Episode Transcript
[00:00:05] Speaker A: Hello and welcome back to the Loop Marketing podcast. Today I'm thrilled to be joined by Koege's director of programmatic operations, Hannah Schatz, as well as Malcolm Halley, head of strategic accounts for global programmatic healthcare technology company and longtime Koegi partner, Pulsepoint. And we brought together these experts today to the table to discuss an important topic of personalizing the digital patient journey. So welcome to you both. Excited to have you here. But, you know, for our users, it's no secret that AI and machine learning, it's top of mind for all marketers these days, and that's not any exception for healthcare marketers as well. But healthcare organizations, they're increasingly turning to AI and machine learning to personalize that. Page I patient journey. So today I wanted some time to explore that evolving patient journey with you all and the role that technology plays in enhancing that journey and ways that marketers can bring an innovative but ethical approach to the space. So, Malcolm, I'd love to kick off with you and just hear from you on how patient research habits have evolved from your perspective in the digital erade. So would you love to chat about that and, like, resources that are used?
[00:01:26] Speaker B: Absolutely. It's wonderful to be part of this very special podcast. Pulse Point teams appreciate our partnership with Koeige for a long time. Excited to kick us off with this topic. So, patient research habits in the digital age, I think the first thing to really talk about is how much that they have truly, truly changed.
And if we can take maybe just a quick step back, how we got here from a technology standpoint, and I promise I'll bring this right back to the patient research habits. But technology has a history of rapid evolution. So if we think back to kind of the first ever technology that there ever was, it was literally just like stone tools. Like, people just had this idea, like, all right, we're going to rub two stones together until one of them is really sharp, and then we're going to use that for hunting, to cut down trees and fruits and things like that. That was the first technology ever, first widely recognized technology. And that was five and a half million years ago. Fast forward to about five and a half thousand years ago the wheel was invented. That was obviously a major innovation in technology, but it took over five and a half million years to get from just like primitive tools to the wheel. And then five and a half thousand years after that, we get the first laptop. And that was maybe 40, 50 years ago, something like that.
This thing didn't look anything like a laptop. Looks like today it was this huge, unwieldy, suitcase looking thing that you would unfold.
But the whole idea here is that technology began moving very, very slowly.
Took five and a half million years to get from one thing to something else, and then 5000 years to get to the laptop. And now, since then, technology has just been evolving more and more and more rapidly at a very exponential pace. And so bringing this back to kind of patient research habits, with all the digital tools today, patient research habits are changing quite rapidly as well. We find that people are taking deep, deep, deep advantage of the different tech and the tools that are available to them. And from a research standpoint, what we see is that patients ultimately, they're using the tools at their disposal to make their own informed decisions. So whereas in the past, they didn't really have that many channels, that many avenues, they had professional resources, they had people close to them. But what we're seeing now, more and more, is that they're pulling together all the different types of information that they have in order to make an informed decision and really find out what it is that they should be doing next. So if we think about what commonly starts a digital patient journey today, the answer that I give now would have been very, very different three years ago, five years ago.
But we find that most patients, from a digital side of things, they begin their journey with search. So using things like Google Search, Bing search, much more recently, of course, AI chat tools to really start that journey. And from there, the journey can go in lots of different directions. And I think we'll probably touch on this later and throughout the podcast. But ultimately, what's happened is that people have gone from having not many resources to find out about their digital, or to use digital in order to kind of understand what's going on to almost, in some cases, an unwieldy amount of resources. So we've gone from not having enough to having a lot. And then it's really about synthesizing it all together so that patients can truly understand, okay, what's important, what are the sources that I truly trust? How am I going to move forward in their journey? And they use these digital tools throughout the journey, often referencing similar sources back and forth, finding out exactly, okay, what are the digital sources that are truly helping me in this journey versus what are those that are kind of, okay, I'm past that stage in my journey, and now I need to focus more on these kind of direct, much more helpful resources.
[00:06:02] Speaker A: Yeah, I mean, that makes complete sense to me. I think that doctor Google is a common practice popping on WebMD, anytime that you have some sort of symptom and trying to figure out, okay, is it this? Is it this? Do I need to go to the doctor? Can I, you know, just take some. Some cold medicine and be able to fix it myself?
