The New Era of PR: Artificial Intelligence and the Preston Platform

Ready to revolutionize your PR game? Join us as host Peter Woolfolk chats with Steve Marsenuk, Managing Director of Intelligent Relations Public Relations, about their groundbreaking platform, Preston. You'll be amazed at how this AI-powered tool empowers small PR teams to secure media coverage and amplify their brands like never before.

We dive deep into the world of AI with Steve, exploring how Preston's automated pitch-writing capabilities and real-time analytics are transforming the PR industry. Learn how this innovative platform creates a multi-dimensional perspective of content creators and uses vectorization to match client pitches with the journalists most likely to cover them. Say goodbye to generic pitches and hello to a tailored approach that not only increases your success but enhances the overall experience for journalists. Don't miss this opportunity to gain a 360-degree understanding of content, elevate your PR efforts, and to benefit from a Special Offer to try "Preston" at the end of the episode.

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Transcript

Announcer Speaker-1: Welcome. This is the Public Relations Review Podcast, a program to discuss the many facets of public relations with seasoned professionals, educators, authors and others. Now here is your host, Peter Woolfolk.

Peter(Speaker-2): Welcome to the Public Relations Review Podcast and to all listeners all across America and around the world. Question is the current Public Relations Agency model outdated? My guest today believes so. As a result, he and his colleagues have launched Intelligent Relations Public Relations, a new startup that believes that they have an exceptional fix with their new PR platform called Preston.

Preston enables growing teams the opportunity to win media coverage and amplify their brand while delegating support tasks to a PR pro. In addition, your firm gets a dedicated PR professional, committed to your success, to execute all of your media outreach, helping to coordinate your interviews and to execute all of your campaigns. A very important feature of the Preston platform is your access to real-time analytics about your campaigns. Now founded in 2020, they have quickly grown to over 50 team members distributed across 14 countries in four continents. Within this short time, they have already helped a global client base to achieve impactful media coverage in all types of media. So joining me today, all the way from South America, is Steve Marsenuk, managing Director of Intelligent Relations. So, steve, welcome to the program.

Steve(Speaker-3): Thanks for having me and appreciate the welcome and the thorough introduction. 

Peter: Well, look, let's talk about Preston. From what I have read thus far about it, i'm actually excited, so I'd like for people to hear exactly how we go about doing what you do. 

Steve: Yeah, absolutely So. First of all, i've been listening to a couple of recent episodes. You've done an artificial intelligence and it's clear that both you and, it seems like your listening audience, are rather up to speed with some of the transformative things that AI has done and will continue to do for the PR industry. So we actually, as you mentioned, we started back in 2020 because we saw some of the artificial intelligence that was coming up, early versions of GPT, which is now, you know, chat GPT, and we're just seeing that the PR industry was a perfect application for some of the AI technology that was going to be emerging at that point over the next few years and, you know, sitting here in 2023, emerging now. And so I think that that's where our jumping off point was for Preston is what would be the technology, the AI technology that would empower more intelligence, streamlined workflows, improved outputs and to help facilitate many aspects of the PR process. 

Because,  I mean it has so many features that PR people really need. And let's start at the top about that. Preston has automated pitch writing included. Talk about that a bit. 

Steve: Yeah, absolutely So. I've been running a PR agency for about five years or so prior to help and start intelligent relations, and we started in year one. spent about nine months, 12 months, just trying to reinvent the process of what it takes to media outreach to the right folks with the right message and the right journalists who care about this, pitch these topics and then manage your relationships with them. 

Try to kind of reinvent that from the ground up. And that's how we, you know, that's how we started from a jumping off point. So I so, from the pitch writing perspective, i'll say just high level there's. There's multiple technologies are built into Preston. I'll drill, and very happy to drill, into the pitch writing side. So we have media monitoring which identifies journalists and everything they're writing about and to build a smarter journalist database. Then we have the pitch writing capabilities, which understands a given client and writes, is pre-trained, with pitches that work based on, you know, success through the platform and recursive learning based on what we're seeing as gang responses. And then we have the follow up, tracking and transparent reporting process. So those are kind of the pillars of what's baked into the platform From the pitch writing perspective. You know, i just listened to your last episode, one of your recent episodes, about GPT and some of the uses of GPT in for PR professionals. I think you know your guest absolutely nailed it, and a lot of the things you talked about from ideation to subject lines to preparing messaging briefs for clients all of those things are really decent and really strong use cases for out-of-the-box AI technology like chat GPT, like Google's Bard, something like that. 

