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Episode 04: Succeeding in the New Era of Privacy-Focused Digital Advertising

Hosted by Aaron Burnett with Special Guest Alex Martin

Understand the impact of Apple’s iOS updates and the evolving privacy landscape on digital advertising, particularly in the healthcare industry, with Alex Martin, Associate Director of Digital Advertising at Wheelhouse DMG.  

On this episode, we explore how advertisers can adapt to these changes by leveraging first-party data, implementing innovative tracking methods, and focusing on creative marketing strategies. The conversation emphasizes the importance of building a strong data infrastructure, utilizing business intelligence, and shifting towards a more privacy-compliant approach to digital advertising. Learn valuable insights and strategies for advertisers looking to navigate the challenges and opportunities presented by the new era of privacy-focused digital advertising. 

Apple and Privacy

Welcome to the Digital Clinic, the podcast that goes deep on digital marketing trends, strategies, and tactics for the healthcare and medical device industries. Each episode brings you expert guests sharing the knowledge, insights, and advice that healthcare marketers need to be successful in this complex and rapidly evolving digital landscape.  

Aaron: With me today is Alex Martin, who is our Associate Director of Digital Advertising. Thanks very much for being with us, Alex. 

Alex: Yeah, excited to be here. 

Aaron: So, let’s talk about Apple and privacy. Apple released iOS 17 in September. That was significant for digital advertising. Tell me a little bit about that, and let’s talk about what Apple’s trying to do and what it means for us. 

Alex: Yeah, so the release in September was primarily targeting a couple of areas that I think iOS 14.5+ did not address, which is the Safari browser, iOS default messaging app, and mail app. They released link tracking protection, which all they said when they released it was that it’s going to strip some URL tracking parameters from links in these apps. We didn’t know exactly which links or if it was going to be all URL parameters, when that came out in September. So, over the last couple of months, people have started to realize it’s not all URL parameters, and it seems to be specifically targeting any user-based clicked IDs, like Google and Facebook use. This is, in my opinion, targeting SMS marketing, email marketing, things like that. Whereas before, they were really targeting advertising within apps and tracking across apps. Going back to their whole privacy philosophy, they’ve really leaned into being the privacy platform, and it’s, it’s been really good for them. I think it gives a lot of users, who have felt violated for many years from some of these platforms, it gives them the warm and fuzzies to be able to do their day-to-day life in an environment that focuses on privacy. 

Aaron: Another thing you mentioned was addressed in iOS 17 were some workarounds that Google and Facebook had implemented to try to overcome some of the earlier exclusions that Apple created. Can you tell us a little bit about that? 

Alex: Yeah. So in 14.5, Apple targeted the FB click ID and the Google click ID, which are essentially the user ID trackers that Google and Facebook used. Going back many years, initially, when people started doing things cross device, and they started using their phones, their tablets, their computers, these click IDs allowed Google and Facebook to tie that behavior all together and tie that all to a user and a user account. But, what they were doing is in kind of the app environment on iOS, they were able to tie a lot of data together in the iOS ecosystem prior to iOS 14.5, kind of eliminating that, where they could pull data from all these different apps, third-party tracking on all the different apps and websites you were visiting, and build this extremely rich profile on you. When they came out with 14.5, they were targeting, in particular, when people leave a Google or Facebook app environment and go to, say, Safari by clicking on a link, that allowed them to bypass any app based restrictions that you had set user data sharing settings within the app because now you’re going outside of that app experience where you set those preferences. That was the approach that they were trying to solve for. It was a lot of data leaking through these different ways Google and Facebook were pulling data and tying it together when you’re interacting with your phone. 

Aaron: In ways that consumers weren’t aware of at all. So that was addressed in 14.5, but then, Google and Facebook responded with alternative means of collecting data. 

Alex: Right, so that’s when the GBRAID for Google anyways, when the GBRAID and the WBRAID parameters came out, which technically complied with Apple’s restrictions around privacy. There isn’t a ton of information out there about exactly how they comply, but from my understanding, the WBRAID parameter is when you go from a web to an app. So, you click on an ad in web, and it opens up in the Google app, for instance, that parameter can tie those two together, but it has some level of aggregation with it, rather than a one-to-one user ID tracking scenario. The GBRAID is the other way around. You click from an app, and it takes you to a web experience. Those complied but now seem to be the target of what link tracking protection is removing from iOS 17. 

Advertising Campaigns at Wheelhouse

Aaron: All right. So then in 17, it was feared that all parameters were going to be stripped potentially. We’ve been able to continue to successfully structure, manage, and optimize campaigns, taking an alternative approach. What approach have we taken, in particular, for healthcare clients? 

