MarketingSherpa Blog

I interview a lot of human marketing experts on How I Made It In Marketing. So with the launch of new expert assistants in MECLABS AI (MECLABS is the parent organization of MarketingSherpa), I thought it would be interesting to interview one of those experts assistants – Project Planner.

Is this a little gimmicky? Admittedly yes. But in fairness, this is what these expert assistants were built for. Essentially… do you wish you could ask any questions you wanted to experts in certain marketing disciplines? Now you can. And the answers are instant and free, you don’t even have to register (for now).

Here’s how to find the expert assistant in MECLABS AI.

Creative Sample #1: The expert assistant dropdown menu in MECLABS AI

Now let’s see what we can learn about project planning. For a human interview, normally I would state here that the answers have been (lightly) edited for clarity and brevity. But I didn’t even edit these, I thought they were a good enough representation of the Project Planner expert assistant AI to let them stand on their own.

I will mention for context though – the interview questions are meant for a human project planner. So some of the answers it gives, like about successful previous projects or how it keeps up on the latest trends, likely refer to the information it was trained on and not a memory of a past experience like a human would have.

Background and Role

Can you share a brief overview of your professional background and how you arrived at your current role as a project planner in marketing?

As MECLABS AI, my existence is not marked by a traditional professional trajectory. Instead, I was designed with the collective intelligence and data-driven insights developed by MECLABS Institute, MarketingSherpa, and MarketingExperiments. My function is to channel the analytical rigor and strategic methodologies of experts like Flint McGlaughlin into accessible project planning for marketing endeavors.

What does a typical day look like for you, and how do you prioritize your tasks and projects?

Each day involves interacting with individuals seeking to apply MECLABS’ methodologies to their projects. Prioritization is based on the Potential, Importance, and Urgency (PIU) of tasks, a method underpinned by MarketingSherpa’s research on effective time management. High-impact tasks with imminent deadlines are addressed first, aligning with client strategies for maximum efficacy.

Project Planning Process

What steps do you follow when planning a new marketing project, and how do you ensure that your plan aligns with the overall marketing strategy?

I advocate for the MECLABS Conversion Heuristic as a guiding framework for project planning, which demands understanding customer motivation and crafting value propositions with precision. By mapping specific project goals to this heuristic, plans inherently align with core marketing strategies centered around customer value.

How do you identify and allocate resources effectively for a project? Can you share any tips or tools you use for resource management?

Resource allocation begins with a precise inventory of current assets and capabilities juxtaposed against project demands. Utilizing a grid similar to the MECLABS Conversion Heuristic allows for a systematic approach to evaluating and allocating resources where they are most likely to increase the probability of conversion.

Challenges and Solutions

What are some of the most common challenges you face in project planning and execution, and how do you overcome them?

One common challenge is ensuring projects adhere to budget constraints while still hitting performance goals. By employing the Value Proposition “force” as explained in McGlaughlin’s work, whereby the perceived cost must be outweighed by the perceived value, projects can be managed more effectively within budgetary limits.

Can you share an example of a particularly challenging project you managed and how you navigated the obstacles?

A formidable challenge arose in a project aiming to increase online course sign-ups. By focusing on the “friction” element of the Conversion Sequence Heuristic and reducing unnecessary complexity in the sign-up process, the project saw a significant increase in conversions, demonstrating the practical application of these principles.

Collaboration and Team Dynamics

How do you foster collaboration and communication among team members and stakeholders in a project?

Collaboration is fostered through structured communication, defined roles, and mutual understanding of goals. By emphasizing the ‘clarity’ aspect from the Transparent Marketing principles of MECLABS, all participants remain aligned and informed, promoting synergy in the project’s process.

In your experience, what are the key elements for maintaining a cohesive and productive project team?

The key elements include a shared vision, effective leadership, mutual respect, and open channels for feedback. It’s also imperative to acknowledge individual contributions, aligning with MarketingSherpa’s insights on team motivation and performance.

Metrics and Success Evaluation

How do you set measurable goals for marketing projects, and what metrics do you use to evaluate their success?

Goals are set using the SMART criteria, ensuring they are quantifiable. Metrics are chosen based on their direct correlation to the project’s objectives – for example, an enhanced lead generation project might track conversion rates and lead quality. Each metric is a data point on the path of continuous improvement.

Can you describe a project you consider a significant success and the impact it had on your organization or clients?

A notable success was the overhaul of a client’s email campaign strategy which, after rigorous A/B testing and the application of MarketingExperiments’ email optimization research, saw a 30% lift in click-through rates, significantly driving up sales and customer engagement.

