So What? Automating Email Newsletters With Generative AI - Trust Insights Marketing Analytics Consulting

So What? Marketing Analytics and Insights Live

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In this episode of So What? The Trust Insights weekly livestream, you’ll learn how to use generative AI to create newsletters. You’ll see how to build a generative AI prompt that will take your ideal customer profile and podcast transcripts to create a first draft of a newsletter. Discover the benefits of using generative AI for newsletter creation as well as the ethical considerations. Finally, get a look at a real-world example of a newsletter created with generative AI.

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So What? Automating Email Newsletters With Generative AI

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In this episode you’ll learn:

When & why to consider gen AI for newsletters
Construct newsletters with generative AI
Test whether AI-led or human-led content performs better

Transcript:

What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.

Christopher S. Penn 00:32
Happy Thursday, everyone. This is the marketing analytics insights live show. From Trust Insights, I’m Chris. John, how are you doing?

John Wall 00:39
Good, good. This is my last day in the virtual studio here, so we’ll be back to the normal deal next time we’re on.

Christopher S. Penn 00:44
Very nice. And Katie is somewhere in the mountains lost. We’re going to send some drones to find her.

John Wall 00:52
Hopefully, they’re safe.

Christopher S. Penn 00:54
Hopefully today we’re going to answer the question about should you, and if so, could you automate the construction of an email newsletter using generative AI tools? And we’re going to specifically do it using the Marketing over Coffee newsletter as an example. So John, start us off. What is the Marketing over Coffee newsletter? How often does it go out? How long does it take to make it, etcetera?

John Wall 01:26
Yeah, over the years, we’ve collected email addresses of folks that listen to the podcast so they get the podcast weekly and are able to keep track there. But this idea of sending them an email right now, it ends up being quarterly. Pretty much of here are two or three of the biggest shows over the quarter. And then I usually just have four or five other links of things that I throw into a pile that I want to push and hit.

But there’s definitely an opportunity for it to go more frequent. I mean, there’s no shortage of content. We have tons of stuff. And so then it’s a matter of, the challenge right now, though, is it’s just, it’s low-priority work. I mean, we have to get the episodes out. The sponsors have signed on to specific episodes and specific sponsorships.

John Wall 02:11
So creating that content always takes the top shelf because, yeah, I would love to do it at least monthly. And it ends up being quarterly because after two months I’m like, “Okay, I have to crank one of these out the door because I haven’t done it in so long.” But the thing is, it’s more disciplined. It’s not that it’s a ton of work. It’s just that it’s sitting down to write the content, come up with that first ugly draft, and then after that it’s mostly cut and paste.

We use Ghost for the distribution of it, which that’s gone through a bunch of iterations, too. We’ve used different email service providers, and then now we’ve switched over to this publishing model just because it was kind of less headache. But that’s kind of the starting point for the thing.

Christopher S. Penn 02:50
Got it. So what would going to monthly, what would the benefit be versus quarterly?

John Wall 02:57
It’s all just about more engagement because we do find that even if it’s because there have been times where I started doing it monthly or better, and it still gets great engagement, it’s content that people want so there’s no reason not to publish as often as we can. It’s just a matter of making the time for the work.

The other big one with that, too, is it’s a great value add for the sponsors because we get to plug whatever they’re plugging in the episodes. It’s very difficult for people to click through an ad when they’re listening to a podcast. But if the email is right in front of them and we literally say, “Hey, Netsuite by Oracle is helping us out this month, go ahead and give them a click here. Check out what they’ve got going on.”

John Wall 03:34
That drives a lot of traffic, and those are qualified leads. That’s a real upsell for the sponsors.

Christopher S. Penn 03:40
Got it. So in terms of the audience, who is the audience? What does that customer profile look like?

John Wall 03:49
Yeah. I mean, we don’t really know much beyond the fact that they are Marketing over Coffee fans. I mean, they listen to the show and have somehow been driven to moc.com dot. But yeah, that’s another one. Tom Webster is looking down on me with a frown because if we were to be doing more research, we would. Because I think a big part of it, I think there’s a segment of that audience that doesn’t have time to listen or it’s just easier for them to read an email and depict the highlights and get summaries of things.

So yeah, not much known. They do fit the Marketing over Coffee audience profile, but not much knowledge beyond that as far as why are they opening the email and what else are they interested, and we really have no other insight there.

