a continuous and automated process. Different headlines, images, and calls to action are persistently trialed to identify which combinations resonate best with your audience. But AI goes beyond mere experimentation; it applies the winning formulas in real time, adapting content dynamically to user responses and behaviors.
You could even experiment with using it to diversify your content mix. Use AI to mix up the formats of your content and optimize for which ones perform the best or reframe existing content from a “definition” type of post to a guide.
Without AI, the best you could hope for would be a daily update according to what’s performing best—and doing it daily is already pretty extravagant. But AI can update your content continuously while your team sleeps.
Harnessing Cognitive Insight AI for Data-Driven Content Marketing
Cognitive insight AI is reshaping content marketing by enabling data-driven strategies that can predict trends, understand audience sentiment, and personalize the content experience. This advanced form of AI moves beyond task automation to leverage machine learning and deep learning, analyzing large data sets to uncover patterns and make intelligent predictions. Here are some transformative ways to use it:
Predictive Trend Analysis
Utilize cognitive insight AI to conduct predictive trend analysis, which helps in forecasting future content directions. By analyzing current and historical data, AI tools can predict which topics will become popular. This allows content creators to stay ahead of the curve, developing and positioning content that meets the audience’s needs just as the topic gains traction.
Enhanced Sentiment Analysis
With cognitive insight AI, sentiment analysis is more sophisticated than ever. It can comb through social media posts, reviews, and other user-generated content to gauge public sentiment toward your brand or products. This insight is critical in tailoring content that resonates on an emotional level, ensuring that messaging aligns with audience attitudes and perceptions.
Content Performance Prediction
AI-powered content performance prediction can analyze past content engagement and conversion data to forecast the future performance of content campaigns. These insights help marketers prioritize content types and topics that are likely to drive engagement and conversions, ensuring that resources are allocated to the most impactful content.
Audience Segmentation for Personalization
Cognitive insight AI can segment audiences based on a myriad of factors, including behavior, preferences, and engagement history. This segmentation is vital for crafting personalized content strategies that speak directly to different audience subsets, vastly improving the relevance and effectiveness of marketing campaigns.
Strategic Competitive Analysis
Deploy cognitive insight AI for strategic competitive analysis to stay ahead in the market. By monitoring and evaluating competitors’ content strategies, AI tools can provide actionable insights that inform your content approach, identify market gaps, and help differentiate your brand.
Integrating cognitive insights into your content marketing strategy means embracing a predictive and adaptive approach. It allows for a nuanced understanding of your audience, the competitive landscape, and the performance of your content, which, in turn, enables a more targeted and successful content marketing strategy. With cognitive insight AI, content marketers can transform vast data into strategic insights, ensuring that every piece of content is not only well-crafted but also well-informed.
Elevating Content Interactions with Cognitive Engagement AI
Cognitive engagement AI transforms the way brands interact with their audiences, offering personalized and conversational experiences. Unlike process automation or cognitive insight, this AI type focuses on understanding and communicating with users, enhancing customer service and engagement through direct interaction. Here’s how content marketers can leverage cognitive engagement AI to elevate their strategies:
Conversational Chatbots and Virtual Assistants
Incorporate AI-driven chatbots and virtual assistants on digital platforms to provide real-time, personalized user interactions. These AI tools can engage with customers by answering questions, offering customized content suggestions, and guiding them through the buyer’s journey. By simulating human conversation, they provide a seamless and interactive brand experience that can significantly boost engagement and conversion rates.
Interactive Content for Enhanced Engagement
Use AI to create dynamic and interactive content formats such as quizzes, polls, or videos that respond to user inputs. These engaging content pieces not only captivate users but also gather valuable data on preferences and behaviors, informing future content creation and offering insights into audience interests.
Advanced Customer Feedback Interpretation
Employ AI tools to parse through and interpret customer feedback across various channels. Cognitive engagement AI can dissect large volumes of data to discern sentiment, extract significant themes, and pinpoint areas for content improvement. This analysis can guide the development of more effective content strategies and ensure that the content resonates with the audience.
Real-Time User Assistance and Support
Integrate AI-driven systems that offer instant assistance and support to users navigating your content. Whether it’s helping with content discovery or providing answers to content-related inquiries, cognitive engagement AI can enhance the user experience, making it more interactive and helpful.
By embracing cognitive engagement AI, content marketers can create a more personalized, responsive, and interactive content ecosystem. This approach not only delights users but also builds a foundation for long-term relationships. Cognitive engagement AI stands as a testament to the power of personalized interaction in the digital age, ensuring that each user’s journey with your content is as engaging as it is unique.
How to Start Your AI Journey
AI in content marketing transcends mere text generation, opening a new frontier of personalized, efficient, and strategic marketing practices. By harnessing process automation AI, marketers can save time on mundane tasks, while cognitive insight and engagement AIs provide deeper audience understanding and interactive experiences.
This guide illuminates the path for integrating AI into your content marketing, ensuring you can stay ahead in a rapidly evolving digital landscape. As AI technology progresses, those who leverage its full spectrum will find themselves at the vanguard of engaging, impactful content strategies that resonate deeply with their audience. Learn more about what AI has in store for marketers.
