MarketingSherpa Blog

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

Whenever we have questions in our weekly LiveClass – ChatGPT, CRO and AI: 40 Days to build a MECLABS SuperFunnel – we answer them here on this blog to help attendees, but to help any of our readers who didn’t attend but may have had a similar challenge as well. Read below and get ideas for powering the growth of your business with marketing experimentation. And feel free to join us for a Wednesday LiveClass using the link I just mentioned.

Has anyone tested video ads vs image? Preston’s question in the LinkedIn group got me thinking. Daniel Burstein, do you know of any?

Here’s an example. “The team discovered through testing these Facebook ads that medium-form copy received 33% more clickthrough than short- or long-form, and video drove more clickthroughs and had greater reach than static images. Because of this testing, the team realized that video was one of their most powerful tools” (from Email Marketing: List size increased 600% in one year through content, paid ad strategy).

The reason I start with this question is because it lays out the reason we should be conducting marketing experimentation – so our customers answer key questions we have about our company and our marketing with their real-world behavior, instead of just making decisions based on internal guesswork.

No matter what has worked for another company (including the above example I just used), it doesn’t mean it will work for your unique customers, your unique value proposition, your unique situation. So don’t just follow what others do, use it as fodder to come up with your own wildly creative ideas – and then test them.

Now that we know why we should test, let’s get into some of the mechanics of testing, starting with test planning…

What is the main purpose of the [pre-test planning] calculator? Is it to estimate how long you’ll need to run the campaign? If I have a set daily budget, set level of confidence, set conversion rate, set number of variants and an unknown variance [the questioner is referring to the relative conversion rate difference between variants of the ad], what is the main purpose of estimating the data? As soon as the ads start running the numbers will all change and need updating. What’s the main metric we’re aiming on understanding?

As I have mentioned in a previous blog post, I’m not the mathematician, I’m the storyteller. So I won’t get into the math behind these concepts. But I do think it helps for marketers to understand the concepts at a basic level, to inform their testing. And if you haven’t already, reading last week’s blog post will help get you up-to-speed on some basic marketing testing concepts – Factors Affecting Marketing Experimentation: Statistical significance in marketing, calculating sample size for marketing tests, and more.

In this question the person is outlining the different metrics in the pre-test estimation tool (that is included as part of membership in a MECLABS SuperFunnel Cohort).

The goal of the tool – as with any planning – is to inform your efforts. Things may not turn out exactly as you think they will, but when you see the levers that you can pull to shape results, it should help you make decisions on what you want to move forward with and actually execute.

One of those levers is budget, to affect how large of a sample size your treatments receive. In this question the “daily budget” can’t be changed, so if you run the pre-test calculation and realize it would take an inordinate amount of time to reach statistical validity based on the amount of impressions or traffic your budget can buy, you may have to get creative.

Here’s one example, using Bugs Bunny and Daffy Duck. The team behind Looney Tunes and Merrie Melodies had a set ‘daily budget’ for how long they could work on an episode. So if they wanted to do something a little more groundbreaking, they would ‘borrow’ from other episodes. Maybe they would take only four days instead of five for a few episodes, and then using that time they saved up they would dedicate eight days to an episode to really push the envelope (I recommend Duck Amuck and What’s Opera, Doc?).

Perhaps this planning tool might help you do the same thing. Invest less of your fixed daily budget in experiments where you know there will be a large conversion rate difference between the ad or landing page variants, so you save up some of that budget for experiments where there is a smaller difference.

Which brings us to another decision pre-test planning can help us make…

Ave Test Users = Impressions … Primary KPI Successes = Clicks (Or is it Opt-ins?) Variants = number of ads, Assumed Real Difference = Between the ads

The question is around what the primary KPI (key performance indicator) should be for an experiment – clicks on the ad or opt-ins on the landing page.

This is important to statistical significance because it will impact the sample size. The deeper you test in the funnel, the smaller your sample size will be. More people will click on an ad then will opt-in on the landing page. So the larger budget you will need to get a large enough sample size.

