Crumbling Cookies and Audience Targeting

As consumers shift toward using more mobile and connected technology, and changes in Apple’s iOS, brands are on notice to find new ways to track and measure engagement. With cookies no longer reliable identifiers, how can we target users and measure the success of campaigns? Bigeye’s VP of Media and Analytics, Tim McCormack, and Analytics Manager, Maegan Trinidad, discuss why they believe advertisers need to get creative if we want to continue targeting audiences effectively.

Episode Transcript

Adrian Tennant: Coming up in this episode of IN CLEAR FOCUS:

Tim McCormack: We’ll have to plan for reaching users in a different way, but it’s also gonna change, I think, heavily how advertisers and agencies look at putting together media plans. 

Maegan Trinidad: We have to really pivot and find alternatives that don’t depend on cookies, like contextual targeting and lookalike modeling, for example.

Adrian Tennant: You’re listening to IN CLEAR FOCUS, fresh perspectives on the business of advertising produced weekly by Bigeye, a strategy-led, full-service creative agency, growing brands for clients globally. Hello. I’m your host, Adrian Tennant, Chief Strategy Officer. Thank you for joining us. If you enjoy baking, you know, there’s nothing quite like homemade cookies. But whether home-baked or store-bought, cookies crumble, and especially on a summer’s day in Florida, when cookies crumble, they can get a bit messy. Well, in the world of marketing, there are times when things can feel a little bit messy too. For the past couple of years, we’ve had our work cut out for us, as – in addition to keeping up with the ever-changing landscape of digital advertising – we’ve been collectively bracing ourselves for a future without digital cookies. As consumers shift to using mobile devices and other connected technologies, brands are on notice that we’ll have to find new ways to track and measure customer engagement. So in a world where cookies are no longer reliable identifiers, what will become of digital marketing? How will we target users and measure the success of our campaigns? To answer these questions, I’m joined by two members of Bigeye’s Media and Analytics team. Tim McCormack is Bigeye’s VP of Media and Analytics, and Maegan Trinidad is Bigeye’s Analytics Manager. Both believe that we’ll need to get creative if we want to continue reaching our target audiences. 


Adrian Tennant: Maegan, welcome to IN CLEAR FOCUS. 

Maegan Trinidad: Thank you. Happy to be here. 

Adrian Tennant: What led you to pursue a career in research and analytics?

Maegan Trinidad: I went to the University of Central Florida where I was a marketing major in the Business College, and I found myself involved in a behavioral lab ther, which really meant that I helped administer surveys and helped a professor conduct their own research. And I really enjoyed that experience and I just ran with it.

Adrian Tennant: Today, your Bigeye analytics manager. So could you explain what your role at Bigeye entails? 

Maegan Trinidad: I have grown from being a digital media specialist, which was a role where you can grow into different tracks and see which things you were more interested in, and for me that was more of the analytics side rather than media planning or buying, which goes back to the interest in research and really understanding how things work. So I became a digital media specialist and then from there, when I found out that I really excelled in the analytics portion, I grew that role. And now I manage all of the paid social and web analytics reporting, in addition to being a heavy role in audience creation with the strategy team. 

Adrian Tennant: Now, as I mentioned in the introduction – cookies, they’re crumbling. But for anyone new to digital marketing, or would appreciate a refresher, could you explain what cookies are?

Maegan Trinidad: Yeah. Cookies are digital files that websites send to your devices. They are used to follow you around the internet, really. It’s how we are able to track your behaviors as you surf the internet. So they really remember little pieces of what you’re doing throughout your search history, and we’re able to take that information, understand what you’re doing and then implement it through third-party audiences in our campaign targeting. 

Adrian Tennant: So why do we care about them going away? 

Maegan Trinidad: We care about them going away because really we have seen third-party audiences’ performances decline as the audience size continues to shrink. So if you’re dependent on third-party cookies and third-party audiences, you’re gonna get less and less information and you’re really not going to reach as many people. So we have to really pivot and find alternatives that don’t depend on cookies, like contextual targeting and lookalike modeling, for example. . 