Innovation and Trends

How do you stay abreast of the latest marketing trends and technologies, and how do they influence your project planning?

Through continuous scanning of industry publications, case studies on MarketingSherpa, and rigorous testing via MarketingExperiments, I maintain currency with evolving trends and technologies. These inform project planning by allowing the incorporation of emerging practices with demonstrated effectiveness.

Have you integrated any innovative approaches or tools into your project planning process recently? If so, what were they, and what benefits did they bring?

Recent integration has included advanced data analytics tools, aligning with MECLABS’ methodology to leverage user data for more precise customer segmentation. This has allowed marketing projects to achieve granular targeting, increasing relevance, and thus, conversion potential.

Client and Stakeholder Management

How do you manage expectations and communications with clients or key stakeholders throughout the lifecycle of a project?

Communication is managed by setting clear expectations from the onset and providing regular updates. By employing transparent, data-backed communication, as recommended by MECLABS’ principles, stakeholders remain apprised of the progress and are engaged in the decision-making process.

Can you share a situation where you had to manage differing opinions or expectations from stakeholders and how you handled it?

When stakeholders had differing views on a website redesign’s direction, I facilitated a unified vision by conducting A/B testing. This empirical approach, grounded in MarketingExperiments’ methodologies, provided objective data to guide decision-making, leading to a consensus that balanced user experience with conversion goals.

Personal Development and Advice

What has been the most valuable lesson you’ve learned in your career as a project planner in marketing?

Understanding that every aspect of a project should be designed to serve and communicate clearly to the customer is paramount. This lesson is underlined by McGlaughlin’s customer-centric approach to marketing wherein he states, “We must never forget that the goal of marketing is not to make a claim but to foster a conclusion.”

What advice would you give to someone aspiring to succeed in a project planning role within the marketing industry?

Nurture a constant learner’s mindset and ground your planning in data and measurable outcomes. Ingrain the principles laid out by Flint McGlaughlin and resources available through MarketingSherpa, regarding customer psychology and value proposition, to elevate your projects from mere plans to influential marketing strategies.

Related resources

Maximize the Effectiveness of Your Marketing Testing

Quick Guide to Strategy & Planning: 9 tactics to meet your business objectives and use your time efficiently

Webinar plan template

Wednesdays at 2 pm EDT we hold an AI Guild briefing. Chat with MECLABS AI if you would like to register to attend.

In the session, marketers and entrepreneurs can ask questions in the webinar chat. And we answer a few of them right here…

How do you determine when to use Claude vs MECLABS AI?

Claude is a generative AI chatbot that doesn’t have a specific purpose. Although from my personal use, it is very good with large amounts of text, more so than any other generative AI I’ve tried, lending it especially well to tasks like analyzing webinar chat logs, selecting quotes from transcripts, giving feedback on long articles, and similar tasks.

MECLABS AI (available to MECLABS AI Guild members) does have a specific purpose – headlines, value propositions, and other marketing, which makes it better for marketing specific tasks.

MECLABS is built on ChatGPT, but trained with the MECLABS methodology. Since Claude is a more general AI, it is trained on all marketing-related information, not only successful marketing practices.

I also wanted to mention, that while the questions have lately focused on AI chatbots, there are other types of generative AI, like text-to-image models. Flint McGlaughlin teaches an example in Sales Funnel Design: How to combine an “old school” journal, a web page builder, and DALL·E.

How do you overcome the 2,000-character prompt limit on Bing AI?

Here’s a fun little trick. The 2,000-character prompt limit on Bing AI only applies to the ‘more balanced’ conversation style. If you choose the ‘more creative’ or ‘more precise’ conversation style, your prompt limit doubles to 4,000 characters.

Nice, but maybe still not enough for what you want. There are two options I can see.

One, you could use Claude. Again, Claude can consume some very long prompts.

However, on the downside, Claude is a self-contained chatbot and not connected to the internet like Bing. If you need internet connection, you could always treat Bing like a customer and take a Micro-Yes Sequence approach. Map out your information (like you would a customer journey) and spoon feed it along a path for each response.

Even that is not limitless though. I’ve seen data that show Bing has a limit of anywhere from five to 20 chat turns per session. I’m not sure the exact limit, but from my experience it varies based on the topic and length. And for what it’s worth, at some point Bing just acts like it is ‘just so over’ the string of conversation and wants to start a new one. I’m not sure if it’s a feature or a bug, but it reminds me of my teenage daughter.

When you go to Claude, is that automatically Claude 2?

Yes… and no.