I think that it's definitely a blessing in a lot of ways for the consumer, and it's helpful for building that bridge to the healthcare provider as well. I'd be curious to hear what you guys think in terms of the information that is prioritized. So, you know, I mentioned, like, WebMD as a source of great, great information.
There's a lot of thought leadership being shared by different healthcare institutions.
So what sort of information are you seeing consumers prioritize, whether it's, you know, qualifications from providers or, like, reviews, or are they going to their insurance providers, or how are they seeking out that type of information?
[00:07:07] Speaker B: Yeah, so, like you said, there's. There's all different kinds of information out there, and it's really, in a lot of ways, up to the individual patient to help prioritize what is most important. Where is sort of the source of truth coming from. So from, you know, there's different types of conditions, of course. So there are some where the journey is going to be very, very short. So I have a headache. Hey, search, what can I do to help alleviate this headache? The answer comes pretty quickly. You might try a product that's used to relieve headaches. If it works quickly, that's sort of the end of the digital journey. That's it. A lot more conditions are way, way, way more involved. So let's say the headache doesn't necessarily go away. Now you start to really look and see, okay, what happens if I have a headache? Advil didn't work, et cetera. Now what else do I do? So what we kind of see is that while the digital search might begin or the digital journey might begin with a sort of basic search, it really depends on the condition, the severity of the condition, and really the overall patient, because everybody truly is unique. We see that there are certain publisher websites, for example, that are used at the very beginning. They're going to be very, very high level in terms of what patients will expect. They're ultimately, for the most part, gonna say, talk to your doctor. And many, many patients are going to do that very, very quickly. However, we're seeing more and more that prior to that doctor appointment, patients really want to get a jump start on the journey. So beyond just standard publishers who have or trusted medical organizations from an educational standpoint, you know, university studies, things like that. What patients really want to find is somebody who's been through that journey before. So somebody who's actually had that headache, it didn't go away. Then what was it? So, yes, if I'm a patient, I'm still going to eventually talk to my doctor, but before doing that, I want to know what happened to other patients who had these headaches and they didn't go away. What was their ultimate journey? Because what that's going to really do is harness the power of technology and collective learnings from people all across the world, really, in order to best inform the patient what might be coming next. We all want to be very prepared for the journey, and we don't want to have to see six or seven different doctors. If we can first identify, here's somebody who's been through that experience, got maybe misdiagnosed or a questionable diagnosis from one doctor. We want to be able to learn, okay, here are the various outcomes of somebody who had a headache that didn't go away and kind of use that information to truly understand, okay, if I have this headache, it didn't go away. There's about seven or eight different things that I've seen. Patients who have actually been through this experience end up being diagnosed with, and they often find this information in patient forums. Reddit is probably one of the most common sources that folks go to find, those people who have been through the experience. And with that information, now they can take it to that initial doctor and say, here are the kinds of things that maybe I might have, and even more than that, they'll be able to explain their symptoms a little more deeply. We don't always know what symptoms are related, but you start to see, okay, somebody had that headache. It didn't go away, and it ended up being diagnosed with this condition. Patient looks into symptoms for that condition and starts to recognize and identify, oh, I have those, too. I didn't realize it might be related to the headache. Now I know what symptoms I should explain to the doctor. And the overall idea is to basically use all the technology, the collective learning that patients have across the world in order to figure out what should I tell my doctor, what's relevant, what's irrelevant? The doctors oftentimes are seeing hundreds of patients in a very, very short timeframe. I think most patients have experienced a doctor who seemed a little bit rushed, kind of just expecting you as the patient to tell them the symptoms and then the doctor make the diagnosis. But you don't always exactly know what to share. What's relevant. So by actually taking all this information from the various sources stemming from common publishers to academic organizations to things you might have learned from an AI bot, things like that, and now that kind of helps inform the patient. Okay, this is what I should really be telling my doctor, because that can help lead to the quicker diagnosis. I don't want to live through that three to four year diagnosis period that I read about in a patient forum. I want to get that diagnosis really quickly. I want to get on the optimal therapy so that I can get on with my life in the best way possible.