This is another reason why using the pre-test estimation calculator can be helpful – to inform where in the funnel you decide to test, based on your budget and/or other capabilities for getting people to see the conversion action you are trying to test.

What should your sample size be? There is no set sample size you need to reach. It is affected by how different the performance is in the different treatments. And we use the pre-test planning calculator to help us find that number.  “An important factor in sample size determination is the difference in results between the treatments. If the treatments return very different results, it’s much easier to confidently say that you really do have two (or however many) emails that will perform differently. You don’t need as many samples to do that. However, if the treatments have very similar results, you want many more observations to see if there really is a difference.” (from Marketing Optimization: How to determine the proper sample size)

Why make impressions-to-ad-clicks as the primary KPI and then ad-clicks-to-appointments a secondary KPI? Why not make impressions-to-appointments the primary KPI? Is that just because the volume of data for the latter would be higher? So measuring more the message lever, rather the whole funnel effectiveness?

This question naturally follows from the previous one. As discussed, your KPI for a test is partially informed by the sample size and relative difference between the control and treatment.

But it is also partially informed by what you are trying to learn. Let’s not get too deep in the math and mechanics that we forget the goal of test – to learn how to better serve the customer and better communicate to the customer so we can improve our results (as discussed in the first question in this blog post).

And remember, you don’t have to learn everything in one big test. Your goal is to test and learn repeatedly. So your first test can be in the channel, and then your second test could be on the landing page, for example.

To inform future testing it helps to establish secondary KPIs when you set up your test. Of course, you could just look at every possible metric under the sun. But the reason we do pre-test planning is to run our experiments with intention.

One of our former data scientists explained it to me this way – an experiment is picking a specific tree in a forest, then throwing a rock and seeing if you hit that specific tree versus throwing a rock into a forest, seeing which tree it randomly hits, and then remarking, “oh yeah, I meant to hit that tree.”

Pre-test planning focuses our thinking and efforts on hitting that tree. And secondary KPIs can help here as well. “Don’t try to analyze it all; you’ll get lost in data and become discouraged and confused. Instead, narrow your focus to the metrics that will provide the most relevant insights. Having primary and secondary KPIs for your site will help you begin to narrow your focus” (from Marketing Analytics: 6 simple steps for interpreting your data).

So you could first test message levers in the channel using a primary KPI of clickthrough. Then if your secondary KPI is conversion rate on the landing page, and the conversion rate is low for the winning ad treatment, you have a next (and very interesting) question to test.

Did the ad message you used simply bring lower-quality traffic, less motivated people to your website? For example, an ad message of “Free iPaid” might win a test in the channel but isn’t necessarily doing your funnel any favors if you can’t pay off that promise.

Or, is it an effective ad message to attract your ideal customer, but you don’t pay off that message well with you landing page. There is poor continuity between the ad and the landing page, which was simply a previous page you already had and didn’t align with the treatment ad’s messaging. Which brings us to…

Why would we use a page separate from our webpage?

You may have an ad message you want to test that is very different from the message on any webpage you have now. In that case, it would likely make sense to create a new landing page for it.

We could use the experimentation process I just mentioned to determine that our current webpage does not deliver on the new ad message, that there is poor continuity from the new ad message to our webpage.

However, signing up for marketing experimentation is not a binding agreement to endure unnecessary agony. We can also use our common sense and marketer’s intuition to avoid changes that are very likely to have poor results – after all, we are testing with a real budget and real people – and focus our energies on the questions that are more difficult to answer and will have a big impact on our business.

Of course, this means you may have to build a new landing page. Which brings us to our next question…

Chris it looks like you followed the template exactly, Daniel are you saying feel free to move the layout around and put the hero image in place of the form?

Participants in the MECLABS SuperFunnel Cohort get access to MECLABS SuperFunnel builder software (a simple drag-and-drop landing page builder that is embedded with the MECLABS methodology). This includes templates to help you build a landing page based on an approach that has shown to be effective in previous experimentation.