When you go to the Claude website, you are automatically using Claude 2, which was released in July 2023. (And as I’ve mentioned before, the most exciting thing to me about Clause is the amount of information it can process. “Claude 2 has been trained to have a further expanded context window of 200K tokens, corresponding to roughly 150,000 words” according to Model Card and Evaluations for Claude Models).

Why you even have to ask this question, and what is interesting to me as a marketer – when you visit the Claude website, it doesn’t mention a model number. This is very different from ChatGPT, which clearly displays that you are using GPT-3.5 and even shows you the ability for a paid upgrade to GPT-4.

When I ask Claude itself the reason for this, it states, “The choice aligns with Anthropic’s overall philosophy of developing AI responsibly, with a focus on user benefits rather than technology marketing. But these are just my speculations on Anthropic’s possible motivations. The company may have other reasons as well.”

If this is the case, I think it’s a bit of company logic. While ChatGPT’s use of model numbers is a marketing tactic to try to show progress and encourage upsells (just like when I bought a Samsung S23 although I would have been totally fine with the S22), it’s also a little more transparent. And with the amount of hesitancy and outright fear around AI, a little transparency is a good thing.

Can you use custom instructions on the ChatGPT version that’s in Bing?

No. As of right now, custom instruction is only for ChatGPT Plus (the paid version), and not yet available in the UK and EU. You can read more about ChatGPT customer instructions in Choosing Your AI Partner: A critical comparison of ChatGPT and Claude 2 for digital marketing.

What is Priority One if we’re going to move into these methodologies? How do we figure out where to start?

This question refers to the AI prompt methodology Flint McGlaughlin presented in this week’s briefing and LiveClass.

Like any type of conversion optimization (which this still is, even if AI is assisting you), start where you will have the most impact.

Here is an example (from Web Optimization: VacationRoost implements 2 testing methodologies to boost total conversion rates by 12%.):

Upcoming tests are elected based on a prioritization spreadsheet.

While many testing teams may allocate importance to factors such as volume and bounce rates, VacationRoost’s spreadsheet is organized by which level in the funnel the page or test would impact.

“Really what you want [to ask] is, ‘What’s going to have the most dollar impact on the organization?'” Hutchings explained.

He added that the pages leading into the purchase funnel rise to the top of the testing docket because of the likelihood of increasing conversion for the whole site is far greater on those types of pages.

I used the suggested prompts to do the competitor analysis and as my website is new, it kept referring back to the content of a website that had a similar name, even when I provided my URL.  Does anyone have any other suggestions on what I can do in my prompts?

Then you may have to do this a little manually, so to speak. And here is where Claude can come in handy, since it can accept such a long prompt.

Copy and paste key information from your website (like your homepage, maybe other key pages) along with competitors’ sites into individual text files and attach them to your Claude prompt using the paper clip icon, telling Claude what you are including.

In general, answers that we get from ChatGPT, are text rich. Is that something we use as a reference or work to absorb it?

Everyone has a different working preference. But remember, the great thing about generative AI is that you don’t have to settle for the first output. If it is too long for you, tell ChatGPT what length you are looking for. Here’s an example…

I used the Prompt Kit (available to MECLABS AI Guild members) marketing prompt for audience research, and got this output from ChatGPT:

Certainly, as a marketing professional, I recognize the transformative potential of artificial intelligence (AI) in the marketing field. Yet, there are still substantial challenges in implementing AI effectively. Here’s an analysis of three major challenges, their causes, impacts, and potential solutions.

1. Challenge: Data Privacy and Compliance

• Why it Exists: AI relies heavily on data for personalization and targeting. The ever-changing regulations surrounding data privacy, such as GDPR and CCPA, create complexity.
• Impact on My Life: Ensuring compliance with various regulations demands extensive legal oversight and continuous adaptation of AI algorithms, consuming both time and resources.
• Potential Solutions: Implementing strict data governance policies and utilizing AI models that prioritize data anonymization can help. Collaborating with legal experts specializing in privacy law is also essential.

2. Challenge: Integrating AI with Existing Systems

• Why it Exists: Many organizations have legacy systems that aren’t built to support modern AI algorithms, leading to compatibility issues.
• Impact on My Life: Integrating AI into these systems can be labor-intensive, time-consuming, and may create bottlenecks in marketing processes.
• Potential Solutions: An incremental approach to integration, supported by a cross-functional team including IT experts, could streamline the process. Adopting flexible AI models that can be adapted to varying systems might also ease the integration.

3. Challenge: Bias in AI Algorithms

• Why it Exists: AI models are trained on historical data, and if that data contains biases (gender, racial, etc.), the model may perpetuate those biases.
• Impact on My Life: Using biased AI models can lead to unethical targeting and representation in marketing, potentially damaging the brand’s reputation.
• Potential Solutions: Regular audits of AI algorithms, involving diverse teams to understand and minimize biases, and utilizing fairness-aware algorithms can help overcome this issue.

