Full episode transcript.

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Stephanie Wierwille (00:00.714)

This is the No Normal Show brought to you by BPD. This is where we leave all things status quo, traditional, old school, and boring in the dust. And instead, we celebrate the new, the powerful, the innovative, the future, all related to how brands can lead the way in health. Hi, I'm Stephanie Weirwill. It's good to be with you all again. I am the EBP of Engagement here at BPD. And I'm joined by two really special guests.

We're going to talk all things data and analytics and precision marketing. And to do that, I'm joined first by Anne de Nepoli Block, Managing Director of Data Solutions and Analytics. Anne has an amazing background in all things data and analytics and precision marketing. And what's really cool is Anne comes to health care, which she's been in now for a few years, but she comes to health care from the retail world, which of course retailers have really perfected.

this idea of highly targeted personalized marketing and our job here and Anne's job here is really to bring all of that goodness into healthcare, which is desperately needed. So Anne, thank you for joining us. Thank you for bringing your smarts every day and on the show.

Anne DiNapoli Block (01:14.338)

Hi Stephanie, so glad to be here. Thank you so much for having me. I think this is my second time on, so I'm very excited to keep talking about precision marketing and our data and analytics offerings at BPD.

Stephanie Wierwille (01:27.738)

and I have a pretty good feeling it will not be your last. I think there's no shortage of that discussion that we can have. All right, we also have a new guest on, Mika Sigol, who is precision marketing and data strategist at BPD. And Mika's background is in all things healthcare and digital marketing and consumer analytics and really has some really strong understanding of how to apply.

data and segmentation and technological best practices to healthcare specifically. So hi, Mika. Thank you for joining

Micha Siegel (02:04.105)

Thanks for having me and a pleasure to be here and glad to be my first time and hopefully it won't be the last like the end. So thank

Stephanie Wierwille (02:09.434)

I will not, please. We will take all that we can get of the day to talk. So to that point, I'll just give a little bit of a setup for our conversation today. So I've used the term precision marketing a few times. And for our listeners, we've discussed this topic a bit before, but there's, we just really did the tip of the iceberg. I think at this point, there's so much depth here. But first I just want to set up what is precision marketing?

So I'll give a little bit of a textbook definition. This is our definition at BPD for precision marketing. And then unpack that a little bit. then Anne and Mika, I would love you all to unpack that even further. when we say precision marketing, here's our definition. It is using proprietary data to identify lists of individual consumers that have a propensity for health care needs. And then we segment those groups and engage with them using all varieties of targeted media. So what does that really mean?

I think maybe to circle back to the retail point for folks when you have your consumer hat on and we're all browsing the web and we get served for very, very, very targeted advertising and media that feels like it knows us. We think, is my phone listening to me? And for some it feels wild and crazy and for others it's really exciting. Regardless, it has such a significant

behavioral effect on folks to be able to actually get served this really targeted opportunities. And as I said earlier, that's challenging in healthcare. We'll get into some of the challenges of that. But really that's what we're talking about here with precision marketing is getting very personalized, very targeted because we know folks and we know what they need and we know what they need from us. So I'll pause there. And what would you add or, you know, correct of what I just kind of gave of the background of precision marketing?

Anne DiNapoli Block (04:04.354)

Well, not correct, but I think we'll really unpack. A lot of folks might be sitting there wondering, how do you replicate what retail is doing in a HIPAA compliant way? That is a question that we get every single day. So we're going to go really deep and unpack that here today for you all, but just know that it's really the purposes.

oftentimes to drive patient acquisition for certain service lines. So we'll talk through some examples of that as well, but use cases for precision are infinite, but think about it maybe potentially as your really truly lower funnel activity for healthcare marketing.