Christopher S. Penn 04:29
Got it. This is something that Katie put together before she got lost in the mountains. This is the ideal customer profile for the show. Based on the shows, some of its competitors, some of the folks that you would want to have as listeners. In terms of people who are tuning in, how well does this resonate?

John Wall 04:50
Well, the thing when she had pulled out, we really focused primarily on advertisers, folks that are using this audience. So it’s people who value this audience, which, it still ends up being the same audience. So the research is the same because it’s the same group of people. It’s just a matter of them being, their target versus my target.

But yeah, it’s definitely dead on. You’ve got the intersection of marketing and tech. It’s folks who are listening for actionable tactics, very specific in marketing and tech. It’s not, this is not Joe Rogan. This is a very specific audience. And, but of course, that makes them very valuable to advertisers, too. There’s no wasted impressions with this group.

John Wall 05:30
I mean, everybody listening to the show is very interested in marketing and technology and trying to, get their organization to stay at peak performance. Yeah, it made. And then, I don’t know, we can, I don’t want to dig in too deep into the ICP because we have a lot of stuff that we’re kicking around with this and going on with it, but it is great. And that it goes all the way to. Okay. And so here’s the tactics that work, and here’s your competitors, the tactics that they’ve been using, and here’s suggestions as far as what to do next. Things you should shortlist as far as activities to test out and go. So, yeah, it’s a good picture of who the listeners are and kind of what we need to be doing going forward.

Christopher S. Penn 06:10
Yeah, one of which is called out as newsletter optimization. Doing more with the newsletter. So walk me through the process of making an issue of the newsletter. You sent over one not too long ago, but talk me through what is in the average issue of the newsletter.

John Wall 06:31
Yeah. It’s really, I mean, looking at the newsletter, you can see the format of the thing. And, in Ghost, it’s a WYSIWYG document. So basically, I have one of those in front of me, and it’s always the same basic format of, there’s the editor’s intro. I just kind of say, “Hey, how are you doing? Talk about one or two big things that have happened.” And then there’s usually three to five segments beneath that. Usually, two or three of them are the bigger interviews from the past month or two. And then there is kind of an x-factor in there. There are usually at least one or two spots of just random things that I’ve come across in the past month that I think are appropriate for the audience. And sometimes they haven’t even been in the show.

John Wall 07:14
They’re just things that have come across, and for whatever reason, it’s more appropriate to hit it via email. But yeah, it’s literally just five chunks of the biggest thing that has, the biggest things that have happened over the past couple of months. And usually, three or four of them are direct from the show. And then I always, the last rap is always entertainment or media or books, some kind of media recommendation and a farewell out. But yeah, it’s basically kind of stare at that blank sheet and fill in the blanks until I get something that’s crowd-worthy.

Christopher S. Penn 07:43
How long does it take?

John Wall 07:45
It takes about an hour to get the thing where I want it to be. It’s one of those things where I have it as a side project, so as I’m between calls or whatever, I’ll spend 10 or 15 minutes on it and just keep chipping away at it over, like, three or four days because usually, I’ll start hacking away on it on a Friday or Monday. And the goal is to get it out the door and not, go to the Friday graveyard, get it out before Thursday afternoon.

Christopher S. Penn 08:11
Got it. Okay. So it’s gathering up the episodes. You have to go to the website, gather up the episodes and the URLs from the website. We don’t, for the show, most of the time, do transcripts. It’s usually just show notes.

John Wall 08:27
What?

Christopher S. Penn 08:27
What would it take to put the transcripts on the website?

John Wall 08:31
Yeah, that’s, I’ve kind of, I mean, we’ve done that in the past. I’ve done it for big episodes. I mean, it was you using Otter, just throw the auto file in there and cut and paste it back over. We’ve switched to Fireflies, and I haven’t tested that out yet. There’s also, I know Libsyn is supporting some kind of transcript stuff, and I haven’t had a chance to play with that either. So, yeah, that’s just been on the kind of to-do list forever: Find a quicker, easier way to do that or hire that out or whatever, and it just never gets done. I have in the past done it for bigger episodes. If I ever come to a point where I want to do an encore episode or re-push an episode, then I definitely run a transcript.

John Wall 09:07
But, yeah, that’s basically, it’s not as bad as the missing metadata, but it’s definitely in the top five of data that should be in the data store.