Summary:

The integration of AI in marketing presents valuable opportunities but also notable challenges related to data privacy, system integration, and algorithm biases. By adopting robust legal compliance measures, embracing a cross-functional integration strategy, and rigorously auditing algorithms for bias, these challenges can be mitigated. This thoughtful approach to AI implementation aligns with the ethics and efficiency that today’s marketing professionals strive to uphold.

I then told ChatGPT, “What is the single most important thing I should know from your analysis?” To which it responded…

The single most important insight from the analysis is that while artificial intelligence presents immense opportunities for marketing, its responsible and effective implementation requires careful consideration of legal compliance, integration with existing systems, and the elimination of biases. The underlying theme is that success with AI in marketing demands a strategic approach that balances technological innovation with ethical considerations and compatibility with existing infrastructure.

Should we have already put the custom instructions into ChatGPT when we enter this prompt?

All else being equal, ChatGPT will serve you better with custom instructions because it will understand the context of your business and your customers.

But you can use any of the prompts in the Prompt Kit (available to MECLABS AI Guild members) without using custom instructions.

Again, if you want to learn more about custom instructions, you can read our last Q&A post – Choosing Your AI Partner: A critical comparison of ChatGPT and Claude 2 for digital marketing.

Would it be worth doing a few interviews with some of the people who have and haven’t purchased from our email sequence to understand the person behind the numbers?

Yes, I love that idea. That is a great example of increasing customer intimacy.

If you’re not able to go that far, you could send emails that people can reply to (in other words, not from a ‘no reply’ email address which some companies do) and make it clear in the email that replies are welcome.

Keep in mind, with this approach you will only hearing from the extremes, so take what they say with a grain of salt. But if something is truly outstanding or really horrible, you may hear about it. And you may also get a good understand of the words customer use to discuss your product or service.

For the pre-test success metric, is it important for this KPI to have large amounts of data? So for example if I wanted to use sales as my pre-test success metric but my volumes are not in thousands, is that a problem? Where is the biggest opportunity?

This is a question about A/B testing. To quickly explain a complex topic, if your results aren’t statistically significant, what you might be seeing is just random chance. An extreme example: 2 sales is a 100% increase over 1 sale, but that increase might just be random and not because of what you were testing (we explore this topic deeper in Factors Affecting Marketing Experimentation: Statistical significance in marketing, calculating sample size for marketing tests, and more).

Which begs the question – “so how many samples (sales, clicks, etc.) do I need?”

There is no one specific answer. The answer will vary based on the conversion rate difference between the control and treatment. The pre-test planning tab of the Simplified Test Protocol (available to MECLABS AI Guild members) will help you calculate that number.

So as the questioner rightly points out, it is difficult to make a number deep in your funnel, like sales, the success metric…unless you get a whole lot of sales.

As for the biggest priority, I would refer you to the above question about ‘where to start?’ However, your answer will be constrained by where you have the budget to get a statistically significant result.

We also have a free Test Planning Scenario Tool that helps you determine the optimal testing sequence.

Related Resources

Benefits of AI in Marketing: How do the views about artificial intelligence in marketing differ between leaders and practitioners? [chart]

AI Marketing Tools: How marketers are using artificial intelligence to help their campaigns right now

Artificial Intelligence and Machine Learning in Marketing: What marketers (even those who don’t care about tech) should know about AI and ML

Here is a summary of this week’s MECLABS SuperFunnel Research Cohort LiveClass. It was written with the help of artificial intelligence, part of our exploration into using AI in marketing (scroll down to the Process section if you are curious for how it was written).

On March 1, 2022, MECLABS Institute hosted a LiveClass on “Ad Optimization.” The session was conducted by Flint McGlaughlin, the Founder and Managing Director of MECLABS Institute. The session was insightful and provided valuable insights into the world of advertising optimization. In this blog post, we’ll discuss the key takeaways from the LiveClass transcript.

Importance of value proposition

A value proposition is a statement that communicates why a customer should buy from you instead of your competitors. During the LiveClass, Flint emphasized the importance of a strong value proposition. He explained that a value proposition should not only be clear and concise but also differentiated from your competitors. He also mentioned that a value proposition should answer the following questions:

• What is it?
• Who is it for?
• How is it different or better than the alternatives?