Stephanie Wierwille (04:46.52)

Yeah, absolutely. And you said service line there, which is a key word. It's not the only application for precision. And we'll talk about that more later. But it is probably the primary one and the one where our health care marketing clients have the biggest need, which is, OK, I have my orthopedic service line and my oncology service line and my neuroservice service line and whatever. And I know I need to drive growth. And maybe I have a goal of the growth I need to drive and

you know, patient acquisition I need to do. How do I do that? Right. You can put out advertising, TV spots and radio and talk about the how amazing your orthopedic services is. And that's that's something that we do for sure to build what we call brand for service line. But this is even further down the funnel. Right. This is getting very personalized and saying maybe at the service level, really targeting folks that need that service. Is

And would you kind of agree with that? You know, just kind of, this is really bottom of the funnel stuff

Anne DiNapoli Block (05:50.316)

Yes, bottom of the funnel and maybe unlike some traditional channels, the fact that we have lists and we are using typically digital addressable channels, we can measure it all in a closed loop fashion. Closed loop meaning who was exposed, what did they receive and what actions did they take? Where did they have an encounter? What types of services did they have at our health system? So

the ability to really truly be able to measure that as a chord differentiator as

Stephanie Wierwille (06:23.706)

Okay, love it. Okay, well, let's start there then. think, go ahead, go ahead, Mika, go

Micha Siegel (06:24.871)

And as it just to add to that, it's actually also looking at really being efficient in how we're that market, right? So you can target individuals from, you know, the zip code level versus, you you run a service line campaign and you target everybody in that market. But yet with precision, you're actually able to be more efficient in your marketing dollars, apply those dollars more effectively. And then as I said, actually measure that dollar back to your ROI. So it's a full funnel piece was actually helping to be more effective and efficient.

in your service line marketing, not just that you can target them at the lower funnel, but really make sure you're targeting the person that you want to target, not just at that zip code level that you can typically do from a healthcare side.

Stephanie Wierwille (07:05.422)

Yes. Yeah. And it's really powerful stuff. And often one of the first questions that we get is, so, and you mentioned lists, right? Lists of individuals. That's really what makes this special and key is we're talking about specific people, not just broad groups, demographic or cyber graphic groups. So why don't we start there? Let's talk a little bit about the data that we use. So maybe I'll toss this first to you, Mika, if you want to just give some examples

What are the types of data that are really valuable and that BPD really leverages in order to make this

Micha Siegel (07:43.46)

Yes, we actually kind of look at sort of multiple facets of data. One is that sort of consumer data, right? All your likes, your interests, your hobbies, your do's and don'ts on the web that you are participating in. On the retail side, couple that with some clinical data that actually takes sort of information from your encounters at a hospital or a primary care provider or a specialist. And we use that data to really build a model around those individuals. So it's not just taking a consumer data file and targeting those individuals.

really coupling that with the actual clinical based data that's de -identified and building, and that's really the secret sauce, is how that clinical data and that consumer data marries together to build that type of model and building that type of target that we're able to do in a HIPAA compliant way. So it's really not just one or the other, it's both combined that makes that big impact on the precision list.

Stephanie Wierwille (08:35.234)

Yes. OK. I think you said a lot there and we can we can talk more through this. So there's so let's just break down some of this this data that that we're really leveraging. We're we're we're talking about I heard you say demographic data. I heard you say psychographic data. I heard you say you know clinical data that we marry with consumer data. So it sounds like

you know, a wide variety of data types so that we could get a full picture of a person. And I've, I love how you all talk about this sometimes as it's the individual person and it's their specific likes and interests and needs and, and healthcare, you know, needs, right? So give me some examples of, you know, okay, we're talking about John or, you know, this person, like, what does that look

Micha Siegel (09:27.966)

Sure, so a good example, so orthopedics is a really good sort of one to sort of comprehend and process, right? So somebody who is active, they're into cycling or biking or hiking, running, anything that's outdoors, anything that makes them active, we can identify those types of interests. Also then based upon, so that's your demographic or psychographic type of data, but then you look at some of that clinical type of data of somebody who is maybe in their 60s who is more inclined to have a knee replacement or hip replacement or other orthopedic types of injuries due to their desires of hobbies and interests of that outdoor lifestyle, we can sort of build that model around an individual to say this person, this John Smith is more likely to need a knee replacement because of their age plus their hobbies and interests that we've seen them be doing. So therefore we can run a targeted orthopedic campaign to that individual. So it's really using those types of personal information that's on the web out there, plus with your clinical data to make that distinction between somebody versus the next person down the block who may not be into those activities and doesn't need a knee replacement or may not need a knee replacement.

