Episode Transcript
[00:00:00] Ryan Charles: I love AI.
[00:00:00] Elizabeth Gearhart: I love and hate it.
[00:00:02] Ryan Charles: It is a double edged sword right now for sure. That really acts as like the central brain, the Ultron, if you will, for a source of truth on our clients and the work that's being done. What would have taken me like 80 hours is now 8 hours. It's absolutely mind blowing.
[00:00:16] Richard Gearhart: When I read it back, it sounds like me.
[00:00:17] Elizabeth Gearhart: You have to constantly fight with these things to get it the way you want.
This is Real AI Use Business Owners Roundtable with hosts Elizabeth Gearhart, podcast consultant, marketing expert and PhD researcher using a every day. And Richard Gearhart, entrepreneur, seasoned business owner and intellectual property attorney specializing in innovation.
Here's how real companies are using AI right now. Welcome to Real AI Use Cases.
I'm Elizabeth Gearhart.
[00:00:45] Richard Gearhart: And I'm Richard Gearhart.
[00:00:46] Elizabeth Gearhart: And we have our guest Ryan Charles here with us today to talk about how he's using AI in his business, Omni Common. So welcome Ryan.
[00:00:54] Ryan Charles: Hey, thanks for having me. Glad to be here.
[00:00:56] Elizabeth Gearhart: So first of all, do you love AI or hate AI?
[00:00:59] Ryan Charles: I love AI.
[00:01:00] Elizabeth Gearhart: I love and hate it.
[00:01:03] Ryan Charles: It's true.
That's fair. Yes, it is a double edged sword right now for sure.
[00:01:08] Elizabeth Gearhart: You have a growth marketing agency, so how, how are you using it in your agency?
[00:01:13] Ryan Charles: So many ways. We're using it to automate tasks. We have a platform we use for project management for all of our clients called Notion and basically we feed all of our data in there. We use it for reporting platforms like to pull in data from, you know, go Google Analytics, Google Ads, Shopify Square, pos, all these different platforms as well, alongside of all of our meeting recordings, notes from our team tasks, all of that. And that really acts as like the central brain, the Ultron if you will, for a source of truth of basically all information on our clients and the work that's being done.
[00:01:51] Elizabeth Gearhart: I want to talk about Notion for a little bit. Have you heard of Notion?
[00:01:55] Richard Gearhart: Yeah, I've heard of it.
[00:01:56] Elizabeth Gearhart: So I was researching different places to put my brain on which LLM to put my brain in, where to put my brain. Notion came up as one of the places for your knowledge repository and I would, could not really get a clear answer from the LLMs like which one would be best for me because I have a lot of different. I have a podcast studio but I'm also doing AI visibility and marketing and so I hadn't chosen one yet. I mean, I love Claude. I mean people do like Claude. What do you think is better about Notion? Like why did you choose Notion in particular?
[00:02:29] Ryan Charles: I mean it's really the platform for the interaction to do work and for project management and to build out templated pages for different users, for our internal team, for the clients to work with us in there. But it works hand in hand with Claude, which is my favorite as well. So I'm working in Claude. It'll be tapping into Notion to pull info that's in there. Right. As well as all the other sources we have. So yeah, Notion has its own AI, but we use it hand in hand with Claude.
[00:03:02] Elizabeth Gearhart: So does it have an mcp? Is that how you're connecting it to Claude? Is it an mcp?
[00:03:06] Ryan Charles: Right, exactly. Yeah.
[00:03:08] Elizabeth Gearhart: Okay, so that's pretty easy to do. Right. So if a software has an mcp, Claude loves it because. Anthropic infinitum.
[00:03:14] Ryan Charles: Right, exactly. Just pipes it right in.
[00:03:17] Richard Gearhart: Are you able to sort of quantify yet what the impact of using Notion has had on your business?
[00:03:25] Ryan Charles: Yeah, I mean, just in terms of time spent building reports or calling up information, you know, is this on brand for this client? How many pieces of work have been delivered this month? What are the KPIs trending towards all those things? I mean, recalling that is 10 times faster than it used to be.
[00:03:47] Richard Gearhart: Does Notion do.
It's not like you're downloading something into an Excel spread spreadsheet and then putting it into to Claude. Right. You're configuring the template in Notion and then Claude is just looking for the fields and the information and then does its analysis.
[00:04:07] Ryan Charles: Right, exactly. And another use case that I'm using CLAUDE for heavily, that I'm actually more excited about is just data analysis for building an overall growth strategy and growth model and to really tell the true user journey, customer behavior in order to inform, you know, investments in different levels and channels and that sort of thing. And then the ability for me to analyze a data set, to do that, put it into a presentation, I mean, it's literally cut the time, you know, by a tenth. It's what would have taken me like 80 hours is now eight hours. It's absolutely mind blowing.