I won’t go through the entire template, but it begins at the top of your landing page with Micro-Yes 1 – Yes, I will pay attention. This section should be a synopsis of your core offer. Followed by Micro-Yes 2 – Yes, I will engage deeper – where you address any friction or anxiety. Also, in this section you can add a video, image, or a form that supports your message.

The Cohort member I was providing optimization advice for in the LiveClass has a spokesperson that is well-known in his industry, and my point was invoking that spokesperson earlier on the landing page may help grab attention and be a core element of the offer that gets the ideal customer to say ‘yes.’ It may also be a way to reduce anxiety.

For example, I am a huge fan of Jerry Seinfeld. If he ever produced a show focused on marketing (let’s call it Copywriters In Cars Getting Conversions), his participation in the show would be a core part of the offer that would grab my attention. His participation in the show would also reduce my anxiety that it is a quality show and get me to engage deeper.

The SuperFunnel template can guide you to build your landing page but should also be spurring future hypotheses in you for further testing. For example, is our founder a core part of the offer and she should be included at the top of the page along with her image? Or is she a tertiary credibility indicator, and she should be used lower down on the page to help address any last-minute anxiety?

This is an example of a question you can test that has implications for the business. You can start by testing in the channel and conduct further testing on the page.

To get you thinking of possibilities for your own business, you can see three value categories we test through email for VolunteerMatch in A/B Testing: How to improve already effective marketing.

If you are conducting a marketing experiment in the channel, you will also need to create the different ads to test. Which bring us to…

Ask ChatGPT what colors to use: “I have an ad with #CFB82C as the primary text color, #384E6C as the background color, and #333333 and #FFFFFF as additional colors. What color should my call to action button be and what color should the text be on top of it. Give me html codes.” … “Is there a green color that will work?”

OK, this isn’t really a question. I found this in the Zoom chat, and I just thought it was some nifty advice for using artificial intelligence to help you build an ad.

Hi Flint, what does the cohort entail? 4-5 weekly meetings. 40 days total/ price? Also if I’m generating a sales funnel for the first time is this a good option for me or should I start on another level (finishing my Micro Yes’s now)

How do I join this group!?

How do I join the MEC200 group?

How do I register for the next cohort?

Is there another cohort scheduled yet after April or approx. start date?

Jane, Is this video zoom call a part of the first cohort?

What happens with the transition to cohort 300?

There were a lot of questions from attendees about the cohort itself, and we answered them with a Q&A session at the end of the cohort. If you would like to learn more about the cohort, and the five ways you can ‘pay’ if you choose to participate (there are monetary and non-monetary options), just join us on a Wednesday LiveClass of ChatGPT, CRO and AI: 40 Days to build a MECLABS SuperFunnel.

Even if you don’t choose to join, by attending you should get a few ideas you can implement to your marketing funnel right away to improve conversion.

Here’s a quick excerpt from a recent LiveClass to give you an idea of what to expect – Hypothesis Articulation vs Essence.

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 22^nd MECLABS SuperFunnel Research Cohort LiveClass, written by artificial intelligence (scroll down to the Process section if you are curious for how it was written).

The MECLABS SuperFunnel Research Cohort recently conducted a LiveClass, which attracted a diverse group of marketers from different backgrounds. The participants shared their experiences, insights, and suggestions on various aspects of digital marketing, from AI to headlines. Here are some of the key takeaways from the LiveClass.

AI as collaborators rather than doppelgangers

One of the participants suggested that AI should be viewed as collaborators rather than doppelgangers. In other words, AI should be used to enhance human life rather than replace it. The participant added that businesses should focus on using AI to augment their existing processes and workflows, rather than trying to replace humans with machines.

Headlines should contain four value words

Another participant noted that headlines should contain four value words. The participant added that these value words should address the customers’ pain points and offer a solution to their problems. Another suggestion was to include the words “you” and “your” in the headlines, which could help to make them more personal and engaging.

