AI Explored: Creating an AI-Driven Content Marketing Workflow
Host: Michael Stelzner, Social Media Examiner
Guest: Keith Mooring, Founder and CEO of L2Digital
Release Date: December 17, 2024
Introduction
In this episode of AI Explored, Michael Stelzner welcomes Keith Mooring, the founder and CEO of L2Digital, to discuss the intricacies of creating an AI-driven content marketing workflow. Aimed at marketers, creators, and business owners, the conversation delves deep into leveraging AI to automate and enhance content marketing processes, making them more efficient and scalable.
Guest Background and Journey into AI
Keith Mooring shares his unconventional path to the world of AI and marketing automation:
"[...] followed by working at PR 2020 and eventually diving into the technical side of marketing, embracing automations, integrations, web development, and data analytics."
— Keith Mooring [02:25]
Starting in mortgage refinancing and PR, Keith pivoted towards marketing technology, finding his passion in automation and data processing. The turning point came in February 2020 when he launched his own business amidst the emerging challenges of the COVID-19 pandemic. Faced with overwhelming tasks and limited resources, the release of ChatGPT by OpenAI became a game-changer for him.
"ChatGPT changed the game because now I have that intern-level assistant I needed to get a lot of time-consuming projects done quickly."
— Keith Mooring [06:16]
Understanding AI Automation: Triggers, Operations, and Outputs
Keith introduces the foundational concepts of AI automation using tools like Make.com (formerly Integromat):
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Triggers: Events that initiate the automation process.
- Time-Based Triggers: Automations run at set intervals (e.g., every hour).
- Event-Based Triggers: Specific actions (e.g., a form submission) that start the workflow.
"The trigger is the thing that kickstarts the automation... like a lead fills out a lead form."
— Keith Mooring [10:13] -
Operations: The actions performed on the data received from the triggers.
- Processing, transforming, and integrating data through multiple steps.
"Operations are just functions where information goes in, gets processed, and something comes out the other end."
— Keith Mooring [12:23] -
Outputs: The final results of the automation, such as creating documents or assigning tasks.
"The output is the final step where the information goes after the automation runs."
— Keith Mooring [13:18]
Building an AI-Driven Content Marketing Workflow
Keith outlines a step-by-step approach to automating content creation, using a newsletter as a primary example:
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Identifying a Repetitive Process:
- Example: Writing a weekly newsletter by summarizing recent articles.
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Breaking Down the Process:
- Read and scrape the content of the chosen article.
- Summarize the article and extract key quotes using AI.
- Draft an outline based on the summary and previous content.
- Conduct additional research by referencing past related posts.
- Draft the final article and save it for editorial review.
"The key is to think through everything in a very logical, step-by-step way."
— Keith Mooring [13:41] -
Implementing Automation with Make.com:
- Trigger: Adding a new row with the article link to a Google Sheet.
- Operations: Scraping the article, summarizing content, extracting quotes, drafting outlines, and researching past content.
- Output: Creating a Google Doc with the drafted article and assigning it to an editor via a project management tool like ClickUp or Asana.
"Just by adding a row to a Google Sheet, a minute later I can have the draft of a blog post in my inbox with a link to it and assign that task to my content editor."
— Keith Mooring [09:03]
Leveraging Conditional Logic and Structured Data
Keith emphasizes the importance of conditional logic and structured data (JSON) in refining automations:
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Conditional Logic:
- Directing workflows based on specific criteria (e.g., topic types like social media marketing vs. generative AI).
"If the topic is social media marketing, maybe it sends it down one path than it would if the topic was generative AI."
— Keith Mooring [24:25] -
Structured Data (JSON Objects):
- Ensuring outputs are organized and easily usable within subsequent automation steps.
"By sending back a JSON object with summary, quote one, quote two, it allows me to grab those specific pieces of information later."
— Keith Mooring [35:03]
Integrating AI Tools: ChatGPT and Claude
Keith discusses the seamless integration of AI tools into the automation workflow:
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Custom GPTs:
- Creating tailored AI models using OpenAI's Assistant to perform specific tasks like summarizing articles or optimizing content based on SEO guidelines.
"I have an operation that is an SEO expert... it optimizes my article according to the experts."
— Keith Mooring [32:48] -
Prompt Engineering:
- Crafting precise prompts to ensure AI outputs are clean and structured, avoiding extraneous information.
"You have to be very, very specific in terms of what the output needs to be... like summary: [text], quote1: [text]."
— Keith Mooring [29:47]
Advanced Automation Features: Email Triggers
Exploring more sophisticated triggers, Keith explains how email can serve as a powerful initiation point for automations:
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Dedicated Email for Tasks:
- Setting up a specific email address monitored by Make.com to receive task commands.
"I created a Gmail account specifically for this project... I send an email with the subject line 'write me a blog post' and details in the body."
— Keith Mooring [38:50] -
Automated Task Creation:
- Parsing email content to extract relevant information and automatically creating tasks in project management tools with all necessary details and links.
"The automation can create the task automatically for me, assigning it to the right person with all the necessary information."
— Keith Mooring [41:09]
Time Investment and Learning Curve
Addressing potential concerns about the complexity and time required to set up such automations, Keith provides insights:
"Setting up one of these things could take a matter of 10 to 15 minutes... the real trick is going to do the work upfront to find the process and think through how this is going to work technically."
— Keith Mooring [42:06]
He highlights that while there is an initial learning curve, especially with tools like Make.com, the long-term benefits in efficiency and scalability are substantial. Additionally, once a basic automation is established, it can be cloned and adjusted for various other tasks, streamlining the setup of multiple workflows.
Conclusion and Final Thoughts
Michael Stelzner wraps up the discussion by encouraging listeners to explore AI-driven workflows, emphasizing the transformative potential of automations in content marketing. Keith Mooring reiterates the importance of thoughtful planning and precise prompt engineering to fully harness AI's capabilities.
"Once you set one up, you can literally clone it and then just tweak from there... it's so much fun that you may not want to stop."
— Keith Mooring [43:21]
Listeners are invited to connect with Keith on LinkedIn or visit L2Digital's website for further engagement and support in implementing AI-driven marketing strategies.
Key Takeaways
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Automation Fundamentals: Understanding triggers, operations, and outputs is crucial for building effective AI-driven workflows.
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Practical Implementation: Starting with repetitive tasks, like newsletter creation, can showcase immediate benefits of automation.
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AI Integration: Leveraging tools like ChatGPT and Claude with structured prompts enhances the quality and consistency of automated outputs.
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Advanced Features: Utilizing email triggers and conditional logic can further refine and personalize automation processes.
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Efficiency and Scalability: Initial time investment in setting up automations pays off through increased efficiency, consistency, and the ability to scale content marketing efforts effortlessly.
For more insights and detailed show notes, visit Social Media Examiner Podcast.