Christopher S. Penn 09:16
Yeah. Because you can see here this episode, this is the one that you did with Katie recently. This is what’s in the show notes. Now, in preparation for today’s episode because transcripts are an important part of feeding generative AI useful information, I went ahead and I put the transcript. So I used, we switched over to Fireflies. So I put nine episodes worth into Fireflies and just dumped that out and put it back in. So you can see this is what’s in the show notes. And then when you get to the transcript, we have a lot of text, a lot of valuable information in here that you would want to have if you were going to be building, you’re going to be putting the stuff up to promote it and to get into newsletters.

John Wall 10:00
Yeah, well, and then, from the ICP, too, it really leans hard on SEO. And that’s a whole other benefit of that, is having all that text in there. That’s a lot of rich text, and it’s all, keyword appropriate. It’s not machine-generated. It’s real-life speak and stuff. So that’s all quality.

Christopher S. Penn 10:17
Exactly. Okay. So you gather the episodes, we summarize the episodes, sponsor content. How do you decide which sponsors go in the newsletter? Is it just the ones that have advertised for that quarter?

John Wall 10:28
Usually, the ones that have advertised for that quarter. That’s kind of, that comes down to a deal-to-deal date basis. But I know it could easily if it just grabbed the two. I’m trying to think of how it would do that because actually quarter over quarter is not changing a lot. There are usually two primary sponsors that ride for the quarter. So if it would grab from one of those, that’s fine. Or again, I know as soon as I’m putting it together, it’s literally just cut and paste from the, again, from the same page here.

Christopher S. Penn 10:56
Got it. And then the format of the newsletter, is it just a web editor?

John Wall 11:01
Yeah. Again, it’s Ghost’s interface, which is WYSIWYG, but yeah, I can cut and paste code over there. So if it dumps HTML, that’s good enough for me to get running with.

Christopher S. Penn 11:14
Got it. Okay. And then how do you measure the success of the newsletter? That is just.

John Wall 11:20
Kind of opens and clicks, that’s literally all we go with and landing pages. Of course, I occasionally use Reddit, not Reddit, Bitly links. If there’s one I want to see how it’s doing, I’ll throw a Bitly link in there just so I can go back and check in on it later. But it’s not, it’s pretty much as long as it’s the same as the last previous newsletters. If there’s a 10 to 30% open, and I get a couple of hundred clicks, like that’s all good. It’s definitely, I’m not optimizing the thing or testing what’s going, it’s more of just, okay, if it gets some action, that’s great.

Christopher S. Penn 11:51
Got it. Okay. So if you were to use generative AI to build the newsletter, at least a first draft of it, what would you be looking for in terms of benefits to you, benefits to the audience, benefits to the sponsors?

John Wall 12:08
Yeah. I think, again, it could take a lot of the pain out of the ugly first draft. Like in a perfect scenario, it would take a look at the last four or five episodes and just create summaries for each of the episodes and grab the sponsors and just dump that all into HTML. I mean, in a perfect world, that would just dump it right into Ghost, and then I could just move the cubes around. But, getting to HTML would be at least enough for me not to have to do the writing on that first round. Just be able to start cutting and pasting stuff.

Christopher S. Penn 12:41
Got it. So if you had something that looked maybe like this, would this be a good first draft?

John Wall 12:51
Yeah. I mean, that’s the perfect place to start with. And the great thing with that is I could give that to a VA and say, “Okay, put that over in Ghost, and go get some graphics and clean it up.” And that would at least, that takes a lot of the pure grunt work out of it. Yep.

Christopher S. Penn 13:05
Because you have your sponsored by your fun stuff about the stuff that was the fun stuff that was mentioned in that quarter’s shows, et cetera.

John Wall 13:12
That is cool. Wow. And that’s really, that’s way beyond the scanning that I’m able to do. I mean, my pathetic mind can grab the fun stuff from the past two episodes or so, but to be able to get the full list from like the last six, that’s killer.

Christopher S. Penn 13:24
Okay. So let’s talk about how you build this because I think there’s a, there for being able to do this. The first thing we need to do is we need to know what a good newsletter should be. Because a good newsletter for a podcast generally should be more than just spitting out a pile of links. That doesn’t really help anyone.