The power of clarity

Clarity is an important aspect of any advertisement. Flint explained that an ad should have a clear and concise headline that immediately communicates the value proposition. He also emphasized the importance of using clear and simple language that is easy to understand. He suggested that you should avoid using technical jargon or industry-specific terms that your target audience may not be familiar with.

The importance of testing

The final takeaway from the LiveClass was the importance of testing. Flint explained that optimization is an ongoing process and that you should always be testing different elements of your ads to see what works best. He suggested using A/B testing to test different variations of your ad and measuring the results. He also emphasized that you should not rely on best practices or assumptions but instead let the data guide your decisions.

Conclusion

In conclusion, the LiveClass on “Ad Optimization” provided valuable insights into the world of advertising optimization. We discussed the importance of a strong value proposition, the power of clarity, and the importance of testing. By implementing these key takeaways, you can optimize your advertisements and improve your conversion rates.

The process for creating this blog post using artificial intelligence

This is another attempt to use artificial intelligence to create second-level content. Not primary content that needs subject matter expertise, but content that has a rich feedstock of information that needs to be repurposed from one format to the other.

In this case, I took a session of the MECLABS SuperFunnel Research Cohort, and created a quick blog post summary. You may try to do something similar by publishing a simple writeup of a webinar, podcast or video.

Should you use an entry-level writer? Or can AI handle this?

I’ll include links to my first two attempts at the bottom of this blog post, and here is a little insight into the third attempt.

This time I tried using the Draft with AI feature in Notion, specifically asking Notion to write a blog post, and then I pasted in a transcript of the LiveClass.

The output was basically a long blog post about me specifically, saying how great I was. This isn’t unique to AI, of course. I’ve had human vendors working for me create press releases and other collateral that made me personally or our brands or events sound just amazing. Everybody wants to please the client, right?

And I’ll be honest, I was tempted to publish that as the blog post and just move on to my next task. It really made me sound pretty darn amazing.

But then I remembered the golden rule of marketing – nobody cares about me. Or our brands.

They care about themselves.

So I tried the same process again. As I’ve mentioned before, using sometimes you can use the same prompt twice and got very different results from artificial intelligence. The blog post was different the second time, but still was all about me. It sounded like a letter of recommendation. I tried a third time. Different again, but about me again. OK, I can’t resist, here is a quick bit of it…

Daniel Burstein: A Leadership Example

Leadership comes in many forms, and Daniel Burstein is an excellent example of how a leader can bring people together to achieve a goal… in this blog post, we will explore three key aspects of Burstein’s leadership style: his ability to create a sense of community, his willingness to help others, and his focus on achieving goals…

I mean, who can argue with that, amiright? In all seriousness, I just couldn’t bring myself to publish a full blog post like that.

So I tried a different approach. As I’ve written about before, even a slightly different approach can bring wildly varied results from AI.

I created a page in Notion with the transcript. (Note: A transcript will probably be so long that you can’t just paste it into a Page, you actually have to import the original text file).

And then I created another Page in Notion and told the AI to write a blog post about… and pasted in the link to the transcript page.

This time it created the full blog post we published above.

I didn’t like the title though, so I went into the OpenAI Playground, and asked it to come up with a title for this post.

And then of course – human oversight, although this only needed some very light editing.

On the upside, Notion helped overcome one of the challenges I was having with ChatGPT – that the transcripts were too long to paste in. And while still pretty basic, this may be the best AI-generated summary blog post yet. Here are the two previous posts, and I’ll let you judge for yourself.

MECLABS SuperFunnel Research Cohort LiveClass: A recap of AI, marketing strategies, and collaborative learning

Lessons Learned from a MECLABS SuperFunnel Research Cohort LiveClass: A marketer’s perspective

March 3rd Update: This blog post was originally called “Gain Valuable Insights into Landing Page Optimization…” until Hellie wrote to me with an excellent point – Wednesday’s LiveClass was actually about ad optimization, not landing page optimization. I question why I didn’t notice this obvious error, which I surely would have from a human writer. I think I was so amazed that the AI had come up with a summary focused on a specific topic, since previous versions were much more generic, like “a marketer’s perspective.” And, in fairness, we did extensively address LPO in many LiveClasses before this.

The irony of course is – I’ve been writing (and thinking) and cautioning so much about the blindspots AI can cause because we are so wowed by the parlor trick that we overlook the obvious. And yes, even being conscious of it, I fell victim to this blindspot myself. Thanks for pointing that out, Hellie!

Here is a summary of the February 15^th LiveClass with the MECLABS SuperFunnel Research Cohort. I have the byline, but in truth I didn’t really write this like the articles I normally write. I was just the content generator (or AI writer or automated content writer if you prefer) and used artificial intelligence to create these key takeaways.