Alex: We’ve really leaned into a couple things really, but UTM parameters in general, that don’t use user ID tracking, we’ve moved away from auto tagging. Auto tagging was a feature that made link tracking and user tracking and ad campaigns really seamless and easy. It automated that whole experience for you. To go back a little ways, prior to auto tagging, we would have to do keyword level URLs, sometimes for millions of URLs in a campaign, that is super complex, and it’s very inaccurate, there’s a lot of user errors. Auto tagging was a really seamless, cool feature where Google Analytics just automatically knew all of that information. They pulled out all into the reports for you. We’ve now, due to privacy restrictions, requests from our clients, and working in the healthcare field, we’ve walled those systems off from each other. We’ve had to kind of rebuild the old school manual URL parameter tracking that we had in the past. What we do is we use very structured strategic approaches to our campaign naming conventions, to what information we enrich our URLs with, and we pass that data directly into our CRM systems, bypassing any kind of automated links. Then we ingest all of that data into our first-party data warehouses, and we rebuild those reporting features on the back end. 

Aaron: So, the UTM parameters that we use are very detailed – I understand their campaign, their creative, their messaging, their placement, their awareness level – we target based on awareness level. Every campaign, every account, every strategy for us is based on wanting to deliver the right message and the right channel at the right time. We’re thinking about targeting people who are unaware, who are aware of a solution, who are aware of just a problem, who are brand aware, and then those who are ready to convert. And so, I understand we’re able to track all of that using UTM parameters as well? 

Alex: Correct. Every single one of our campaigns that falls into one of those groups is classified, and “hey, we’re targeting this particular awareness level.” So, we baked that into our UTM parameters strategy, and we use a lot of different kind of approaches. We use our own kind of manual UTM parameters, and ad platforms also provide some really interesting dynamic parameters that we leverage as well, that pull in information from your ad campaigns, and automatically tell you where this ad was placed, whether it was on a feed or a story, or the Instagram platform versus Facebook, or what have you. We use all of that information, what type of ad, what’s the subject of the ad, what is the text that accompanies that ad, on a Facebook ad, for instance, all that information goes into our URLs. And then, the key is actually leveraging that on the back end, which is where our Compass data warehouse and visualization platform comes into play. We can look at all of that data on the back end across channels and slice and dice it any way that we want. If we want to see what video creative and messaging resonated the most with our brand unaware audiences, or specifically, our problem aware audiences, we can see that in aggregate across all of our campaigns, search, social, and any platforms. We can build all of that into the URL parameters strategy. 

HIPAA-Compliant First-Party Data Strategies

Aaron: That’s great. You mentioned we’ve walled off the ad platform from analytics platforms. How are we then going about getting data into our data warehouse? How are we integrating with clients’ CRMs in a HIPAA compliant manner, so that we have the data that we need? 

Alex: We are not using any native connectors to the ad platforms with, say for instance, Salesforce has a native integration with Facebook and with Google, we’re not giving them that access. We’re using UTM parameters on the front end, and we’re capturing those along with any conversions that are happening. If the conversion is a form fill, we’re grabbing all of that information, or at least the information that we need at the lead level, and we’re capturing that in Salesforce. And then we’re building reports in Salesforce that can automate sending that data back into our first-party data warehouse, where we combine our advertising data sources as well, using the information that we ingested in forms. 

Aaron: So, because we’re working in healthcare, and we’re covered by HIPAA, and we have a BAA with our clients, we can collect that information. We can evaluate, we can analyze it, but the issue is a sharing issue, right? We can’t share it, but we can collect a really high fidelity, very granular data and use that to inform our strategies, right?  

Alex: Right, and in particular, where it becomes really interesting is when you start to look at lead stages, or the type of customer that particular lead was, whether that was a type one diabetic or a type two diabetic. If we’re optimizing specifically towards type one diabetics, but we’re still getting type twos because not everybody’s search intent or browsing intent identifies that on the front end, once we find out, through our sales teams, when they call that lead or speak to that lead, and they find out, “okay, this is a high quality type one lead,” now we have the information to connect that all back to the ad, the creative, the platform, whether that was in your news feed or in an Instagram story, whether it was a product agnostic ad, or it featured an influencer that we’re partnered with, all that information can be rolled up into our aggregate first-party data warehouse. The one thing that we can’t then do is automate sending signals back into the advertising platform. That’s where the manual optimization and analysis has to happen. Where before we would kind of automate that whole process in a closed loop system, now we have to go back to analyze this data over here in our own kind of walled garden, and then take action. I think, in the future, in the next couple of years here, that’s where we’re really going to be able to have an edge over other advertisers – the amount of data that we’re able to collect in a compliant way, most importantly, what we do with that, how we visualize it, how we turn that data into insights, and then actually taking that information and being able to make smart strategic, consistent optimizations based off of it. 