So let’s start off by going to go into Google’s Gemini here, and I’m going to put in our system prompt instructions. This is just going to help flesh out the topic. And I’m going to say your topic is creating best practices for creating a newsletter, a monthly newsletter that supports a podcast, a weekly podcast. So let’s see what Gemini has to say about it. I’m going to turn the safeties down here.

Christopher S. Penn 14:27
So it says things like consistently align the value of consistent value alignment with your podcast strategic content strategy for maximum engagement. Optimize design and format for readability and action. Promote your user effectively. Analyze and adapt and analyze your data. So that’s pretty decent in terms of things that we would want a newsletter to do.

Let’s go ahead now. So we’ve got our basic instructions about what a pod, newsletter, podcast. A newsletter for a podcast should do. We need to get the information, and we need two pieces of information. The first is we need that ideal customer profile, and the second would be we would want to have the actual episode content itself. Now, one of the things that you can do with podcasts, if you have a standard show, is you can actually go to the feed, the RSS feed itself.

Christopher S. Penn 15:23
And as long as your feed publishes full episodes and not episode summaries, if your transcripts are on the page of the episodes, your feed contains the whole transcript. And this is super valuable and fast for getting the, essentially, the raw materials that the AI needs to be able to create episode summaries and stuff. So if your feed has that, then you’re pretty much like three, four, the way done.

You’d want to copy and paste this into a text file that you would ask it to read. The next thing you’d want to do is you’d want to build that ideal customer profile. Who is your audience? Who is it you’re trying to make your newsletter for? And this, by the way, applies to any newsletter, not just podcast newsletters, but any newsletter at all.

Christopher S. Penn 16:13
Building out that ideal customer profile means that you know who you’re writing for, and you can evaluate whether or not your newsletter is a good fit. Or you can even take your existing raw data and format it if you like, help building that. Of course, shameless plug. We do that, go to Trust Insights AI services. We can help you do that. Okay, so we’ve got, we’ve, so let’s say we’ve got those two pieces.

The next thing we do is we need to start assembling the prompt and the prompt. This is where we’re going to go away from basic prompt engineering. We’re going to go into some fairly heavy stuff because today’s language models are incredibly capable of following very detailed instructions. So I’m going to, we’re going to do this like a cooking show.

Christopher S. Penn 17:01
I did a lot of baking in the background because this stuff takes hours to get right the first time. Once you’ve got it right, then it’s pushing a button, and off you go. So let me walk you through this. The pieces of this prompt.

First, you. It’s. You say it’s system instructions. And let’s see if I can make this bigger because it’s kind of hard to see. Typeface regular. Let’s go to. That’s too large, 18. And can we fit this to the window width? There we go. Okay, so in our prompt, we first have our background. Here are the best practices for creating a podcast newsletter. We just talked through that with the machine, and it spit out all this very useful information about what should be in a podcast newsletter.

Christopher S. Penn 17:52
Common mistakes, what to avoid, writing a wall of text, and so on and so forth. Some common myths, and then some surprising truths. Personalization matters, A/B testing, etcetera. So that’s the best practices.

We want to have that as part of the prompt because it tells the model, here’s what you should be doing. Like these are your basic guidelines. The next section is we want to start giving instructions. You’ll notice, by the way, the anything that’s background information like that I keep with these three n dashes to let the model know that’s copy, it should just read.

You’re going to create the podcast newsletter invalid markdown format. The user, us, will provide the following configuration information: the podcast title, the ideal customer profile, the episode text, and in our case, sponsor information.

Christopher S. Penn 18:43
If the user does not provide this information, ask for it using the provided episodes text file. You’re going to create summaries following this format. You’ll note the episode title uses the episode’s URL in markdown to make the title clickable because we want this to be something that can go into an actual newsletter.

Each episode is separated by the Apple headphones. There do not include the delimiters. And so I have specified in this template. This is what I want every episode summary to be. The title, the URL in clickable format, the URL naked so that if it’s in the text, email reader, whatever it is, someone can copy and paste it, and then directions. Write a one-sentence episode summary on why the ICP would care. This is important because we want this to be, we want it to use the knowledge of who the ICP is.

Christopher S. Penn 19:34
You’ll notice all these things are here in curly braces. The curly braces there because it is a way to denote to the model. These are essentially placeholders. They’re variables. If we have a title, we have episode text, we have all these pieces. The model knows to look at this and go, “Okay, I need to insert items into these slots.”