[00:12:46] Speaker A: Absolutely. So, I mean, I feel like a lot of what you just spoke about is connecting that HCP to patient journey and simplifying that path. And I think thinking about what that patient journey looks like, we have a lot more visibility into that, especially through digital channels, into understanding how patients are choosing to engage with content. And so, Hannah, I'd love to hear from you about how healthcare providers or healthcare organizations can use this information in their advertising or in organic content to improve that online visibility, attract new patients, drive loyalty, and ultimately just build a better, better patient experience.
[00:13:32] Speaker C: Yeah, for sure. I thought it was interesting. I'm going to start with this first, but Malcolm had talked about Reddit being a resource for a lot of users that are honestly just hearing from other patients who have experienced the same thing. And I feel like a lot of people get really lost in their stories. And I never thought that I would be bringing up TikTok today, but I am. And I've actually noticed a very similar thing on TikTok where it's, you know, you've got a user who's creating content around their journey, around whatever they're going through. And if you look at the comments, you see so many people that are also, like asking questions, hey, how did you first notice XYZ symptoms? What were your first symptoms and what has your journey been? So it has been really interesting to see people engaging about those topics in an environment that I just never really expected to. So I just wanted to say that. But I think as like healthcare providers and brands that are promoting helping people with their various pharmaceutical drugs and whatnot, as they were getting more comfortable showing up in digital avenues or digital places, I think patients began to also be really comfortable showing up in digital avenues, is what I'll call them.
I think with messaging, a lot of times we like to encourage even just the conversation between hcps and patients. So we're not necessarily promoting this drug, but we're saying if you are experiencing these ailments push to talk to your healthcare provider about these and we could be a solution to this. But you guys talked a lot about, like, digital touchpoints, that working with folks like Pulsepoint and Kwegi can help HCps understand the value of those touch points. And then what can you actually do with those? So how can we actually turn those into a marketing strategy or a digital campaign?
Keyword research is a big one that comes from search. Using tools like Semrush can help us identify, you know, relevant terms that patients are searching for.
So we can use those across the search campaigns, but not just search, we can use them across programmatic channels as well.
Going to like the organic side, too. It's if hcps can put an emphasis on writing really relevant blog posts and faqs and different patient resources on their websites can really help improve their rankings when people do begin to use search engines and going into KwE specialties, all of our paid social and programmatic dsps have really strong predictive analytics where we're scoring the value of every single impression that comes through the bid stream based on patient behaviors. And so this helps allow providers to predict patient needs and be really relevant in our marketing strategy. So we like, kind of like, we have so much data now, so many data points used compared to even three years ago, five years ago. So, yeah, there's a lot out there now.
[00:17:05] Speaker A: Yeah. I mean, both of you touched on how critical the omni channel experience is. I mean, like you said, maybe the first touch point is search, but then going to sources like TikTok, going to sources like Reddit, kind of those community type environments, it brings kind of that social element to things. And we also talked a lot about how technology has evolved rapidly. And speaking of technologies evolving rapidly, AI obviously is a critical topic today, and a bit of a complicated one, I would say, for healthcare in particular, especially with some information coming from the AI world, you know, if it's being prompted with vague information and things like that. So, Malcolm, I'd love to hear from you into what you're seeing in terms of AI and machine learning from a healthcare perspective and ways that we can think about using AI on behalf of our clients and our brands to, to personalize that patient experience in a way that is seamless across all these different omnichannel environments.