Stephanie Wierwille (10:42.446)

Yeah, great.

Anne DiNapoli Block (10:43.246)

Well, and I'm going to chime in because everyone may be wondering, well, where do you find these people? Where do you get their contact information? What lists are they on? What lists do you speak of? get that question from our client all the time. So, you know, I call these like the data marts in the marketing landscape. There are very large, robust consumer database sets that are available for direct licensing and usage. Again, it is all privacy and HIPAA compliant lists that we're able to generate. But what's great is all those attributes that Mika talked about are available to match at those individual zip codes. So we can really get very precise in the way that we're reaching Mika, for example, in South Florida.

Versus where we wanna maybe reach Stephanie and her market. So that is exactly how we get the data and the models are applied in these use cases.

Stephanie Wierwille (11:46.498)

And you hit on a really important point, which I think is just so key, which is this is something that is very special to BPD, right? That you and team have spent so much effort and bringing all of your background and experience to bear to say, what are the right data sources? What are the right varieties of places to capture that data? Because this goes far beyond your typical maybe third party data that's gathered.

But you just want to talk a little bit at a high level around the work that's gone into making this so specific to our our clients needs

Anne DiNapoli Block (12:24.096)

Yes, absolutely. So we have a very robust team that really helps to not only access this license data, but really do the modeling and the management of it. There's, data engineering that gets applied as far as how to build the use cases against what our clients may be trying to achieve in that orthopedic example. And then really truly helping diversify the ability to apply modeling. So we work with a lot of different third party data partners. We love to say at BPD that we are data agnostic. But while we're agnostic, we have built over time a very, very large proprietary data partnership pool, if you will. So a lot of times our teams, Omeka, and my group at BPD are looking at, okay, here's what we're trying to achieve. These are the right sources to apply to this marketing use case. And these are the best people to reach. And that's really the methodologies and the system, if you will, that we've created over time to be able to do this at

Stephanie Wierwille (13:37.102)

Yeah. So speaking of data, I think just it wouldn't be a no normal episode if we didn't talk about ding ding ding AI. But but Anne, when you talk about, know, the the wide variety of data that you're pulling in, the data science that goes into it, the engineering that sits behind it, I imagine there's another member of your team, too. Right. Which is machine learning effectively. Can you talk a little bit about how you leverage machine learning in order to make all this possible?

Anne DiNapoli Block (14:09.868)

Yeah, absolutely. Well, and I'm going to go back to my retail roots because when we started doing this in retail, not to date myself, but you know, more than seven years ago, we really looked at, how do you apply these data sets to all these different attributes? And it took pools and teams of data science capabilities. It was an extremely large investment typically from like a resource perspective, but then also, you know, when we thought about the time to build the models and get accuracy of data models, that has just sped up tremendously. Even within the last 12 months, I am very excited. Even since I've started at BPD last fall, we are really able to apply some of these new technologies, machine learning models, generative AI on top of where we can speed our response to spinning up new models that may be customized or really to test the accuracy. One of the things that is very exciting in our roadmap is we are really now wanting to differentiate some of these healthcare propensity models with coupling with our response data. So how are people responding to different messages?

What is that right way of speaking to somebody with an orthopedic need or care that we can then apply to the model to make it smarter? So those are some of the things that are excited to be building right now because again, five years ago, this would have not been available to the level of scale that we'll be able to achieve in the next 12 months.

Stephanie Wierwille (15:55.258)

Yeah, it's so exciting. think what's possible, not just today, but tomorrow. And I think what's really exciting is, Anne, what you and your team have built is, well, one, it levels up, you know, healthcare marketing today in 2024. But it also for the clients that are implementing this, gives them a really strong path for future development and growth so that even they can capitalize on, you know, the smarter models and in gathering performance data of what works and improves over time. So I think that's what's so cool. We'll talk about ROI here in a little bit, but I would imagine that what you're saying is really what allows us to achieve really significant ROI numbers and then improve on them and beat them and be really competitive on them. Is that right?