What we saw with Preston for the pitch writing tool is that out-of-the-box solutions are not well designed for very specialized functions such as what we do in the PR industry. So, pitch writing, you could go to chat GPT and say, hey, write a pitch on this topic. But the problem with an out-of-the-box solution is it doesn't know what works. It doesn't know what good is. It doesn't know the client that you're pitching on behalf of. It doesn't know the news. Chat GPT was I had this knowledge cut off as, i think, September 2021. And so it's an imperfect tool for what's really the bread and butter, daily activities of a PR pro. 

So instead, what we did is we built a framework where Preston has individual accounts set up for any individual client, where it learns that company. It understands their messaging, it understands what they care about, what they do, their areas of expertise. It's pre-trained with their leadership, and so it knows all that and it can go into a cold solution and saying write a pitch about this. Oh, by the way, our CEO is so-and-so and they do these topics, et cetera. It knows all that. They pre-trained with pitch examples that have worked. It's pre-trained to know what the standard is And so by having those things, by having a custom pre-trained model for a specific client, knowing what the standard is of what's likely to get a response, you're able to get really good outputs right out of the gate. Again, our thesis is that you always want to have a professional who knows what the outcome should be. They're able to review and obviously fact check, not sending anything out without that approval. But it's certainly a great jumping off point for anyone who's using a gender to day high to write pitches. 

Peter: Well, i can certainly see the benefit of that because, as you said, chat GPT just Regurgitates what it can get its hands on. It goes up and looks for stuff that fits What you've asked for and then gives that to you. As I hear you said, your program Understands what it is your client wants and how they go about it, so it can better frame and recite, if you will, things that will better adapt itself to their needs. 

Steve: Yeah. So, for example, you know, we have a data privacy client on the platform And, rather than having to reeducate The your pitch writer each time Oh, by the way, the CEO's name is is Rob and their website is this and here's their service offering That just comes standard. So it's. It's really like building a custom set of AI tools for any client and it sets up and learns instantly, and that's one of the pain points I know you're. You know, do folks listening, or likely were, that somebody does take a little bit Of a learning curve to get up to speed with what a new client does, especially if they're in a niche or in highly technical industry. This helps to accelerate through that learning curve and let's you know, ensures that the content you're creating is on message And on point from from pitch one. 

Speaker 2: Mm-hmm. And now is this also an overview of? when you say that I guess Preston empowers anyone to win their own media coverage? Is that built into the fact that your pitches are much more directed, better and more accurately because of the way you put them together? 

Speaker 3: So I would say the right way to frame what what we're doing from my perspective is AI assisted. So if someone wants to write a pitch, you have a PR professional working in house, a PR consultant Or you know talented marketing professional knows what they're doing if they they know their messaging, they know what they're trying to communicate. This is a really solid set of, say, training wheels to help them get out the door. So we're seeing that the folks were most successful in our using Preston for themselves are our folks who have a strong PR background. They have a marketing background. You know they understand what good messaging is and they can use a tool to jumpstart Polish and work through. You know the process of sending a pitch from Ideation through to response a whole lot faster than they could without. 

Speaker 2: Without that now Is there this have you made a distinction between, let's say, the some of the smaller firms that might have only three or four, five people there, as Compared to some of the big national firms, and in some cases a few might even be international? Can you work with both of those extremes with this? 

Speaker 3: The target market for us really is. It's designed for the, the solo practitioners, the small firms. It's a great solution for those folks because you want to set up a dedicated account for each, each one of those clients. It's people who maybe they don't have the entire infrastructure baked in. They don't have, you know, the team of analysts, they don't have the team of folks who are, you know, helping with with the ideation. They need, you know, extra hands, press and metaphorically helps them to have that and helps them to, you know, perhaps compete with, with teams that have more resources. So those are the folks who, when we're we're hearing feedback from clients, those are the folks who are our biggest fans and biggest promoters now in terms of Because I had a brief glimpse at some of your list of reporters How extensive is that? 

Speaker 2: then? let's sort of maybe focus on the US, but is how extensive is it in terms of either just gross numbers or by areas that they cover? Just wondering how you put that one together. 

