Social Media Audit GPT: How I Built It & How To Create Your Own GPT for Work or Learning.

In integrating AI into my courses, I’ve had experience using Custom GPTs. They can be very beneficial over broad AI use as they focus specifically on a single task or project to help the user – whether student, professor, or professional. For example, I have used JobsGPT in a previous blog post as a way to help predict how AI will impact the skills marketers need in the future so that I can adjust my course material.

I was also recently inspired by an article in Chronicle of Higher Ed. In “Teaching: Can AI actually help students write authentically?” Beth McMurtrie shares how Jeanne Beatrix Law, director of composition at Kennesaw State created a custom GPT Writing Guide Assistant. She found a way to engage students with AI to teach critical thinking and the writing process through prompting versus having AI write for students.

I also realize my students need to gain experience working with AI such as custom GPTs and agents to prepare for today’s marketing jobs. The latest CMO survey reports use of generative AI in marketing increased by 116% since 2024 – now 15% of marketing activities. As a hopeful sign, the same survey reports companies are still growing their marketing teams – 5.3% last year and predicted 5.0% in 2025.

My Social Media Audit GPT. Available now – an AI assisted social media strategy tool.

 

The Primary Goal of My GPT

My goal in creating the Social Media Audit GPT was to provide students with a learning assignment to teach step-by-step an important course concept. Social media audits are an amazing strategic tool but students often struggle to understand them completely – even with new examples in the 4th edition of my Social Media Strategy book.

This custom GPT takes students and professionals through the process of completing a social media audit through prompting, and you can ask questions at any time along the way. It also has the benefit of focusing on source materials to ensure accuracy.

To create the Social Media Audit GPT I gave it an article I wrote on this blog last year detailing the process for conducting a social media audit with a social media audit template. I see the custom GPT as a great support to in-person instruction giving each student access to how I would tutor them in this key concept 24/7. For those using my Social Media Strategy text in classes, this is a great supplement to support your instruction.

Social Media Audit Template To Improve Social Media Marketing Strategy.
I trained the GPT on the Social Media Audit template from my Social Media Strategy book.

Secondary Goals of My GPT

A secondary goal was to show students how to use AI responsibly to empower their learning, not harm it. Creating a custom GPT is a key demonstration of AI integration and teaching AI literacy versus AI bans labeling all AI use as cheating. This helps teach responsible AI use for students tempted to use AI to complete assignments.

Another secondary goal is to teach students how to work with AI as a partner in developing marketing strategies. The GPT is not a replacement for those creating a social media strategy for an employer or client. The AI agent doesn’t complete the audit.

I instructed the GPT to not collect data for the user it to prompt them to formulate their own insights. The real value of a social media audit is getting into each social media platform and seeing what’s happening with your own eyes. I built the AI as a strategy development assistant demonstrating how students or professionals can use custom GPTs and AI agents in their future or current marketing careers.

How I Created The Custom GPT

I had a working model of this Social Media Audit GPT several weeks ago as a Microsoft Copilot Agent (AI-powered assistant), but it was stuck inside my institution – you can only share with individuals or groups in your organization/company. Google Gemini Gems (custom AI experts), and Anthropic Claude Projects (curated sets of knowledge) have similar limitations in that your custom AI agent, gem, or project can only be shared internally within your organization.

Only OpenAI’s custom GPTs can be published on the open web and mobile app to be shared publicly. Anyone can use Custom GPTs with a free ChatGPT account, but to create a custom GPT you need at least ChatGPT Pro (at $20 a month). Before this, all my AI use was limited to only models and tools that I could access for free (so my students wouldn’t have to pay).

Yet with custom GPTs, I was in the opposite situation. As Marc Watkins explained recently, while OpenAI and Google are giving away premium subscriptions to students, they have not extended that offer to professors. I finally secured some funding to purchase a ChatGPT Pro account.

One thing I like about my blog is I own it and control what is published there. With this GPT I’m relying on OpenAI to host for me. If I downgrade to a free account, I can’t access it. Thus, I’m locked into paying $20 a month to manage and update. OpenAI, if you’re reading, please extend the free Pro account to educators, not just students.