Anne DiNapoli Block (16:41.838)

Yes, absolutely. we love to say and throw out really high ROI numbers. A lot of our clients are utilizing precision marketing and seeing some really amazing returns on their investments. We're talking like 20 to one, even larger than that in some use cases. At the end of the day, the closer that we can get to applying a client's benchmarks and their financial success to the models will ultimately be able to deliver better outcomes. So while the range may vary tremendously based on the service line and exactly what type of success we are capturing, the goal would be to be able to really prove and put a lot of value in all this activity so that we can show that it really works to deliver effective results.

Stephanie Wierwille (17:41.05)

Yes, yes. And that's, that's a, think I call it an Oprah moment, an aha moment, a mic drop moment of this kind of ROI that, you know, marketers clamor for to be able to merchandise up and share with their CFO and sit down and say, here's really the value of marketing and service line marketing and numbers like 20 to one, even three to one, five to one. Those are key. Those are critical to be able to say, I invested X amount. Here's what we got from it as an organization.That's tied back to revenue and contribution margin. And so here's the level of investment that's required to improve that over time. So really exciting.

Anne DiNapoli Block (18:23.01)

Yeah, and I'm just going to add, you know, I think when we think why healthcare, right, and this type of success, at the end of the day, the numbers and the success are what our CFOs want to see, right, from a marketing investment perspective. But, you know, what I love about the work that we're doing is at the end of the day, what we've successfully been able to do is connect patients to services that they need.

The fact that that is what we live and breathe all day and what data enables at the end of the day is just like, I think, a dream and kismet and exactly why we are all sitting around this virtual podcast table.

Stephanie Wierwille (19:05.676)

Yeah, absolutely. So, you know, some may be wondering, OK, how, how, how is this possible? So why don't we get into a little bit of the best practices and some of the things that we've learned. And you all both talked earlier about the importance of making sure that this type of marketing is really working in the health care space where there's a lot of compliance needs.

There's a lot of specific legal and ethical requirements, especially when it comes to HIPAA. And sometimes that throws up a giant roadblock for marketers who are like, I don't want to touch this at all because there's a big risk. So let's talk a little bit about how we've worked through that. So maybe I'll come to you first, Mika, if you can give some examples of best practices overall, but especially on the compliance side.

Micha Siegel (19:54.51)

Yeah, happy to. So I think the first thing to really note is that we're actually not using any PHI data from any healthcare system, right? It's all de -identified, it's all anonymized data. So at the very onset really, it's looking at where that data is coming from and it's all from a basically national level type of data, it's all de -identified. We don't know who's who in a data set, we just know that somebody had this type of need. So when we talk to the health, when we talk to clients about HIPAA policies and compliance,

It's really helping them understand that, we don't even need their EMR, their medical data. It's really just that we can use this based upon a national level of data. So that's really the first thing we kind of address with some of our clients is, nope, we don't need your data. We can do without this. If you have information, we can certainly look at it at a de -identified level. But again, the very onset, it's all HIPAA compliant. There's no compliance issues in terms of ingesting any PHI data. That's kind of like the very first thing we kind of look at. And then the second piece really

In terms of how we actually report that data back, this is all information that we can share that's consumer level data. So anything, all the PHI data is still kept within the medical record systems and the EHRs. What we're sharing is really any kind of consumer level data from a name and an address standpoint, which is no different than if you were to go out and buy a consumer list or rent a direct mail file with people. So there's no difference in data that we're able to share and provide that you wouldn't, someone wouldn't be able to provide on the open market.

Stephanie Wierwille (21:24.588)

Okay, well that's awesome. Thank you. That's a really great explanation and I think helps quell some fears there. Anne, is there anything that you would add in terms of either compliance or just learnings? I know you've also been out on the road, literally on the road speaking about some of the roadblocks and some of the issues. Are there any other kind of key things you would highlight that can help push through those?