Speaker 3: Yeah, absolutely So. The the media database will talk about breadth and we'll talk about that. So, in terms of breadth, number of journalists who in the hundreds of thousands of journalists and it's growing every day and obviously there's Because we mentioned in our online presence, expanding to other platforms soon the way we see it and you know no news to anybody here is that The media landscape is continuing to fragment. There's someone who has is a, is a writer, maybe a freelancer, for many publications and have their own sub-stack, substack and have a podcast, and so building a centralized platform That's able to take all that information about all the content they're creating on all of their platforms to create a really deep and three-dimensional view of that influence or of that journalist. That's where we're seeing the trend goes and that's where we're focused as well And, in terms of depth, that's where we're, frankly, most excited. So a lot of the media databases out there are. Obviously they have a wide number of folks. They have great tagging on there of the journalists and the editors in their database. We're going a step further. Rather than putting folks into predefined categories, we're just sucking in all of the content that these folks are creating and creating. The technical term is vectors of who these folks are and creating a much more three-dimensional, four-dimensional it's a multi-dimensional perspective of who these folks are and what they're creating, beyond just putting someone into a box. 

Speaker 3: Say, you have a pitch about your client has a disagreement with an approach that Elon Musk is taking to business and you want to find journalists who are likely to care about that. Well, we have a method that allows you to look at the pitch in the client and understand what their take is and then map that, using variations of vectorization, to the journalists who, based on all their recent coverage, are most likely to cover that. And that may or may not be a journalist who's covered Elon Musk in the past, because that might be about his personal life, it may be about his stock price, or it may be about someone whose journalist most likely to care about that, maybe someone who wrote about Bill Gates or Jeff Bezos, like folks who literally the language doesn't map, but on a concept basis, these are the journalists who actually care. So it's kind of leapfrogging the filtering process and the tagging process on topics and themes in doing a more direct match between what's at the heart of this pitch, what's at the heart of this journalist and making the connections based on that. And I'll say there's one other layer to this which is beyond just thematic appropriateness. 

Speaker 3: We think it's important to understand what the journalist replies to. So, for example, does the journalist respond to pitches about interviews? Do they respond to reviews You know we should review our product Do they respond to a written Q&A? Do they like receiving announcements or not? These are things that typically, pr professionals would have to make their own custom notes about what that person would like to receive. 

Speaker 3: You know, that's essentially recursive learning. That's taking the feedback across all of the pitches that are being sent out and understanding positive responses, negative responses, what's getting their attention, and so the intelligence and that relationship, like what was previously had to be looked at as a i learned this about this journalist. Now we're able to do better matching based on what they actually like, and so the end outcome should be better targeted pitches and, hopefully, a better experience for the journalist on their receiving end, because the platform knows that well, this person only covers Tesla's stock price, not their company developments, and so therefore, you know, make sure your pitches are actually mapped on on those criteria that's interesting that you describe that sort of minutiae, if you will, that it's able to define that they're more interested in stock prices as compared to something else, being able to disseminate that difference as they decide. 

Speaker 2: I don't want to say category, but how to pitch or not pitch an individual report. I think that i find that rather fascinating that your system can pick up those new nuances and and pass them on yeah, well, it's, it really is. 

Speaker 3: It's deconstructing with our team. What are the things that our internal PR team cares about, what are the things that matter? and so we're looking at you know many, many thousands of pitches and responses and what ended up resulting in media coverage, and we're realizing like, okay, that's a distinction, that's something that should be baked in and so every time we're drawing this distinction that becomes part of you know new set of ai algorithms to start intelligently tagging folks and having a deeper understanding. 

Speaker 3: So, same way a pr pro would, you would learn about what folks you respond to and don't respond to. The platform is able to capture and build that intelligence into the system okay. 

Speaker 2: Well, since you mentioned that, let's talk a bit more about media monitoring. How many different things are programs and platforms are you listening to and what are you looking for? how do you just to discriminate, how do you break down information and decide where should it go and whom should it go to? 

Speaker 3: sure. So our platform is is, by design, it's content agnostic. So that's, you know, a way of saying the, a transcript of a podcast versus an article, versus, you know, a tweet or a caption on a on a social media post. All of that is is content that can be fed in to the platform via apis and analyzed intact back to the folks who are creating that content. So, in terms of sources, we use a number of different data providers to be the raw, you know, to provide that raw content, and that's actually one of the things that made this a very good moment for creating. 

Speaker 3: You know, communications technology is that the ability to process massive, massive amounts of data is now possible to scale. It wasn't previously. You can now analyze, you know, we got in the last couple months, 35 million plus articles in our database. Wow. We can process all of those in, you know, depending on the analysis, in hours in a day, and we can process all data flowing into the platform real-time along all those kinds of criteria, and that's just that. 

Speaker 3: That's possible now and it previously wasn't. So that's where we're at. That's where we're going to continue to go is just to. In order to do true 360 understanding, you need to be able to absorb and process all this data and we think that you know as it gets harder and harder for an individual to keep up with you know a journalist's moves or an influencer's content across multiple platforms. Technology will also be part of the solution to that because it can keep up and it helps to make the jobs of the pros responsible for running media coverage, helps make it easier for them to keep up so talk a little bit now about the campaign analysis. 