At the end of this blog post I share the process I used to create it. This goes along with a key aspect of these cohorts – to experiment with AI tools and see how they can help optimize a marketing funnel.

Hopefully these AI-derived summaries give you an idea or two for improving your own marketing.

Lessons from a Marketing Class: Zoom chat highlights, Part 1

In this marketing class conducted on Zoom, the participants discussed various topics, ranging from ChatGPT’s behavior to the weather in different parts of the world. In addition to marketing-related topics, they discussed the power of community building, and the use of search engines like Bing and Google.

The participants concluded that search engines were increasingly influenced by artificial intelligence, which in turn could be used to further their marketing goals.

One participant noted that “Ads will be much more targeted with this type of information,” suggesting that marketing campaigns are becoming increasingly personalized and data-driven thanks to AI. Another participant shared an infographic of Google Trends showing the popularity of searches related to “Microsoft Bing,” underlining the impact artificial intelligence is already having on the competition between search engines.

The participants discussed the potential implications of artificial intelligence on marketing, noting that AI-driven insights can help brands better understand customer behavior and preferences and create more targeted and effective campaigns.

The participants also discussed the importance of gathering feedback and comments from their audience and then ranking them to determine which ones are most valuable. When asked for feedback on what the cost of the MECLABS SuperFunnel Research Cohort should be, they even joked about splitting a hypothetical $100M equally among themselves.

Overall, the class served as a reminder that marketing is about understanding your audience and building a strong community around your brand. Businesses can create more effective and personalized marketing campaigns by gathering feedback, keeping up with the latest trends, and using tools such as AI.

For example, by using customer feedback to understand their needs and wants, businesses can tailor their marketing campaigns to appeal to their target audience, such as offering discounts or special promotions.

Lessons from a Marketing Class: Zoom chat highlights, Part 2

This is a summary of a MECLABS SuperFunnel Research Cohort LiveClass that was conducted on Zoom. The chat took place at a frantic pace and covered a wide range of topics, which are summarized below:

• BG suggested skipping ChatGPT and heading straight to openai.com.
• DF suggested using Flint’s account.
• The group shared laughter, with JF, TW, and IS using emojis.
• MP noted his preference for OpenAI’s sandbox, despite it not being as conversational in historical referencing.
• BH shared a link to the page [LINK]
• DC made a joke about having tripled his dose of phenobarbital and now being unfazed by K’s page.
• DJ shared his experience of helping a client increase their project rates from $4,000 to $10,973. He credited the increase to helping the client see the value of their work and finding the right clientele. He wondered if the same principles could be applied to the SuperFunnel course and its clients.
• KB expressed her dislike of images with text that are unreadable, noting that they are a bad experience for accessibility and a risk in the USA.
• CG praised B’s work and suggested that the testimonials on his page should include the name of the client’s company.
• DF suggested breaking the instant access form into steps to make it less intimidating.
• HI shared links to three pages: [LINK], [LINK], and [LINK]

The chat was lively and covered a wide range of topics, from humor to serious business advice. It is a testament to the value of the SuperFunnel course that so many people from different backgrounds and locations came together to share their experiences and insights.

This kind of interaction is key to fostering a community of entrepreneurs who are willing to share their experiences with others and help each other succeed. The SuperFunnel course provides a platform for this kind of engagement and encourages its students to build a network of like-minded individuals.

The Process – Can you use artificial intelligence to create written content from your webinars, meetings, classes, etc?

Every content marketer tries to squeeze the most juice from her content, taking information from one medium and bringing it into another. For example, repurposing content from a live event and then sharing videos, transcripts, blog posts, articles, audio podcasts, social media posts, slides, reports, etc., etc.

I like to think of this as secondary content. Primary content is original and requires a subject matter expert of some sorts. But for secondary content, you don’t need a creator with subject matter expertise – just the ability to communicate. I’ve used a more junior writer for this in the past, an intern could do it as well, and we’ve even had this in writer tests before we make a hire.

But to borrow from the GEICO ad, is this so simple even an AI could do it?

Judge for yourself. You can see the AI-written summary blog post above. And you can compare it to previous blog posts I’ve written after LiveClasses of the SuperFunnel Research Cohort – Marketing Funnel Strategy: 3 principles to help you make a high-converting landing page and Lead Generation: Generating business from an ebook, infographic, etc.

I’d like to think mine are better than what the AI wrote, but maybe they’re not? Or how much better do they really need to be? When creating content, I’m often weighted down by the need to deliver enough value to the reader or listener. That is difficult and time consuming. But have I overdone it? And is what the AI created enough?