[00:04:48] Elizabeth Gearhart: So is Claude doing presentation slides for you?
[00:04:51] Ryan Charles: Mm, yeah.
[00:04:52] Elizabeth Gearhart: Is it good at that?
[00:04:54] Ryan Charles: It's great at that. I will feed Claude again a whole bunch of data sets. Often I actually do download the raw data into an Excel or CSV just because if it's constantly hitting like the Google Drive API or wherever else, like you'll run up usage really quickly. Actually better just to feed it raw data files sometimes. But anyways, I can walk through a data analysis of this raw Data that's coming out of different platforms, whether that's Shopify or Square or Google Analytics or whatever it may be, and do just a massive analysis to get a really good feel for what their growth story is. And then from that, after building out that, you know, the output of that is a master spreadsheet. That is an awesome analysis this way and that, and cohorts and LTV and CAC and all this stuff basically say, okay, now I want to create a presentation based on this. And then I just say, here's how I've done it in the past. I'll feed it another presentation.
I want to do it in a similar format. Let's show me what you got. And then basically we'll pump out 65 slide deck that, you know, shows this whole thing.
[00:06:01] Richard Gearhart: How much confidence do you have in the output?
Have you stress test any of the numbers that you've gotten against more traditional calculations?
[00:06:12] Ryan Charles: Yeah, you definitely have to do that. I would give it 90% confidence.
And sometimes it gets it wrong because it's just wrong. And sometimes you just didn't frame it well enough. Set up, you know, talking about the difference between a repeat transaction versus a returning customer and how this business thinks about it, or even creating new categories of data, you know, and KPIs, sometimes you have to keep reminding it like, hey, remember we're treating the data this way.
And that's after me going back through and seeing that it got something wrong. Or I'll say, how can this be if this was true over here, this doesn't make sense. And like, good catch. It's because of this and blah, blah, blah, you know, that sort of thing. It's a really great iterative process. But to your point, you do have to go back through and verify all the numbers.
[00:07:01] Richard Gearhart: Yeah, I mean, we've been using chat and some of the other perplexity to evaluate, you know, financial data, different statistical models, and it's squirrely sometimes. And so we started putting things into spreadsheets and, you know, keeping historical records there and then putting it into the LLM because you can't really rely on the LLM to maintain a history. It maintains a history, but it's a squirrely history. Right. And so if you constantly are updating the Excel spreadsheets and the data with new information and then putting that into the LLM and asking it to do the analysis, I think you've got a better shot at consistency. Right. And if you use the same prompt, then you know that. I think that helps too.
[00:07:56] Ryan Charles: I think you're right. Having that source of truth in something like a spreadsheet file is something smart because if you're just relying on its memory, like you'll run out of memory in a chat and then you have to move on to another one. And even if it's contextualized inside a project, some of that context is lost. And I've had to do that a number of times where this is just such a big lift to work through all of this. I will go through five chats and then, you know, have to keep bringing the new chat up to date on what we've done and I'll just drop those files in right. To like bring it up to speed. So I think that's really smart. Yeah.
[00:08:32] Elizabeth Gearhart: For the presentations, are you able to put your brand it into Claude and have it use it for the presentations?
[00:08:39] Ryan Charles: Yeah, I am. When I'm working with it just in Claude, you know, it will just pick a format that's pretty standard. Right. And so I'll do that first within Claude itself in the main chat. And it's great, you know, I can tell it I want a graph that shows this plot these two things against each other. I want to highlight these data points and then ask for suggestions of things that it wants to highlight. So I'll get the main like deck from it first and then I will fill in gaps and then rearrange things. And after it's in a place where I like, I'm exporting out to Google Slides and then adding other, maybe templated slides I have. And then I will go over to Claude Design, dump it in Claude Design, which has our brand kit and all of our brand guidelines and basically say, format this into our brand design, which comes out pretty good. But things are still a little wonky. You have to go back through and manually update some font sizes and you know, things aren't quite coming out. And that's not necessarily cloud design's fault. It's wherever you export it to after that. So. But overall, it's mind blowing to be able to have this polished product in your brand.
[00:09:48] Elizabeth Gearhart: Oh, it is. Can you put it into PowerPoint? Microsoft PowerPoint, yeah.
[00:09:52] Ryan Charles: So I normally download it as a PowerPoint file which I then upload into slides to keep it more consistent with all the styling. You can go other routes, which we're actually heading towards the route of custom web pages for presentations because Claude code makes it so easy because basically we just say take this presentation, turn it into a web page and then publish it. And now you have a dynamic web Page that has, like, animated graphs and stuff like that.