GPTs Are Essentially Good Prompts

What is a custom GPT? OpenAI says “a version of ChatGPT for a specific purpose.” MIT Sloan explains, “Custom GPTs are helpful AI tools tailored for specific domains or contexts. GPTs differ from standard chats through ChatGPT due to custom instructions and the ability to keep a knowledge base in addition to what ChatGPT has been trained on. This allows users to create a custom GPT to address a specific need that might be hard for ChatGPT to achieve on its own. The process … requires no code, and involves using specific prompts and your own data to provide insights into a particular field.”

AI Prompt Framework Template with 1. Task/Goal 2. AI Persona 3. AI Audience 4. AI Task 5. AI Data 6. Evaluate Results.
AI Prompt Framework Template for writing good prompts – what you need to create a GPT.

Creating a custom GPT is essentially writing a good, detailed prompt that users of the GPT will begin a chat from that background and knowledge. In creating my Social Media Audit GPT I wrote a long prompt explaining what I wanted it to do following my AI Prompt Framework of Task/Goal, Persona, Audience, Task, Data, and Results.

In the image below I marked up my GPT prompt to sections of the AI Prompt Framework. The text on the top was my original building the Copilot Agent and adjustments. The text in the bottom right is the adjustments I made in custom GPT.

Custom GPT and Copilot Agent prompts to create Social Media Audit GPT.

Test Your GPT To Make Changes

An important part of this process is to test your GPT as a typical user to see how well it performs. If you find something wrong simply tell the GPT what you like and what needs to change. You can test it in a Preview column next to where you instruct the GPT.

One of the first adjustments I made was to clarify that I wanted the GPT to have the user visit each social platform and report results. An earlier version searched the web and reported back its analysis. I tested the social audit GPT with a running brand (see below).

I like to run so I chose to test Social Media Audit GPT with Saucony running shoes and apparel

Once you’ve tested the GPT you’re ready to publish! Click the “Create” button in the top right. Then click “Share” at the top right. In that pop-up screen select “Only me,” “Anyone with the link.” or “GPT Store access.” After choosing GPT Store your GPT will be available at https://chatgpt.com/gpts for anyone with a ChatGPT account to access. Search by name or click “My GPTs.”

The custom GPT you make is only limited by your discipline knowledge, the data you provide, and the strength of your prompt.

Have you explored creating a Copilot Agent, Gemini Gem, or Open AI Customer GPT? How might you use this in your teaching for professional practice?

Update: An early limitations of Gems was that you could not share them. That has been updated. Follow this same process to create a Gemini Gem if you have Google Gemini access versus ChatGPT.

Please try the Social Media Audit GPT and share any feedback you have. A great feature of custom GPTs is you can revise and update.

This Was Human Created Content!

AI Turned My Academic Journal Article Into An Engaging Podcast For Social Media Pros In Minutes with Google’s NotebookLM.

 I recently published academic research in the Quarterly Review of Business Disciplines with Michael Coolsen titled, “Engagement on Twitter: Connecting Consumer Social Media Gratifications and Forms of Interactivity to Brand Goals as Model for Social Media Engagement.” Exciting right?

If you’re a research geek or academic maybe. A social media manager? No way. Yet, I know the findings, specifically our Brand Consumer Goal Model for Social Media Engagement is very exciting for social media pros! So I wanted to write this blog post.

But, as you can tell by the title, an academic audience, and a professional audience are very different. Taking a complicated 25-page academic research article and translating it into a practical and concise professional blog post could take me hours.

I’ve been meaning to experiment with Google’s new AI generator tool NotebookLM so I thought I would try it. Thus, this blog post is about our research on a social media engagement framework and how I used AI to streamline my process to create it. As a bonus, I got a podcast out of it!

My co-author and I did the hard work of the research. I was okay with an AI assistant helping translate it into different media for different audiences. Click for an AI Task Framework.

Using NotebookLM.