[00:18:16] Speaker B: Yeah, absolutely. And I think one of the first things that we sort of think about with AI, going back to what Hannah was talking about, is prediction, using analytics and data and information to predict what's going to happen next. So to give you know, a personal example of the first thing that I do when I wake up is I go downstairs, I get a cup of coffee. So now we start to see the data points, and we say, okay, when my feet hit the stairs at a certain time of morning, there's a really good chance that I'm going to have coffee very, very soon. And we can even get to a point where, hey, if my alarm went off, then chances are I'm going to be pretty tired. I didn't wake up naturally. So now we can start to predict if my alarm went off, I'm going to get the extra strength coffee. If it didn't get off, then I'm probably going to get the regular strength coffee now. Kind of bringing this back to healthcare. These are all data points. And with enough data points, we start to be able to notice patterns in the data, and we start to see, okay, if Malcolm's alarm doesn't go off and his feet hit the top of the stairs at 06:00 a.m. then he's going to have a certain kind of coffee. And if we can kind of bring that same idea back into the digital space and capturing digital behaviors, we see something very, very similar happening. There are certain digital behaviors where folks begin to repeat them over and over again, and we see certain outcomes coming from those behaviors or resulting after them. And now we can harness that data and use it to start to predict what's going to happen next. A lot of the AI comes from that idea of gathering lots and lots of different data points to be able to actually predict with a high level of confidence what should be coming next. So one of the tools that pulse point uses quite often is we have a proprietary contextual engine, and we've had this for quite some time and thrilled to have partnered with the Coeggi team to actually leverage this in programmatic approaches. But the main idea is that once we see a certain user, let's say, engaging with certain content over a period of time, we can then start to predict that, okay, this is somebody who is very interested in x, y, or z condition. And once we start to bring in those experiences over time and across devices and across channels, we can start to identify, this is going to be a user at an anonymous level or an aggregated level. This is going to be a group of people who are more likely to be receptive towards this kind of messaging, whereas this type of, or this group of people who exhibits this kind of behavior is going to be more receptive to a different kind of messaging. So one of the main ways that we leverage AI, or I should say one of the ways that we've leveraged AI for a long time, is in the idea of actually using natural language processing to understand the content of what folks are looking at. Just the fact that a simple keyword is on a web page, let's say it doesn't tell us a whole lot. We've all seen key healthcare words taken out of context, used kind of liberally. But once we start to scan and understand the entire content of the page, we're able to give it a predictive score so that we can understand. This is the kind of content more likely to be consumed by somebody who is impacted by a certain condition. And so as we aggregate that content, the prediction models start to grow over time and the algorithm can more accurately pinpoint this is the kind of person, or this is the kind of aggregated group of people who might be receptive more towards this messaging. Let's say it's about a product's tolerability, whereas this group of people, based on the content that they're consuming, are going to be a lot more interested in, let's say, brand efficacy. So we can use that data to help understand and start to segment at a large level. These folks are more likely to engage with this content and this is the kind of thing that might help them forward in that digital journey, whereas these folks, they might need a little bit of a longer time. They might be between multiple products. And that helps us understand, okay, this is the kind of content and this is the kind of messaging that might help them continue along in their journey. So from our perspective, AI, obviously lots and lots and lots of applications. But the most exciting part really is the ability to gather lots and lots and lots of data and use that data to help understand and predict what might be happening next.
[00:23:34] Speaker A: And Hannah, I know that, I mean, you've spent so many years being hands on keyboard in the platform, you've seen the impact firsthand of AI on in platform performance for many, many years, and you've seen that getting stronger, as Malcolm's mentioned. So I'd love to hear from you, not only from the predictive analytics standpoint that both of you have mentioned, but just from an overall campaign performance or digital performance standpoint, how you've seen or utilized AI and machine learning at large to improve that marketing performance and how that could ultimately benefit not only the brand, but the patient as well.
[00:24:16] Speaker C: Absolutely. Yeah. And we've always been, if you're a digital marketer, you have to be comfortable with using machine learning AI, every platform almost that you're going to use is going to have some version of machine learning, even if it's a bunch of what if statements, right? So, you know, we've definitely really been comfortable using it. We're very familiar, and this, it's a big reason why we've used Pulse point for a lot of healthcare and pharmaceutical clients, you know, being especially, you know, part of the WebMD family.
Your algorithms are ones that we can really, like, validate and trust. One, the efficacy of it, but also the accuracy. And I'm not just saying that because Malcolm is on this call, it definitely is true. So I like that you brought up the contextual offering as well.
That was one that actually had been top of mind for me. Washington being able to even break out campaigns by certain content based on who we're trying to reach and, you know, test it within hours. We know which content is driving results. And that's what's really nice about digital marketing. You don't have to run for a month and then find out it's. And through that machine learning that their platform is based off of, it's really helped with performance and getting those results and outcomes quickly so we can shift and we can literally see the revenue going in the right direction.
Outside of pulse point, too, though, you know, companies like ourselves that have even built our own proprietary AI models, if you want to call it that, helps us with various different things, whether it's creative analysis, which creative is, you know, driving better results for a new patient, which one's driving better results for someone that may have already had a preliminary consultation with their HCP, or we could use it even during planning, taking, you know, macroeconomic inputs. If you've got a healthcare system that's in different sized markets, they're going to be treated differently. How can we take a all of those economic inputs to help us decide how much budget should we put toward these markets? How are these markets going to be treated differently? And lastly, AI can also help us with the ability to develop and defined keyword lists really quickly.