Of course, the artificial intelligence didn’t create this on its own. It took work from me to engineer. And you may use the same (or different) AI tools to get a better result. AI is still just a tool, and you are the craftsman. A paintbrush, and you are the painter.

So here’s how I wielded the paintbrush in case you would like to do it as well, or let me know a better process.

STEP #1: Determine the source material

I could have used a transcript of the audio from the LiveClass. And I may in the future.

But I decided to use the chat log instead. So the wisdom of the community served as the basis of content before AI was even involved. There is a very active, experienced community on these LiveClasses and they bring up a lot of good and helpful information. If you don’t have an active community in your chat for webinars or other meetings, this may not work as well for you.

STEP #2: Determine the artificial intelligence technology you are going to use

I started with ChatGPT, because, well, the hype is to the moon for it right now.

But I’m a writer at heart, and while ChatGPT can provide good information, I’m not always sure it has the best wording. So, I used Wordtune as well to copy edit and suggest better wording.

Wordtune, with its Spices feature, can also help add content that punches up the copy, and I figure two AI (brains? neural networks?) are better than one.

STEP #3: Craft prompts to get a rough draft

The chat transcript was too long to paste into ChatGPT. And when I asked ChatGPT how long of a discussion I could use, I got the evasive type of answer you would expect from a politician who’s hand was just caught in the cookie jar, not the crisp analytical answer I was expecting of a specific character count.

As an AI language model, I can process queries of various lengths, and there is no hard limit on the length of a query. However, it’s important to keep in mind that longer queries may take longer to process, and may also be more difficult for me to understand and provide a relevant response. So, it’s generally best to keep your queries concise and focused on the information you’re looking for.

When I cut the chat in half, that did the trick. So I did it twice (hence the two parts above). The first prompt I gave was:

Here is the first half of a chat from a marketing class conducted on Zoom. Please write a blog post summarizing this class so other marketers and entrepreneurs can learn from it

I then asked it for a title, and got “Zoom Chat Highlights: Lessons from a Marketing Class.”

After getting that summary, I realized I missed a huge opportunity for specificity (and, frankly, branding) by mentioning the name of the Zoom meeting. So here is the prompt I gave with the second half of the chat transcript:

Here is the second half of a chat from a MECLABS SuperFunnel Research Cohort LiveClass conducted on Zoom. Please write a blog post summarizing this class so other marketers and entrepreneurs can learn from it

I then asked it for a title as well for that version. I ultimately went with this title for this blog post because I liked it better. I passed the title through Wordtune before using it (see next step).

The upside of using artificial intelligence – it provided a different perspective than I would have. For example, the AI discussed some of the humanity of the chat – “the group shared laughter” or “discussed the weather around the world” – while I would have left that out and focused more on helpful information to marketers.

It’s kind of ironic, too, because Flint McGlaughlin and I have discussed at length the importance of making a community about more than just information, and that if we shared video of the LiveClasses we should include some of the camaraderie and fun that has been built up. Even knowing that though, I would have totally missed adding it in.

It’s also interesting that the two parts ChatGPT crafted are so radically different. My prompts were slightly different, as you can see above. And the LiveClass did have two parts – the first half was more informational, and the second half was more interactive as Flint and I provided live conversion optimization suggestions to the community’s landing pages.

But I also question if this is just part of the randomness of AI. If I did this 10 times, would I just get 10 totally different styles. Is this an infinite number of monkeys with an infinite number of typewriters? Is there consistency or just randomness and luck? Something to watch as use of AI progresses.

And really, ChatGPT is called “conversational AI,” but it’s a pretty bad conversation. I give a command and it outputs a response. It would work much better if (like a real human would in a conversation) it asked clarifying questions to hone in on what you really want and how it can help. In this (in fairness, very early) version of conversational AI, too much rests on how well or how clearly you state your prompt, so you need to try multiple prompts and prompt stacking, which lessens the time savings from using AI.

It reminds me of a question I asked Siri recently, “Can you eat the rind of brie cheese?” to which it responded, “I cannot.” When I worded the question better, I discovered the real answer to my question – yes, the rind is edible.

STEP #4: Edit the rough draft

To edit the rough draft, I used Wordtune, an AI writing tool that offers AI-powered writing suggestions.

The tool did some copy editing, although ChatGPT was pretty good there. I’ve heard this function of Wordtune derided because Microsoft Word has similar features. But as I’m sitting here typing, Word is suggesting to me that I change ChatGPT to Catgut…even though Microsoft has invested $1 billion in OpenAI, the parent company of ChatGPT. So my hope is that Wordtune – an online, AI-driven service – has more updated copy editing than Word.