Our study was on types of content that generate engagement on Twitter, but the real value was a proposed model for engagement. So before uploading any of the research into the AI tool, I condensed it to just the theoretical and managerial implications sections. Then I added a title, the journal citation, and saved it as a PDF.

NotebookLM uses Gemini 1.5 Pro. Google describes it as a virtual research assistant. Think of it as an AI tool to help you explore and take notes about a source or sources that you upload. Each project you work on is saved in a Notebook that you title. I titled mine “Brand Consumer Goal Model for Social Media Engagement.”

Whatever you upload NotebookLM becomes an expert on that information. It uses your sources to answer your questions or complete your requests. It responds with citations, showing you original quotes from your sources. Google says that your data is not used to train NotebookLM, so sensitive information stays private (I would still double-check before uploading).

Source files accepted include Google Docs, Google Slides, PDF, Text files, Web URLs, Copy-pasted text, YouTube URLs of public videos, and Audio files. Each source can contain up to 500,000 words, or up to 200MB for uploaded files. Each notebook can contain up to 50 sources. If you add that up NotebookLM’s context window is huge compared to other models. ChatGPT 4o’s context window is roughly 96,000 words.

When you upload a source to NotebookLM, it instantly creates an overview that summarizes all sources, pulls out key topics, and suggests questions to ask. It also has a set of standard documents you can create such as an FAQ, Study Guide, Table of Contents, Timeline, or Briefing Doc.

You can also ask it to create something else. I asked it to write a blog post about the findings of our research. You will see that below. Yet, the most impressive feature is the Audio Overview. This generates an audio file of two podcast hosts explaining your source or sources in the Notebook.

The NotebookLM dashboard gives you a variety of options to interact with your sources.

Using Audio Overviews.

There are no options for the Audio Overview so you get what it creates. But what it creates is amazing! My jaw literally dropped when I heard it. And it will give you slightly different results each time you run it.

I noticed things missing in the first audio overview such as the journal and article title and the authors’ names. I did figure out how to make adjustments by modifying my source document. Through five rounds of modifying my source document, I was able to get that information in and more.

Sometimes overviews aren’t 100% accurate. It says, “NotebookLM may still sometimes give inaccurate responses, so you may want to confirm any facts independently.” In our research article we give a hypothetical example of a running shoe brand following our model. It was not real. But in one version of Audio Overviews, the podcast hosts talk as if the company did what we said and got real results that we measured.

I was impressed that in other versions it didn’t use our example and applied the model to new ones. One time it used an organic tea company and another time a sustainable clothing brand. On the fifth attempt it even built in a commercial break for the “podcast.” This last version gave my running shoe example and added its own about a sustainable activewear brand.

What’s really interesting about the last version is that it pulled in other general knowledge about social media strategy and applied it to the new information of our study. At the end, the hosts bring up how our engagement model will help know what to say but that social media managers still need to customize the content to be appropriate for each social platform. That’s a social media best practice but not something we mention in the article.

The Audio Overview Podcast NotebookLM Created.

 

It’s amazing these podcast hosts discussed our research and explained it so well for social pros. What’s more amazing is that they are not real people! Yet NotebookLM did more. Below is the blog post it wrote. It included our diagram of the model, but had trouble getting it right. So, I replaced the image with one I created from our article.

Brand Consumer Goal Model for Social Media Engagement.

This post examines a model for social media engagement based on an October 2024 study in the Quarterly Review of Business Disciplines. “Engagement on Twitter: Connecting Consumer Social Media Gratifications and Forms of Interactivity to Brand Goals as Model for Social Media Engagement,” published by Keith Quesenberry and Mike Coolsen.

The Brand Consumer Goal Model for Social Media Engagement is a framework to help social pros create more effective plans by aligning brand goals with consumer goals. It emphasizes understanding the motivations behind consumer engagement and tailoring content accordingly.

How the Model Works

The model outlines three key brand goals:

  • Building brand community (Reach): This goal focuses on expanding the brand’s audience and increasing awareness.
  • Building brand-consumer relationships (Response): This goal aims to foster brand interaction and engagement.
  • Building brand-consumer bonds (Recognition): This goal seeks to create brand emotional connections and loyalty.