Here’s an example, and we want to give it a working example. So there’s Katie’s episode, and you can see the title, the URL plane, and then the summary. So we’re giving it what to do so that it can read that properly. You’ll create summaries for each episode in the included episodes file. Here’s the template to use for the newsletter intro markdown format. Don’t include those delimiters, so we have the title, the month brought to you by the sponsors. Write an introductory paragraph.

Christopher S. Penn 20:24
Explain what’s been on the show recently, recent episodes, and the episode summaries. It knows to put those there. Sponsored by, put the sponsored text, fun stuff for our show. Summarize one paragraph non-marketing content for the episodes like favorite TV shows, music and tech gear mentioned in the shows.

Then we give it the final recipe, the execution. Step one, read the ICP. Step two, read the episode data. Step three, create the summaries for each episode using the ICP as directed. Step four, assemble the newsletter following the template and use the configuration information, the appropriate places in the template. Step five, produce the final markdown of the newsletter in total, unabridged and complete.

This prompt is almost 200 lines long. It is 8,400 characters, 1,200 words. What we’re doing with prompts like this is we are way past “Summarize this article,” whatever.

Christopher S. Penn 21:22
This is a piece of software. It’s written like code.

John Wall 21:26
Yeah, no, that’s a, it’s amazing how it’s the entire baking list for the whole thing because that is basically the same process I’m following, but it’s codified and ready to go.

Christopher S. Penn 21:36
Exactly. And I think that is the perfect analogy. This is a, this is not just a prompt, this is a recipe. We’re going to give it some ingredients, the ICP and the episode data files, and we’re going to say, “Here’s the recipe, bake this recipe.”

So I’m going to go ahead and take this, and let’s go to a, let’s start a brand new Google Gemini session here. I’m going to take this whole set of instructions. I’m going to put that in system instructions. That goes right there. This will work with some modification in chat GPT, but chat GPT only allows 8,000 characters, so you’re going to have to do some modification of the prompt if you want to work in chat GPT. I also use Gemini because Gemini can hold an awful lot of data, as the model specifies.

Christopher S. Penn 22:21
We need to give it some starting information. We’re going to give it the following information. We’re going to tell it this is for August 2024. This is for Marketing over Coffee. These are our sponsors, and this is the text. And I copy this right off the webpage. That’s that information.

Let’s then go ahead and go into Google Drive here and pull out the Marketing over Coffee ideal customer profile and the Marketing over Coffee episodes, the episode text. This now works out so far to 52,000 tokens, which is about 35,000 words. And now we can either sit here and wait for the timer to run out. This will take this when I run this normally. It takes two-ish, some minutes to spit this out, although sometimes, depending on how Gemini is feeling, you can start to see something around the 25-second mark.

Christopher S. Penn 23:18
But what you end up getting out of this, oh, look, here we go. It says August was a busy month. Recent episodes, here’s the title. So far, so good. It’s Katie. Robert returns to the show, discussing how to use AI and the ideal customer profile and create actionable insights that marketing leaders can use to drive strategy. Chris and John discussed Meta’s release of its open-weight llama to AI model episode seven. John shares a classic interview with Ryan Holiday, Growth Hacker Marketing. We have dynamic pricing and the concept of expiring emails and new formatting options in Gmail. Alex McAlpine shows how Giphy is more than a GIF library CDP functions, John and Chris on your CDP crystal Carter on SEO and Wix studio the Future of Onboard AI, which that was an RWDC episode.

Christopher S. Penn 24:08
Cassie Bruno with the story of Gen Z parents, sponsored block sponsors. The sponsor text is correct. Fun stuff. A wall of water bottles shocks open run pro, Katie loves her new Sonos era home theater system and Apple Fitness Plus.

John Wall 24:25
That’s not, I don’t think Katie has a Sonos, though. That one. Hallucinate. I think we did kick around Sonos, but I know she doesn’t have one.

Christopher S. Penn 24:34
In her, I gotcha. So once this is done, you have a couple of choices. You can copy the Markdown format file, which is little markdown text. This is something that pretty much every system in the world can speak for interpreting the content. Or if this is good enough as a first draft, I’m going to start at Google Docs because it’s close to a WYSIWYG editor. You can right-click here and choose copy rendered and go into Google Docs, and it will take the formatted version and pop that into any WYSIWYG editor. So it’s styled, it’s got all the emoji, it’s got the links already pre-baked. And so now you’ve got your first draft of a newsletter.