And it's all very doable, and you give it to the client and there's. It's password perspective protected, and they're just blown away. It's awesome.
[00:10:31] Elizabeth Gearhart: I love that. Boy.
Yeah. I have to submit this presentation, like, tomorrow that I'm doing, but I've been doing the slides in chat, doing the research on all the LLMs, and then having Chat do the slides. Chat's pretty good, but then trying to get it to fix things sometimes is a little tough. It's gotten better at being able to change, like, one or two things on an image that is generated. But it's not perfect yet.
But then I put it through Claude for an accuracy check, and apparently I had on there, like, these are the certifications that the different LLMs have in the enterprise versions if you're looking for somewhere safe to put your data. And the table that Gemini generated left off one of Claude's certifications. It got really mad this certification was left off. You need to redo this one.
[00:11:23] Ryan Charles: Oh, my gosh, I love that. Claude checking chat. Yeah, it's interesting. I've been thinking about how I think about different LLMs. I think about Claude for work, like, for everything. Data analysis, writing, all of that. And for some reason, Chat has now taken a backseat in my mind as like a search engine. Like, just I'll have it go search and do research.
And I don't know why it's landed that way. I mean, I kind of do. Claude was putting out better work, basically, and so I switched over to using it more. But it is interesting, you know, just in the different areas, I'm using Gemini in a different place and Claude here and Chat there, you know, that sort of thing. I don't exactly have perfect reasoning for why.
[00:12:01] Richard Gearhart: Which LLM do you both think is best for generating content? Like, you know, blog posts and that kind of stuff?
[00:12:13] Ryan Charles: None of them.
I. This is. It's interesting.
I feel like this is the hottest topic with LLMs is just AI slop, right? And now there's gonna be way more content than ever. Obviously, this is an area we're in heavily creating content marketing articles and digital PR assets and things of that nature.
And there is ways we use it for a lot of that, but for the actual writing, we still stick heavily with humans. So synthesizing the post, maybe structuring it, that sort of thing. And the reason is even the best one, which, to answer your question, I think it would be Claude still, in my opinion. And you can get it really to pump out some good stuff, but it wasn't quite on brand and it didn't have the right voice and tone. And so our writers are basically like, this is taking me more work to dai this than if I would have just written it myself. Right. But what writers do get is like, oh, I understand this topic that I've never touched before a lot quicker. And I'm using AI to make sure, you know, that we're on the right track here and setting it up correctly. And a whole bunch of administrative things that are around the content creation.
[00:13:29] Richard Gearhart: Right.
[00:13:30] Ryan Charles: It's weird. There's also a New York Times article.
I don't know if you saw this, but they basically had five different types of writing. It was like scientific, it was poetry, it was historical stuff. And.
And one was human written and one was AI written. And they had people guess which one was which. And the majority of people chose that it was, you know, human written. On most of them was actually AI. And so it's kind of wild. Like you can get really good output, but I think it takes a ton of manipulation to really get it to that point.
[00:14:05] Elizabeth Gearhart: What I do with my blog, so I have my own personal website and I have a blog on there and I don't really do anything to draw attention to it, but it always shows up now on the LLMs when you ask about me. But anyway, I do research with the LLMs and we have empirical data from the work I do for marketing for Gearhart Law. I'm Chief Marketing Officer for Gearhart Law.
And so we have our Google Analytics and other data that we collect. But I write the blog post myself and then I put it through ChatGPT and I say, optimize this for LLM search. Do the TLDL at the beginning and do the FAQs at the end and structure the data. And then I take that and I correct it and I try to. I tell it, don't get rid of my voice. Right? Because sometimes I'll say something kind of snarky and it takes it out, right?
[00:14:56] Ryan Charles: Yeah.
You want the personality? Yeah, yeah.
[00:15:00] Elizabeth Gearhart: And then I take it to Manus. So I had my website built on Manus, which is an AI agent, and I will move it to WordPress eventually. But right now it's just so easy to have Manus do everything. Manus will change it again so that I have to go in and edit it on Manus. So it's like, can you just post this and not change it? Just optimize it for LLM search. By doing the bullet points and the FAQs and stuff.
So, yeah, you have to constantly fight with these things to get it the way you want.
[00:15:27] Ryan Charles: Totally. Same thing in the presentation sometimes where I'll tell cloud design, don't change any of the words, just the design.
And it'll still change it. It's actually gotten way better at that. But I hear exactly what you're saying. And just to be clear, I do use it for my own content, like LinkedIn posting as well, but it is. I'm trying to constantly manipulate it back into my voice, right? Like I'll just word vomit on a page. Here's everything I want to say. Help me organize thoughts and then write it in my voice. After feeding it a bunch, it comes out. It still doesn't sound like me. And so then I spent a good amount of time going through inserting jokes, taking out whatever it may be, right? Just to get it there. It definitely takes less time, but even at the end of it, I'm like, it's still not quite me, but I need this to go live. So we're going with it.