Aaron: Yeah, you mentioned how important it is to make that work easy for the advertising managers involved. 

Alex: Correct. I think that that is one thing that gets lost. The more friction that you have there, the slower your advertising teams are going to be able to respond and to be able to make optimizations. One of the things that you’re always going to balance in this new kind of paradigm shift is complexity and speed and ease of campaign management. Advertising campaigns, especially on digital platforms, are extremely challenging, they’re complex. Adding any friction to that just slows down how quickly you can optimize and how quickly you can make decisions. It speaks to the importance of having a fully thought out, a fully resourced first-party data strategy, and how much more important that’s going to be in the future.  

Aaron: I think that’s a great point. And in this instance, it’s a first-party data strategy, but then implicit in that this data infrastructure can support that first-party data strategy and the operational processes and the business intelligence (BI). That’s the way we’ve approached it, we’ve created a BI practice that’s focused on this, so that they can turn data that is aggregated in a HIPAA compliant manner into insights that can be actioned without sharing data out to third-party platforms. 

Alex: Yeah, absolutely. I think a key point in there, the recommendation I would make, is in my career, I’ve seen people use just crazy long URLs with tons of UTM parameters. They’re attaching all of this additional data. but the real value in that is what you do with the data. I see a lot of people fall short of rolling that data up into an environment that makes analysis and finding insights easy. And that’s where we’ve really been able to succeed, is building visualizations and platforms where our advertising teams, who they’re generally nontechnical people, they can go in, and they can slice and dice, they can see everything at every level in an easy way. We’ve kind of rebuilt all the automated functionality that the Googles of the world we’re building into Google Analytics and things like that, and we’ve even taken that to the next level. Being able to invest in the data infrastructure and people needed to actually leverage that information is going to be a huge focus, I think, for advertisers. 

Apple and First-Party Data

Aaron: Yeah, I think you’re absolutely right. Jumping back to Apple and what they’re doing with their operating system releases, what do you think is their ultimate strategy? I mean, they’re creating a pretty powerful walled garden, in which they have high fidelity data in a way that other platform providers don’t. They have permission to use that data, it’s first-party data, do you think they’re going to become an advertising ecosystem? 

Alex: I think they will. I mean, we’ve been hearing murmurs for years. It hasn’t come to fruition yet. We know that Apple, historically, they put up a very strong wall of secrecy, but I think they have a couple of motivations here. I mean, Google and Facebook are clearly their competitors. Meta is clearly their competitor. They have such huge market share, and in the US, in particular, that they would be out of their minds not to leverage that first-party data environment that they have. But I also think that, in general, consumers are just tired of feeling taken advantage of and feeling like their privacy is being completely invaded. We’ve seen Apple strategically, outwardly structuring themselves and marketing themselves as the privacy platform of the big technology providers. I think there’s a bit of marketing involved as well. But absolutely, they have positioned themselves, while kind of pushing out the Googles and Metas of the world, blocking them from sucking up all this data and keeping it for themselves, essentially. So, I would imagine in the next couple of years, we’re going to see Apple move beyond Apple Search Ads, and start offering advertising services in some form, whether that’s through a DSP or something that we haven’t seen yet. I imagine there’s a lot of conversations going on internally with them on how to best approach their advertising ecosystem.  

Aaron: Yeah, I think you’re right. You know, if I were to prognosticate, I would think an ideal time for them to come out with a great ad offering would be after Google has deprecated third-party cookies, and advertisers have realized what they’ve lost. Folks in healthcare, our clients, have needed to pay close attention to all of this for a long time because they’re covered entities, they’re governed by more restrictive privacy regulations, they’ve needed to be more careful.

Evolving Analytics Reporting

Aaron: Folks who are who are not in highly regulated industries, though, just general advertisers, I get the sense they’re not paying super close attention to what’s happening right now and what will happen with deprecation of third-party cookies and the introduction of Google’s Privacy Sandbox. I think that when that happens, there will be a sizable part of the industry that freaks out because they won’t be able to do all the things that they assumed they would still be able to do. I know in looking at Google’s Privacy Sandbox, there are fundamental things, in fact, most of the fundamental things that you can do with digital advertising today, you cannot do in the Privacy Sandbox. It would be, thinking about the marketing side, an ideal time to announce a great advertising ecosystem, in which you have all sorts of first-party data available that you can offer up, you can’t share, but you can offer to support targeting in a way that other platforms can’t, after people have freaked out.  

Alex: We’ve seen there’s a good parallel there with GA4, right. And I mean, even going all the way back to Universal Analytics, where they have to force the change, most advertisers are super reactive to this type of thing. Healthcare has to be a little more proactive, and especially over the last year and a half when new guidance has come out on tracking and compliance and things like that, but advertisers don’t change until they’re forced to change. So, I would agree with you that I think people are going to kind of get blindsided by this, and once their hand is forced, they’re going to have to rethink their entire strategies.