Anne DiNapoli Block (21:53.12)

Yeah, absolutely. So we actually get this question a lot on the road and in all of our client meetings as well. At the end of the day, I always try to explain to folks what is so important is that you understand the ins and outs of how this works, right? So we have lots of education materials that we provide with our clients. We really take a handheld approach of explaining this, you de -identified world and even how you explain how data gets de -identified is like a whole methodology. But at the end of the day, what I love to tell folks is, you know, as long as you are educated. Now, we're not saying that you have to be, you know, a law student or get your legal degree in your like evening work,

If you can go to the table, explain to your legal stakeholders and counterparts exactly how this data works, it's to your favor so that you can really be that educational gap for them to interpret what the risks are. And again, we have really found the secret sauce and the magic button to be able to do this at scale in a way that protects our consumer privacy at first and foremost.

Stephanie Wierwille (23:18.862)

Well, and I would sign up for that course. know that maybe I'm here at home with fellow nerds in the room, but I think a deep dive on how data gets de -identified and consumer privacy laws, it's never been more important for folks to understand, especially because there's been shift after shift over the last few years in terms of the policies that have come out.

I don't know, Anne. Maybe you should teach a full class in this.

Anne DiNapoli Block (23:50.316)

Yeah, we definitely, well, what I will say is it's always job security when the landscape changes so quickly and whether that's AI being applied to new data things or interpretation of really truly how to apply methodologies based on what you're hearing from legal. So we would love, we could probably do a whole podcast session just about

Stephanie Wierwille (24:14.062)

I mean, I'm here for it. I'm here for it. So speaking of changes and shifts, really our last topic here is what does the future hold and what are we seeing? Because as we've discussed, one, policies change every day, every time we turn around. Two, the technology continues to advance, and that's what's really exciting. As machine learning continues to get more more sophisticated, our models get more smart, and we're able to do much more advanced things.

The future I think is really bright for this area. So there's a lot we can talk about here. Let me just first ask the question. I'll put this to you first, Anna, then Mika, if you want to add anything onto it. I think let's just start with what are some of the key trends that we're seeing? What are the things that are happening and shifting in this space?

Anne DiNapoli Block (25:03.852)

Yeah, absolutely. Well, I know we touched on AI and machine learning, I mean, by far, that is really catapulting the ability to do this work in, you know, days and weeks versus months and years like it used to.

And then I also think the trend that we're seeing is other use cases, right? The methodology here is great for patient acquisition, but when we think about the other needs in healthcare marketing, things and challenges like recruiting for nurses or physician referrals for certain services, right? Those are nuts that we are actively working on cracking. And then I think we have a whole session coming up soon, but I think we'll spend a lot of time talking about creative as well, right? Because at the end of the day, the data can be so great, but the messages that we are serving to these consumers in the spaces where they're spending their most time, right? Like how much time are we all spending eyeballs on our screens, scrolling all of our streams at night and being able to capture attention and the way that data is allowing that to happen in a more effective way is an area that we are really leaning into as well. again, I think, you know, obviously a little bias here, but I think the data unlocks all these great opportunities to advance the creative, the media strategies, all that goes into this type of precision marketing.

Micha Siegel (26:42.21)

And I'll just add to that, you know, it's also accountability, right? Every day we're getting from our clients that are the CFOs and their budgets are being tightened into more accountability on how they're measuring their dollar spent on marketing and how that impacts the system. So one the nice things about Precision as we mentioned is that you can actually measure that dollar for every dollar you spend while you're generating that return. And you typically can't do that with your typical traditional healthcare marketing on the digital space or traditional space.