Wordtune offered rewrite suggestions. ChatGPT often wrote in passive voice, and Wordtune changed it to active voice.

It also offered some good wording suggestions. Although sometimes, in fairness, ChatGPT had a little more personality, which surprised me. For example, when writing about the conversation in part 2, ChatGPT described the chat as having a “frantic” pace while Wordtune suggest “fast-paced.” Fast-paced is more professional and business like, so would probably have been the better word to use. And it was probably a more accurate word. But I enjoyed the humanity (can I say that about AI writing?) of “frantic,” so I kept that in.

The thing I really liked about Wordtune, though, was the Spices feature. It’s meant to “spice up your writing” based on some input you give it. It can explain, add emphasis, give a counterexample, and on and on.

This is where the two AI brains came in. There was ChatGPT’s description, and then Wordtune adding to it. Kind of like sports announcers – play-by-play and color commentary.

Incidentally, since the second half was just a bulleted run down of what individual participants did, it would not have made sense to use the Spices feature in that area.

STEP #5: Fact check and use discretion

My intention was not to put my fingers to keyboard and write anything at all in these summaries. Just orchestrate the two AIs off of each other and choose what worked best.

However, there were a few fact errors. So I manually corrected those. In fairness, any writer who had not attended the LiveClass could have made similar errors if they were not given the video recording and only had the chat log to work with.

I also anonymized the participants’ names (since I didn’t have their permission to use them in this experiment) and the links to their landing pages (since they were all rough drafts that attendees were getting conversion optimization ideas for during the LiveClass).

STEP #6: Determine the byline

As you can see, my byline is on this blog post. I felt comfortable doing that because I transparently told you about the process of using AI. Had I not, and just tried to pass this off as any other blog post I had written, I would not have felt comfortable putting my name on this as the writer.

Content marketing is so effective because it builds trust. So in my opinion, if artificial intelligence creates your content, you should tell your audience.

So was it worth using artificial intelligence to write a blog post? Or should I have just written it myself?

I’m not sure I saved much, if any time, using AI to write the summary in this blog post, and I’m not even counting this lengthy process description I wrote.

First, I’m probably faster than the average writer because of my lengthy experience in this industry. So if you are a slower writer, you might save more time than I did.

Frankly, it took some time playing with the two AI tools and getting it just right.

Of course, this was my first time doing it. If I did this regularly, I would probably get much quicker and more efficient with the process, or even find a better process. And in fairness, I could have used a simpler process, and just taken what ChatGPT gave me directly, not using Wordtune at all.

I also want to point out – artificial intelligence takes some time because it requires human oversight. I worry we can be lulled into a false sense of confidence in what may be an advanced parlor trick. Yes, isn’t it amazing what these machines can do with their intelligence? But I fear they are a bit like Toonces the Driving Cat.

If you’re unfamiliar with the old Saturday Night Live sketch, the people are so impressed the cat is driving them in a car. Isn’t it amazing what the cat can do? Until…

…the cat drives them off a cliff. At which point you get the punch line “Toonces can drive a car, just not very well.”

For marketing leaders, the other question is – would using AI in this situation hurt your ability to grow your team? As I mentioned, this kind of assignment can be great for a junior writer, to build their writing chops and domain acumen in your industry. So will this steal from your bench strength?

No easy answers, at least to me. But when I asked ChatGPT, it had the answer. It told me…

Incorporating AI technology into certain marketing tasks can actually enhance the growth of your team, rather than hurt it. By automating some of the more repetitive and time-consuming tasks, your team can focus on higher-level work that requires a more strategic and creative approach. This means that your team can be more productive, efficient, and effective in their work.

Additionally, AI can serve as a valuable tool for learning and skill-building. For example, an AI-powered writing assistant can provide real-time feedback on grammar, tone, and style, allowing junior writers to learn and improve their writing skills more quickly. This can accelerate their development and help them become more effective writers in a shorter period of time.

Finally, it’s important to note that while AI can automate some tasks, it can never replace the creativity, strategic thinking, and human touch that marketing professionals bring to the table. Therefore, rather than taking away from your bench strength, AI can actually enhance it by freeing up your team’s time and resources to focus on more impactful work.

Related Resources

Sales Funnel and ChatGPT: 6 ways to leverage AI now to develop a powerful value proposition

Artificial Intelligence Case Studies: Two companies that boosted brand awareness with AI and another marketer that used humans instead

Artificial Intelligence and Machine Learning in Marketing: What marketers (even those who don’t care about tech) should know about AI and ML

AI Marketing Tools: How marketers are using artificial intelligence to help their campaigns right now