Each brand goal is associated with a corresponding consumer goal and form of social media engagement as seen in the graphic below. Consumers can manage people’s impressions and persuade others by sharing certain brand posts. They can gain information about a brand with other types of brand content for deliberation. Then they can bond with others regulating their emotions in evaluating brand posts with other fans.

Brand Consumer Goal Model for Social Media Engagement Template
Click on the graphic to download this model for social media engagement.

Here is an example

  • A sneaker brand launches a running shoe and aims to build brand community (reach) creating content that appeals to runners’ desire for impression management and persuasion. This could be sharing inspirational stories about runners breaking records encouraging retweets and brand visibility.
  • Once awareness is established, the brand could shift its focus to building relationships (response) by providing information about the shoe’s features and benefits, appealing to consumers’ information acquisition goals, and prompting replies and comments seeking further details.
  • Finally, the brand can foster brand bonds (recognition) by sharing content that resonates with runners’ social bonding and emotion regulation needs, such as posts about the challenges and rewards of training, which encourage likes and emotional connections.

Key Insights from the Study

The study found that simply using popular content types like videos or photos is not enough to guarantee success on social media. The message delivered with the content is crucial.

Marketers need to consider:

  • The target audience’s motivations for using social media
  • Buying cycle stage (awareness, consideration, purchase, loyalty)
  • Desired word-of-mouth function (sharing, deliberation, evaluation)

The Brand Consumer Goal Model for Social Media Engagement offers a strategic framework for developing effective social media campaigns. By understanding the motivations behind consumer behavior and aligning content with both brand and consumer goals, marketers can achieve better results and build stronger relationships with their target audience.

I hope you found this look at NotebookLM and the insights from our social media research helpful. In what ways do you think NotebookLM can help in your job? In what ways can the insights from the Brand Consumer Engagement Model improve your social media content strategy?

NotebookLM Could be a Great Study Tool for Students.

NotebookLM could be a great tool for student learning if used as a study guide, reinforcement, or tutor. It would have a negative impact if used to simply replace reading and listening in the first place. What’s missed when you use AI in the wrong way is depicted in the graphic below. It is from a previous post on the importance of subject matter expertise when using AI

Personally, I was fine using this tool in this way. My co-author and I did the hard work of the research. This AI assistant simply helped us translate it into different media for different audiences.

This graphic shows that in stages of learning you go through attention, encoding, storage, and retrieval. You need your brain to learn this process not just use AI for the process.
Click the image for a downloadable PDF of this graphic.

Half of This Content Was Human Created!

UPDATE: Customize Audio Overviews Before Processing.

Google released a new version of NotebookLX where you can customize the Audio Overview before processing. I was very impressed with this feature. For example, I had another academic article published about a new no tech policy in the classroom that I implemented after COVID restrictions were released.

I uploaded this academic article and before processing I Customized the Audio Overview telling NotebookXL that my target audience was college students distracted by technology in the classroom and to keep the overview shorter for their short attention spans. Here is the result:

 

UPDATE: Interrupt Audio Overview To Ask Questions With Voice.

With the latest release Google has added the ability to engage directly with the AI hosts during an Audio Overview. I’ve tried it and it works creepily well.

I created an Audio Overview of my student professional blogging assignment for personal branding. In the beginning the hosts tell students to write about their unique skills. I clicked a “Join” button and the host said, “Looks like someone wants to talk.” I asked, “How do you know your unique skills?” They said “good question,” gave good tips and continued with the main subject.

Later I interrupted and asked, “Can you summarize what you have covered so far?” They said sure, gave a nice summary and then picked back up where they left off. Finally, I asked about being nervous putting a blog out in public. The hosts reassured me that I don’t have to be perfect. People value honesty and personality. It’s not about perfection.

For a look at my next blog post in AI see “Beyond AI Bans: An End of Year AI Integration Pep Talk for Educators.”