Being able to actually show that return and show your CFO's leadership that, hey, for every dollar we're spending, we're bringing in $3 for revenue contribution margin really has a strong, effective impact on the health system showing that the dollar that we're spending for marketing is actually driving that patient and the dollar to the system. So I think that's where we're seeing that as well as how am I being accountable for every dollar I'm spending and Precision Health is allowed to do

Stephanie Wierwille (27:36.058)

OK, love it. I want to dig in on one of the top, a couple of topics here. One is, Anne, you were talking about how precision can be applied to other areas, including things like recruitment or HCPs. So why don't we just dig in that just a tiny bit? And Mieke, I know we were even sidebarring on this yesterday.

As you were talking about some of the really cool abilities to target healthcare professionals, including doctors with NPI codes and really take this model and apply it to that. can you all just share just a little bit more about some of the areas that Precision can go into that are even beyond service line marketing?

Micha Siegel (28:19.88)

Yeah, happy to. Yeah, so exactly that. So every clinician has a unique identifier, their MPI code. So if we can identify that, know, doctor, DO, MP, PA, APRN, we can identify who that is from an individual level and actually serve you consumer ads if you're serving your new sites, your consumer sites, and almost as if you're a consumer, but yet we're targeting you from that clinical side. So we know that you're a primary care physician or an orthopedist or a cardiologist or oncologist, we're able to serve you specific ads to that actual service line. So we're not just taking a recruitment campaign for clinicians and serving to everybody. We can target specifically to the field of hire that you want to focus on. So it allows us to, again, be more effective in that dollar that you're spending, as well as actually target the right type of clinician that you want to hire. Nursing is a little bit more challenging because they don't always have know, MPI code, but we're working through some of those use cases as well as how we can target more nursing at large and at scale to be effective in that. But really it's sort of treating our clinicians and a consumer mindset approach. it's really switching that, switching on the title of, you're a clinician, but we're also being able to treat you like a consumer. You act as a consumer as anybody else does, and you're scrolling at night, the laying in bed, we're able to serve you those ads just as if you were a consumer. So it really is a nice way to also augment that ability from just the precision service line side.

Stephanie Wierwille (29:50.134)

Absolutely. And I think what's really cool is this model can be applied to a variety of business needs and business cases. I need to drive volume for orthopedic. I need to drive volume for this very specific service. I need to increase my patient acquisition approach in this market. But I also need to recruit or just reach people on a personalized level. So I think that's so exciting. One last just kind of quick note.

We've talked on this podcast before about what we've called the pixel mayhem, which is of course this challenge that health systems are facing where many have actually had to remove pixels from their websites because of data leaks that have occurred through third party sources like Meta and others. even a variety of platforms, Meta, TikTok, et cetera, have led to this issue.

But I think one thing that's so exciting about this, and I want to hear from you, Anne, a little bit of how we're solving these problems is with Precision, it actually allows marketers to continue to personalize in a cookieless world. Is that right? Can you build a little bit onto that?

Anne DiNapoli Block (31:08.738)

Yeah, absolutely. and it's this pixel mayhem, which I love that that's what we've called it. We've had so many clients recently. know, again, I think until more comes out from the HHS and the stance on marketing tracking technologies and what that means for consumer privacy, we always tell our clients take a conservative approach, right?

Precision marketing at the end of the day could also be called pixel -less marketing because it enables that one -to -one relationship of this person was on our list, they were exposed to our advertising, they were part of this campaign. We have licensed this data, it is not HIPAA compliant, so we're just in a really great place to be able you know, not take out sort of the middle funnel because we know digital encounters and interactions and engagements on content and websites is so critically important. But at the end of the day, when you're trying to drive patient volumes and encounters, really able to expose and understand, okay, this list, this ad, this outcome that will really allow us to be more effective. all that is, you know, the pixel world we can talk about. Cookie deprecation is almost something that we could spend a lot more time on. But because that is happening, right, there's a few things that we're going to see. One, match rates will continue to decrease. And two, being able to measure the outcomes on websites with digital tracking will face new challenges, again, with a potential decrease.

We are enabling all the right technologies with some of the new tools out, like Universal ID 2 .0 is an example of that. But at the end of the day, just know that that world does not get really changed with the ability to reach consumers on these lists. So we are constantly at the forefront of how we'll be able to match folks in addressable spaces as that tech changes.