John Wall 25:24
Yeah. And that level of markdown there, that should dump right over to Ghost, too. So that’s a huge win right there. That’s like all because it’s got all the links pre-formatted. I don’t have to. Around with any of that stuff. Yeah, that’s nice.

Christopher S. Penn 25:39
Exactly. So what we’ve got now is we’ve basically taken the ICP data, we’ve taken the podcast data, and we’ve taken our gigantic, huge recipe for a newsletter and put the three of them together, put it in the Gemini oven, and it bakes this thing up.

Now, here’s what’s cool about this. The way we wrote the prompt was the prompt is relatively agnostic, which is why we have to specify upfront. Like here’s what the show is, here’s who the sponsors are and things. So when you go to do future versions of this, if you’ve got the data, you’ve got the transcripts and things, you could just change it to, September 2024, hand at the new file, and say, “Okay, go.” And now you’ve got the September newsletter or the October newsletter. So this ran in 73 seconds, which is less than an hour.

John Wall 26:34
Yeah. That’s getting, timing my day back. That’s a wonderful thing.

Christopher S. Penn 26:40
Time and day back gets you that, that maybe not as attractive first draft. And if you don’t like the format of the way that we built this, you edit that in the prompt.

John Wall 26:52
Yeah, right. I changed it in the output. Yeah. Because this is one of those things you can totally see where the first three or four times through, I make a list of all the edits that I’m making, and then go back and just put all those in the prompt, and it will just spit out perfect when I’m done.

Christopher S. Penn 27:06
Exactly. So you would have it spit out in the prompt, and then the prompt will be formed. So if you want it like H two headings for the title stuff, you could obviously have it do that instead of having it this way. I like to do it this way personally just so I can verify that it’s actually getting the correct information. But after a few runs, it’s totally fine.

John Wall 27:23
Right? Yeah, yeah. Once you know it works, then you don’t have to spend as much time looking.

Christopher S. Penn 27:27
Exactly. So this, if I had to guess, this would probably take the hour, and I actually guess it’s probably closer to two hours per newsletter issue.

John Wall 27:35
Yeah. To get it from, first note, all the way to, “Okay, I can push the send button now.” Yeah. Two hours is even. Maybe a little more on that, depending on how ugly or broad it gets.

Christopher S. Penn 27:48
Exactly. So this would probably shorten that down to maybe 15 or 20 minutes because I’m sure this still, you’d want to add some images and stuff, maybe probably have a more exciting title than the August 2024 newsletter, but it’ll get you that first punch through.

John Wall 28:04
Yeah, making those edits are easy once you’ve already got the meat done. It’s simple to go and make a couple of tweaks. That’s a lot easier than coming up with each of those paragraphs separately.

Christopher S. Penn 28:14
Exactly. So that is the process for building that out. And if folks are interested, if you are interested, I will put a copy of the newsletter prompt itself in our Slack community. If you go to Trust Insights AI analytics for marketers, we’ll put it there, we’ll leave it there. It goes away automatically after 90 days. So you have to be an active member of the community. Free to join again. So Trust Insights AI analytics for marketers, you can get that there.

Now here’s the big question: Could you use generative AI to do newsletters? And we have to always bring up this reminder.

John Wall 28:59
Whether or not they could, they didn’t stop to think they should.

Christopher S. Penn 29:03
So from that perspective, John, should we do this? Is this a good idea?

John Wall 29:08
Well, yeah, because this newsletter will not tear through the village, shredding people. So it’s, I’m not concerned for safety, and it’s. And what we’ve talked about, and Katie, it’s too bad Katie’s not here. It’s the, human in the loop, having the process and having the peas in there. I would babysit this every step of the process, but there’s just no doubt that it takes a lot of the ugly paperwork out of the front, a lot of the ugly copywriting. And so, yeah, it’s definitely worth doing.

Christopher S. Penn 29:35
Yep. And there are prerequisites. So every episode has to have a transcript for this to work well. But once you’ve got that, then it’s relatively straightforward afterwards. From your point of view, when shouldn’t you use AI for this sort of thing?

John Wall 29:53
I think the only risk is like, you never set it up so that there’s no human checking at any point of it. Like it just spits out at the end of the process, and nobody looks at it. You’ve got to have a check and balance in there. But otherwise, there’s no. Yeah, I guess.