Tips and ideas for marketing a new product

During the LiveClass, participants discussed various marketing ideas for a product, including sample stands in local supermarkets, geotargeting filters on ads, and shipping free samples in a time of inflated shipping costs. One participant suggested that the product’s entire step-by-step handmade recipe could be shared as a marketing strategy, emphasizing the ancient human craftsmanship and unending tradition.

Another participant jokingly suggested that the taste profile could be converted to binary so customers could download the taste to their cerebral cortex. Some participants suggested selling the product to restaurants or stores instead of individuals. The participants also discussed the importance of storytelling in marketing and how it can create an emotional connection with customers.

Tips for creating a compelling landing page for a free ebook about logos

One participant submitted a landing page with a free ebook about logos.

The participants discussed the importance of a good logo in building trust with potential customers. They suggested that the design of a page should be more breathtaking if a company wants potential customers to trust them with their logo. Participants recommended showcasing recognizable logos of companies the design team has supported. They also suggested analyzing the company’s own logo to demonstrate their expertise and convey the logic behind the choice of every aspect of the logo.

Participants suggested creating an infographic that dissects the company’s logo to provide a visual representation of their expertise. They also recommended creating a personal value proposition to help businesses develop their brand identity. Overall, participants agreed that a good logo is a crucial element in building trust with potential customers.

Overall, the LiveClass provided marketers and entrepreneurs with various creative marketing strategies to help them promote their products effectively. It was a valuable learning experience for marketers. The participants shared their experiences, insights, and suggestions on various aspects of digital marketing. The key takeaways from the LiveClass highlight the importance of using AI as collaborators, crafting effective headlines, and paying attention to website design.

The process for creating this blog post using artificial intelligence

When I tried this last week, I went into much more detail about the process for using AI, and thoughts for using AI for content creation. You can read that in Lessons Learned from a MECLABS SuperFunnel Research Cohort LiveClass: A marketer’s perspective.

The basic thrust for using AI is – for something simple like summarizing a webinar, is AI good enough? Should you use an entry-level human writer? Or do you need a skilled, experienced human writer with deep subject matter expertise? One of the participants of the LiveClass summed it up well by discussing marginal returns – when it’s not worth trying 50% harder to get a 1.4% improvement.

The goal this time was to use the transcript from the LiveClass as the feedstock for the AI. So first we attempted to use Fathom. But Fathom only works with Zoom Meetings, not Zoom Webinars. So that didn’t work.

Then I tried to use ChatGPT and paste the transcript in. But that didn’t work either. The transcript was over 22,000 words, too long for ChatGPT. ChatGPT recommended about 1,000 words.

So I decided to go back to what I used last week – the chat log. This provides an extra filter, adding the wisdom of the community. Of course, filters have an upside and a downside. The downside being that you’re not learning from the teaching directly.

Even this was too long for ChatGPT, at over 5,000 words. So I had to cut it into thirds.

This brings up another challenge with ChatGPT. Even if you give it the same exact prompt, it will create different outputs each time (there must be some level of randomness programmed into it).

Not ideal for having a blog post with a consistent voice. Although after some tinkering with different prompts, I was able to get something close to uniformity in voice.

The most effective prompt had the least amount of information. “Write a blog post based on a MECLABS SuperFunnel Research Cohort LiveClass. Here is the first third of the chat from the LiveClass.”

This worked better than prompts discussing the target audience or asking for transferable principles or key takeaways. I found ChatGPT used those prompts like an entry-level SEO writer fond of keyword stuffing. It just repeated those words and synonyms of them throughout (trying to please me, I guess?) When I just asked it to write a blog post with less info, it seemed to use natural language processing more to determine what the chat was actually about. There was also more consistency of voice with this approach.

And then, of course, it required human insight and oversight, although I tried to use a very light editor’s touch, since the purpose of these blog posts is not just to give you a summary of the LiveClasses, but also, to further all of our knowledge in using artificial intelligence (paired with human intelligence) in our marketing and content creation.

So this was another step on our journey into the future.

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