Speaker 2: Once you have put together a campaign for a client and let it go, talk about what you're measuring and the information you're getting back to give to the client to let them know about the performance of the campaign yeah, sure. 

Speaker 3: so the campaign analysis. there's some obvious statistics that would make sense, similar to, like an email marketing campaign let's assume it's all you know, email pitching, so everything from number of sends and open rates and click through rates and response rates, things like that. Further, we're tagging each of the pitches, so the pitch itself will have, you know, i think, somewhere between like 15 and 20 different dimensions to it, attributes to it, such as it kind of alluded to these earlier, like the whether, if it's an announcement, if it's an exclusive, if it is asking for a review, that type of thing. And so we're tagging each of the campaigns to understand what they're about, above and beyond the themes and the topics. So that's happening on an individual level, like an individual campaign level, and that's happening on a larger level, so across all the campaigns, helping to receive feedback from what journalists are responding to. So a campaign, yeah, it happens on that campaign level understanding. So your campaigns about, you know, announcements seem to result in lower response rate than your campaigns about product reviews, for example. 

Speaker 3: You can also see based on responses. you can see this journalist gave five positive responses to you over the last six months. Therefore, this is one of your top relationships that you've built, or this publication, as you've been in touch with three journalists at this publication. therefore, that's one of the publications where you have essentially cultivated a relationship, so kind of. I mean there's a lot of dimensions to you know the feedback that happens, but that is essentially the recursive learning. You pitch something out, the data comes back, based on responses, opens and clicks and ultimately, coverage, and that feeds into data that hopefully is useful and actionable for the users of the platform. 

Speaker 2: Now you've mentioned the fact that you're basically a worldwide. How often do you update your list of reporters? 

Speaker 3: So we have a technological approach and a human approach to updating the database. So we have a team of folks who are behind the scenes analyzing the journalist database. Every time there's a bounce, for example, we go in and we update the data with update information about where the journalist is working. So there's that side of things. And then, because our database is built essentially from content, first we're identifying all the content that's coming in and maybe it'll identify that there's a new journalist you know John Smith at this publication. He's written 10 articles in the last month and that'll prompt one of our teammates to go and update. There's kind of a number of feedback cycles that trigger our technology or our team to go and find updated contact information for these folks. 

Speaker 2: Well, as we begin to come closer to the tail end of things, tell our listeners how they can get their hands on this Preston platform that you've started. 

Speaker 3: Absolutely IntelligentRelationscom. You can go there, you can book a demo. We'll give you a full walkthrough. We've got a great customer success team Happy to help you get set up, set up your first campaigns, and we'd love to have your listeners give it a spin. 

Speaker 2: Okay. Well, let me ask you now is there anything that you think that we should have covered today, and if so, let's have it, so we can have a full picture of what it is you do. 

Speaker 3: Yeah. So I would say the technology that's coming presents a lot of opportunities. I think that there's an understandable concern about how this affects the work of PR pros and the ways that have worked for a very long time. I think that if your job or if your firm operates strictly on the basis of, we can build a great media list, but that might not be the model that continues well into the future. 

Speaker 3: But ultimately it takes professional and it takes someone who knows strategy to understand what good looks like, to understand what's in the client's best interest. And so the juicer, more valuable work that we've all made our livings doing is going to continue, And it's those who adapt to the new technology and adopt it in their workflows that will probably end up getting the competitive edge in the next couple of years. But this tech is coming and it has the opportunity to accelerate a lot of things really quickly And so really encouraging whether it's us or other technology providers in the space, really encouraging folks listening to give it a spin, to try some of this tech, because it could offer real meaningful change the way we see success for our clients. 

Speaker 2: Well, steve, i want to say thank you so very, very much. I have certainly learned a lot, and let me encourage my listeners to actually go read a bit more about this, because once I read what was going on, i had to reach out and get Steve on this program to let you hear about it, and I think once you read more information about it, you too will become excited about this. Let me once again thank my guest, steve Marcinich. He's the managing partner from Intelligent Relations, public Relations and their new platform, preston. And again to my listeners, thank you for listening. Please share this episode with your colleagues as well And join me again for the next edition of the Public Relations Review Podcast. 

Speaker 1: This podcast is produced by Communications Strategies, an award-winning public relations and public affairs firm headquartered in Nashville, Tennessee. Thank you for joining us.