And then the other one would be, if you’re working in medical devices, you don’t want generative AI playing with your pacemaker or anything like that, but otherwise, yeah, it’s just, it’s definitely an opportunity to get the grunt work out of the cycle.

Christopher S. Penn 30:24
Yeah. Renee says she’s willing to.

John Wall 30:29
Maybe be sub-two-hour marathon with, AI-optimized heart rate.

Christopher S. Penn 30:34
Exactly. I think if your newsletter is kind of like the way mine is, the way Katie writes, Ann Hanley’s, where you have a very heartfelt, human-led letter part of the newsletter, that’s probably not as good a candidate for this because you’d be essentially asking generative AI to just write that whole opening block for you. You could, if you’ve got it in a different format and then just have it, clean up the grammar and stuff. But having it write it out of whole cloth, probably not a candidate. Where this is a really good idea is my pandemic newsletter. So it’s my least favorite newsletter. I wish I didn’t have to write it at all. I wish it would go away, but until that happens, that’s not going to be the case.

Christopher S. Penn 31:24
But what I’ve started doing that one is I’ve had it doing all the summaries of the news stories because these news stories are very complex academic papers. These are things that are 20, 30, 40-page studies, and condensing that down to a paragraph without losing key pieces of information is something that AI is just better at doing than I am. I’m not a doctor, I don’t have a Ph.D. in anything, and a machine is much better at taking the existing content and shrinking it down.

So this would be an example of a really good candidate for a newsletter. Any kind of roundup newsletter where you’re just rounding things up, AI is a great choice. Anything that is purely original content, probably less of a good choice.

John Wall 32:15
Yeah, that makes sense. Like you said, this is perfect. With the transcript, there are literally piles and piles of data that need to be combed through. That’s perfect to set the bot to do it.

Christopher S. Penn 32:22
Yeah, exactly. You can see here, this is not stuff, this study is like, “Okay, here are these particular receptors on lymphocytes.” Like, yeah, I should not be writing about them.

John Wall 32:36
Perfect boil down.

Christopher S. Penn 32:38
Exactly. Perfect boil down, one paragraph, and you get to the goods. The other thing, and I think this is worth pointing out, you could see here in this is yesterday’s issue, I’m disclosing, “Hey, here’s how I am using AI.” So that it’s clear for people like, yeah, this portion of this newsletter is generated by a machine. Here are which ones are so that people are not surprised if someone were to stick it into an AI contact detector. And that day it worked, which, it’s a flip of the coin these days. We could say, “Yeah, of course portions of this are AI-generated. We disclosed that.” So you want to make sure that.

John Wall 33:16
You do that. Yeah. And you’re not going to read 5,000 pages of text for the next launch letter. That’s exactly.

Christopher S. Penn 33:23
Exactly. So to summarize the human way, if you want to use AI for newsletters that are great candidates for this are roundups. Content curation is a perfect case study for use. A case for this. Any kind of summary like the month’s stuff. If you’ve got a blog and you’re posting on your blog every single day, having even a weekly newsletter where you use AI to just wrap up those blog posts and present them in very short summaries, would be a great way to use generative AI.

If you are creating very strong, personality-driven, human-led content like an actual letter, AI is not as good a choice there, and make sure you disclose it. Any final thoughts, John, about using AI for creating newsletters?

John Wall 34:14
Look forward to the next automated episode in your inbox that we’ll have some fun with this and hopefully won’t break too many things as we go.

Christopher S. Penn 34:23
Exactly. Again, if you want the prompt that we used, it’s going to be in the analytics for the marketer Slack group as the only place it’s going to be. I’m not going to put it anywhere else, although I’ll probably stick a copy in the paid course. But that’s the place it’s going to be. So we will catch you all next time, once Katie is back from being lost in the woods, wherever. Thanks for tuning in, and we’ll see you soon.

Thanks for watching today. Be sure to subscribe to our show wherever you’re watching it. For more resources and to learn more, check out the Trust Insights podcast at TrustInsights.ai/tipodcast and a weekly email newsletter at TrustInsights.ai/newsletter. Got questions about what you saw in today’s episode? Join our free analytics for marketers Slack Group at Trust Insights AI analytics for marketers.

Christopher S. Penn 35:12
See you next time.

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