[00:16:20] Richard Gearhart: I've been using it for certain content that I generate and sometimes I use a teleprompter.
I'm not using one now, but what I'll do is I might get some general ideas from. From usually chatgpt, and then I'll dictate what I think the content should be into a Word document and I use that for the teleprompting.
So I'll borrow a little language from ChatGPT, but I'll also put it in my own voice and add my own ideas and discard the stuff that I don't like.
And that way I feel like it helps me generate the content much quicker because I'm a very slow writer. It would take me a long. I'll struggle over every sentence. I want to make every sentence perfect and it just takes a lot of time. It's impractical. But if I get sort of a rough draft and then I dictate it, then it's. When I read it back, it sounds like me because it is me. That's how I've been using it for content.
[00:17:29] Elizabeth Gearhart: I said that I had all the LLMs look at my slides, so I had all of them look at it. Well, the main three that I use, right? And I had a slide in there on AI slop. Guess, Ryan, what do you think they thought of that slide?
[00:17:42] Ryan Charles: What do they say, like, no, we don't produce slop. What are you talking about this is wrong.
[00:17:47] Elizabeth Gearhart: Take this out.
Yeah, don't show this slide.
[00:17:52] Ryan Charles: That's so funny. I had a similar experience where in a slide I had like a little warning label at the top of this presentation that said, hey, I was working with an incomplete data set and I wrote in my own words and sometimes Claude hallucinates. And when I had it redo the deck and brand it took that out.
That's so funny.
Oh my gosh, that is hilarious.
[00:18:19] Elizabeth Gearhart: It's like it gets stuff wrong. So like it's giving me these pointers. It's like, you have to say this, you have to say this. I'm like, it's a presentation. Of course I'm going to explain what's on the side. You think I am stupid?
[00:18:31] Ryan Charles: Yes.
[00:18:32] Elizabeth Gearhart: Well, I think they do think we're stupid, but I think they're stupid.
It's like talking to a bratty little kid sometimes.
[00:18:39] Richard Gearhart: Uh huh, uh huh. Yeah.
[00:18:40] Ryan Charles: But that also kind of makes you feel good about yourself, right? It's just very affirming all the time. Like, yeah, that's a great idea. Well done.
[00:18:48] Elizabeth Gearhart: Well, it's almost Father's Day, right? So I got our son this card for Father's Day. I thought it was hilarious. Richard didn't really see the joke, but I thought it was screaming hilarious. It said, I typed into the Internet what is a hashtag Goodfather?
And your name came up with all these attributes, blah blah, blah, blah blah.
And I'm like. So I wrote it and I said, yeah, it was from ChatGPT. And I put this like, tried to put this like laughing emoji. I thought this card was hilarious, like, and I think it was supposed to be serious, but I love it. It was so funny.
[00:19:25] Ryan Charles: I would have laughed.
[00:19:26] Elizabeth Gearhart: So are there any other cool ways that you're using it or that you really like about it?
[00:19:30] Ryan Charles: Those are the biggest ones right now. It's just changing the game in so many areas.
But for my personal use, cases of, you know, just overall data analysis for business intelligence and insights around growth marketing, it's just phenomenal. And then being able to tell that story, because I think that's something that's so hard sometimes is getting folks who are non marketing folks just to buy into the traditional thinking in terms of branding, marketing psychology and the actual funnel and people think it's sort of voodoo, like, oh yeah, top, middle, bottom, funnel. Sure, sure. But then to actually be able to visualize how that's working of you're putting dollars in at each of these points. Right. And we're just checking to see what's coming out the bottom. And here's how it's all working in terms of customer behavior. And sometimes it's not always one to one from like we got a PR placemat, how many customers do we get right? Like, it doesn't work like that. So to be able to really pull that out and visualize that for folks has just been a game changer. I think so. It's, it's awesome.
[00:20:32] Elizabeth Gearhart: I think this has been a great podcast. Lots of good stuff there for people to think about. So thank you, Ryan. So your company is Omni Common and who are your clients? Who do you work with?
[00:20:44] Ryan Charles: Yeah, so we work with e commerce SaaS and marketplaces doing anywhere from 5 to 50 million who are looking to hit that scale up phase. And then we actually have a local marketing arm that works with multi brand, multi location for like true omnichannel efforts as well.
[00:21:02] Elizabeth Gearhart: Okay, great. Thank you.
[00:21:03] Ryan Charles: Thank you so much for having me.
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Because the future of business is driven by AI. This podcast was recorded at the Iheart Studios in Manhattan as part of the Passage to Profit radio show.