Anne DiNapoli Block (33:25.778)

you know, that's why really truly at the end of the day, having a partner that is experienced in this is just really important as you go down this

Stephanie Wierwille (33:35.022)

Yeah, absolutely. And my dad joke of the day is cookie deprecation is not as yummy as it sounds, right, Anne? Unfortunately.

Anne DiNapoli Block (33:43.936)

It's been a week, and it's, yes, and I've written way too many POVs about it. And I like that the deadline keeps getting pushed. We have some more time on our hands, it sounds like, from Google right now. But it's, you know, I think we're all getting really tired. Like, let's just move into a decentralized internet, then maybe we don't have to worry about it.

Stephanie Wierwille (34:06.072)

Let's go, Web3, let's dive in, yeah. Okay, so I'll just summarize a few key takeaways and want to hear from each of you as we wrap up. Mika and Anne, if you have one key takeaway for clients, I think some of the things that I've heard are, number one, ROI, ROI. It's become more and more and more important. I'll do a little reference over to the Roma's Burning episode that we hit a couple weeks ago,

One of the key issues there is the undervaluing of marketing and how do you solve that in a health system? Well, one big way is making sure that you're constantly showing ROI. So if you can bring forward 3x, 5x, 10x, 20x ROI, that's a big deal. I think number two, and you just talked about the pixel -less world, cookie -less world, cookie deprecation, that's just keeping marketers up every single night for so many reasons. So having pixel -less marketing is huge.

And then three, I think I heard you talk a lot about the ability to leverage machine learning to build smarter models over time, which creates smarter marketing over time, which creates better optimization over time, better creative over time, better targeting over time, and therefore better ROI. So those are my kind of key takeaways. Mika, do you want to build onto either one of those three or add a fourth that you think that should be on the minds of healthcare marketers?

Micha Siegel (35:27.546)

Yeah, I'll add a fourth to that. I think it's really empowerment through data, right? So we talk about how all the data is out there and it's leveraging the data that's available from a clinical, from consumer side and being more effective and efficient through data to your actual service line volume growth. And it's leveraging the data that's available at your fingertips already that we can get out in the marketplace and really leaning into that data capabilities to drive your service line volume.

Stephanie Wierwille (35:53.754)

Love it. Okay, and leave us with a couple words of wisdom.

Anne DiNapoli Block (35:57.506)

Well, I don't know if I always have wisdom, but what I will say is this, if you're, if you're listening, right. And this is maybe your first time thinking about marketing in this way. It can be a little overwhelming, right? The advice that we did on that road show was like, just start small. Look at the data that you have available, find a solution for how this could work in your PSAs.

and build on one use case for success, right? You don't have to boil the ocean on day one. And there's ways to get started with this in a very crawl capacity, if you will, if we think about crawl, walk, run. And one day you'll be running if you just start small. So that's what I always love to tell our clients.

Stephanie Wierwille (36:47.822)

That's great. I love it. Very practical. You know, start here. So thank you all so much for joining. I really appreciate it. And I know there will be more conversations coming soon. And you just teed one up a little bit ago, which is a conversation about the creative side of precision marketing. So Anne will be joining this show with our chief creative officer in a little bit. So thank you, Anne, for joining and I'll see you soon.

Anne DiNapoli Block (37:13.698)

Thank you, Stephanie. It's been a pleasure as always.

Stephanie Wierwille (37:17.026)

And thank you, Mika. First time guest, but many, many more to come. Thanks for bringing all of your data

Micha Siegel (37:25.243)

Thanks for having

Stephanie Wierwille (37:27.424)

Awesome. And for those listening, thank you for listening. Thank you for joining in. And if there's ever something you want us to cover, shoot us an email at nonormal at bbdhealthcare .com and share the show if you can and give us a review and rating. We'd love that. But more importantly, until next time, don't be satisfied with non -targeted, non -highly targeted, non -machine learning, non -AI based marketing. Push the no normal, push that precision and we'll talk to you next time.