There's just so many different avenues you can take with it, whether that's during planning, post campaign, or even in the middle of the campaign, too.
[00:27:08] Speaker A: You know, just kind of bringing it back a little bit to what you had said earlier. So AI obviously is the way that technology is shifting to be able to analyze things more quickly, get answers more quickly, and that's certainly a benefit to the patient. But you both had also mentioned earlier the benefit of kind of like this community learning, thinking about things like TikTok and Reddit. And that got me thinking about the role not only of social media, but also of influencers in that patient journey and bringing that more authentic touch point, that approachable feel to the brand experience.
So would either of you like to touch on how you've seen influencer used effectively and how to balance that from an ethical standpoint as well? A little bit of thinking about people who have authentically experienced certain symptoms or certain conditions and have a personal opinion about a certain diagnosis or pharmaceutical drug and how to build that into advocacy for the brand.
[00:28:19] Speaker B: Sure, I can start here.
Influencers obviously has taken on a very, its own sort of meaning here in healthcare. That's actually been a really important part of what we've all done for quite some time, especially with healthcare marketing. So beginning on the HCP side, for example, we call them key opinion leaders kols so these are the physicians who are well respected in their communities, and therefore their words mean a lot, and their expertise and everything that they've drawn on, that means quite a bit to the other physicians within the community and also patients, of course. But we tend to see that physician, key opinion leaders, or really those who influence other physicians based on their expertise, based on their area of study, they've actually had quite a big impact. And we see that that's some of the content that providers engage with most. Sure, it's always great to get brand messaging out there, but similar to patients, doctors want to hear from other doctors who have been through that same experience. They've diagnosed more patients, they've seen more patients present these types of symptoms. So we see that physicians influencing physicians has kind of always been, or for a very, very long time, at least been a staple of healthcare marketing on the patient side. And I'm not going to talk too much to kind of social influencers on the patient side, but at least in terms of going back to the, some of the original or the initial things that we were talking about, patients want to hear from other patients. They want to hear from them on Reddit, they want to hear from them on TikTok. They want to ask them questions. We see that patient stories, real patients telling their stories, their journeys, is incredibly influential. Some of the content that we see on the patient side that gets the most engagement, the longest time viewing, the most interaction on sites, is that patient influence content. So patients who are actually out there telling their stories, whether it's going to be physically at an event or through digital channels, so we do see that essentially they become a very, very important part of the journey. Those who influence other patients, and maybe they're not necessarily influencers like we would talk about in some other social settings, but nonetheless, the idea that it's a real person, person who has gone through an experience and that person is sharing her experience with you, that means sometimes a lot, lot more than reading an article about what you should be doing. And in a lot of people's cases, it might make them help approach their physicians a little bit differently. I've heard that this happened and perhaps the physician hasn't really that sort of factor. Physicians are obviously very, very expert in everything that they do, but just understanding that this is somebody who went through this experience and this was the ultimate outcome, that's very, very influential in terms of a patient experience and the types of things to ask and talk about with your physician.
[00:32:04] Speaker A: So I'm going to throw a surprise question at you all to wrap us up. So forgive me for not prepping you for this, but I'd be curious to hear what you guys think is gonna happen on the horizon for digital advertising or healthcare advertising in the next five years. What are the biggest developments that you foresee, either from the patient or healthcare provider or both?
And how do you anticipate not only digital technology, but also our digital advertising strategies evolving to meet those, those changes on the horizon?
[00:32:44] Speaker C: I think this is funny because it is a surprise question, but I was even surprised to bring up TikTok. Honestly, I was not. You know, I didn't think I was going to take anything or say anything about that. And I think we're going to continue to see, like, really personal journeys out on this. People are really comfortable kind of sharing and putting, you know, their, their information out there. Not, you know, they're like haitian information, but they're sharing their journey. It's a lot different. I don't know, it's a lot different than it was, you know, before, you know, the Internet really boomed. But I think, I always think too, like, AI and healthcare, it's. I always think of it in an actual, like, healthcare setting as well.