Back in the days of the billboards and TV ads when you didn’t have direct attribution and you really had to put a lot of effort upfront into ensuring your campaigns and your messaging, your positioning was extremely strong before you went out and bought that billboard to have the most impact. We’re going to see a fundamental shift back towards things that worked in the past, good marketing principles, really. That’s something that we’ve been working heavily on the last couple of years in the healthcare industry, doing more with less, putting more time in upfront researching campaigns, understanding our audiences, developing our positioning, things like that, where you could kind of just go out and spray and pray before, and then you get the data to find your way pretty quickly. That was a huge value in digital advertising, and you could even use that to inform traditional strategies. We’re going to see the people that succeed in this new kind of paradigm are the ones that are thinking that way. They’re thinking back towards the way that we used to do marketing. I don’t think having one-to-one attribution is necessary to do great advertising. We just need enough data to understand directionality. 

Aaron: Yeah, what’s working in general. Well, and I think, to your point, we’re going to be forced into that paradigm anyway because direct attribution, one-to-one attribution won’t be available. I was looking at this on the Google side in the Privacy Sandbox, where attribution reporting will change fundamentally. There’ll be two kinds of attribution reporting, leaving aside multi-touch attribution, which is just a non-starter for all kinds of reasons. If you don’t have third-party tracking, following user journey across sites, you can’t do multi-touch attribution. Even if we look at just basic attribution modeling, they’ll have event-based and summary attribution. Event-based attribution will not give you the time of a conversion, will not give you the value of a conversion, and will give you really very little information, to the extent the value that is given to you is fake. The example that’s provided in the report that I was reading is that you might have a conversion that’s reported as worth $2, but the $2 is representative of anything from one penny to $50 for that conversion, and so not very useful. Add to that, that in any of these reports, Google has said, explicitly, they’re going to introduce fake data, what they call noise, to obfuscate the data so that there can be a no one-to-one identification.

Summary attribution reporting is worse, depending upon your perspective. I think from the perspective of an advertising agency, it’s worse in that it doesn’t provide us with much in the way of value. You get a summarized report that tells you there were X number of conversions that took place, they’re worth a total of Y, so you might be told there were 10 conversions, they were worth $5,000. You don’t get the times or the individual values of the conversion, so if you’re selling more than one thing, or if you value your conversions differently, you don’t know what happened at all. To your point, we’re going to need to go back to directional reporting and directional attribution. I think much more to the point, we’re going to have to be in a paradigm where we continue to do what we’ve done here, we’ve taken control of our own destiny, we’ve created instrumentation that gives us the information that we need to understand the efficacy of our advertising campaigns and our creative and our messaging, without having to rely on any third-party. I think that, to me, is the big message in all of this. You can’t rely on third-parties anymore; you have to figure out a way to do this in a manner that you control. 

Alex: Right, and I’m excited for that because as automation has taken hold, I think a lot of people in the industry have started to wonder, how can I separate myself? How can I differentiate myself as a marketer? What value can I provide? This new paradigm provides a real opportunity for people who do leverage data in smart ways, who do go back and really understand their audience and do great marketing and great advertising, it provides a way for them to differentiate themselves from the rest of the pack, even in the age of automation.  

Aaron: Yeah, I think that’s a really good point. I mean, you made the point, in the age where an advertiser is going to put up a billboard, they were very careful and thoughtful about the creative for that billboard because they needed to live with it for a long time, and the signals were going to be distant. In an age now where you know that creative is the thing that you can vary to optimize, and creative has to really compellingly attract attention, communicate your message, I think spending more on creative, more time, more effort, more care, and more variation, it’s going to be algorithmically required. It is now by the platforms, but it’s going to be required in terms of just the efficacy of marketing campaigns as well.  

Alex: Absolutely.  

Aaron: Well, you’ve described the approach that we’ve taken and kind of your view of where the industry is headed overall, as we think about on the advance of privacy regulations, the things that are happening now that we’re told are going to happen this year in terms of third-party cookie deprecation, any other advice that you would share with folks? 

Alex: That’s good question. Use the data you have as efficiently and as well as you can, essentially. 

Aaron: I think that’s great advice. Well, this has been very helpful. Thank you, Alex. I really appreciate it. 

Alex: Thank you. It’s been great. 

Related Links

To learn more about the topics discussed in this episode, check out the links below.

Apple announces powerful new privacy and security features 
Navigating the Impacts of Google’s Privacy Sandbox on Digital Advertising 
Clarity for HIPAA Compliance From OCR’s Updated Guidance on Online Tracking 

Questions or comments

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