Not to act like I'm a healthcare provider by any means, but to go into a little bit of like, a personal anecdote. My husband, who actually used to be an occupational therapist, works directly with patients in an in person setting and whatnot. And much of his day isn't with an actual patient. Sometimes much of his day is. Things like charting be a really tedious process for someone that's working with patients and, you know, with the healthcare system in the last few years, there was a lot of pressure on therapists to focus on productivity, meaning how many patients can you see within an hour, let's say, for example.
And, you know, that's not just time with the patients again, that is charting as well.
And it kind of got to the point where they couldn't spend as much time with the patients because they were trying to fit in so many in an hour. And then they also had to do charting. So I think where AI kind of fits in there and I think it's already been happening, is AI and natural language processing helping with those administrative tasks. And at the end of the day, and it's not just making the charting more like efficient, but also making higher quality of charting and the accuracy of like a diagnosis and then kind of getting into the predictiveness of it. It's like if that becomes better, then healthcare providers can perhaps predict things earlier and then that jump starts the journey earlier.
And I guess my thought of where this is going in the future, it's like if those kinds of things that are actually happening within the healthcare space improve its better quality, AI can synthesize and aggregate all that charting data even better than, you know, the data point. The way that we're targeting and using that information to then turn that into a marketing campaign is going to be even better. So this isn't a very specific answer, but I think it is. It's connected from the real world. So now the digital world that it's just, just going to become even more advanced, maybe. That's my opinion.
[00:35:53] Speaker A: Yeah, Malcolm, I'd love to hear your reaction to that and anything else that's on your mind as well.
[00:36:00] Speaker B: Honestly, couldn't have said it any better. Hannah, I think you hit on the key developments in the future, which is going to be all database. The availability of data.
People like you mentioned are out there. More and more people are sharing their stories. The availability of that information taken and aggregated is what's going to make it a lot more efficient in that healthcare provider setting. So ideally, instead of the doctor spending so much time charting, that's a very, very important part of the process because that's how data becomes available. Ideally, that sort of information can be automated to take up less of that physician's time. And the physician on the other side, let's say seeing an x ray, for example, there's a lot less room for error when you see 500 x rays at one time, they're all put through the same machine. It's a lot easier for, from a physician standpoint, to be able to identify, okay, this is most likely what it is. That idea can even be presented to the physician ahead of time so that the physician can spend more time with the patient and understanding what can do next. And as sort of like healthcare marketers, the best thing that we can do is capitalize on all that data, whatever is available, the availability of that level of data at the individual level, where folks have opted in, and we do see more and more folks opt in for sort of the overall greater good, to be able to help inform others at a certain point, you're able to use that level of information and that data to create more of a personalized journey, one that is custom based on the experiences of that individual, but also predictive in nature. In terms of what do I need to see? What is the next thing that I should be doing? So from a patient standpoint, it might be seeing fewer doctors, but the right ones going straight to the right ones, or at least beginning with that primary care and then moving on immediately to the specialist, because certain, let's say, blood results, things that are being charted now, there's lots and lots of data out there from thousands and thousands or millions of patients to help inform the physician. This is the very next step. Let's say 95% of folks with this level of a certain thing in the blood, this is how their journey ends up. This is where the ultimate outcome is. And if you know where you're going, what the ultimate end is, then it's a lot easier to path your way. You don't have to sort of take so many turns along the route. So ultimately, with technology, with AI, where we really see things coming together is with all the data, using that level of information to make things go a lot quicker, to expedite, so that patients ultimately can get to the overall best outcome for themselves as quickly as possible. So the efficiency kind of comes in there, and ideally, we're relying less and less on individual providers and more and more on technology, and the provider is really there to sign off, to be that human element, to be able to understand the individual patient, but use all the data at her disposal to help with the diagnosis and the treatment and the therapy.
[00:39:54] Speaker A: Awesome. Well, I thank you both for being here today. And I know one thing that I really took away from the conversation is using the power of AI for good. I feel like we hear a lot of fear mongering stories about all the bad things that AI could do to our world. But what we talked about today is about using AI and machine learning to actually empower that patient journey and improve the HCP experience. And I'm personally excited to see how that changes in the coming years and chatting with you both about that in the future. So thanks again for being here, and I'll chat with you guys next time.
[00:40:34] Speaker B: Thank you so much.
[00:40:36] Speaker C: Thank you.