Adrian Tennant: For anyone not familiar, what are the differences between first-party, second-party, and third-party data? 

Maegan Trinidad: So for first-party data, that is any data that is owned directly by a company. So if you’re thinking about a company that has a newsletter list, you own that data or if you’re a eCommerce company, you own all of your purchase data and you also own any of the interactions that consumers have on your website or your social media profiles. As far as second party data that refers to when an organization would collect the data and then sell it unanonymized, and they will sell it out. They see that it’s a valuable resource that advertisers can use and they can gain revenue that way by sharing their owned data. For third party data, it’s not necessarily from the publisher themselves. It gets aggregated and anonymized by another party and then sold to different advertisers and platforms that way. 

Adrian Tennant: Okay. So with cookies going away, what are some alternative approaches we can take to audience targeting?

Maegan Trinidad: Yeah. There are a couple that the media and analytics team has already identified. One of the big ones is contextual targeting. If cookie-driven advertising is based on users’ historical, like their browsing history and their actions on websites, contextual targeting is based more on the current content that they’re viewing. And the way that works is you can generate a list of keywords or webpages that we think might be relevant based on keyword research, or just seeing what is related to a certain topic for a campaign.

Adrian Tennant: That’s great. So how do we get that information? 

Maegan Trinidad: Yeah, a big way that we can get that information is through consumer research. We already know that consumer research helps us determine consumers’ self-reported motivators, experiences, their interests. It’s really helpful in informing our campaigns targeting strategies because of that. When we supplement our knowledge from secondary data with qualitative and quantitative data from studies, we then have a more holistic and up-to-date understanding of where our audience is, what media they’re consuming and what they’re influenced by. We are able to bake questions into our surveys and questionnaires to specifically help us develop contextual targeting lists, such as “which of the following phrases do you most associate with this topic?” or “what store or website do you purchase this particular type of product most often?” or even “what type of resources do you typically use to learn about this topic?” 

Adrian Tennant: You’ve also talked to me offline about automatic content recognition, or ACR. Could you explain a little bit about how that works in practice? 

Maegan Trinidad: Yeah. So ACR is a technology that is utilized in OTT and smart TV platforms. It basically samples a portion of the video or audio that is playing on the device and it takes that back into a larger database that sorts the audio file into categories based on what the content being consumed is. So once these buckets are made, they get put into targeting segments that we can put into paid social and more lower funnel direct response channels to help extend the reach of the campaigns. In addition to that, ACR offers the opportunity to purchase inventory directly related to specific events. So if a campaign would do really well during a type of sporting event, ACR offers that opportunity to access the sporting event inventory. 

Adrian Tennant: Well, of course, social media is a major part of most marketers’ plans these days. Maegan, could you talk a bit about how we can use social graph data? 

Maegan Trinidad: Yeah, social graph data is sort of like contextual targeting, but really creates audience based on comments and reviews that are left by consumers. So it takes into account relevant phrases, keywords, and hashtags to build lists for things like in-market targeting, looking for phrases, like, “Can you suggest a type of moisturizer?” or “What’s the best, this type of product?”. It can also be used to identify purchasers by looking for phrases, like “I always buy from this brand,” or “This was a great product for the price,” because that really signifies that they’ve already purchased. They’ve had an experience with this brand or this product, and that can be taken, a list can be built out, and an audience can be created with that in mind to create a similar audience list.

Adrian Tennant: Okay. I know you work on campaigns that use other kinds of targeting beyond those we’ve discussed so far. Could you share a couple of examples with us? 

Maegan Trinidad: Big ones that we’ve been discussing more recently with these changes are time and geo behavioral data. So that would allow us to target users who’ve visited a specific location or region and it also allows us to segment users depending on events that they have attended. So if you attended an event in Orlando in the last month, we can really pinpoint that down based on the date and the location that the event was in. And within this tactic is geofencing, which would allow us to reach users based on whether they enter or leave this particular location. With that comes polygon-ing where we are able to draw a radius or a shape around a specific location so we can really get specific in where we’re reaching those people.

Adrian Tennant: So Maegan, could you walk us through a so-called full-funnel campaign and explain how you might select different types of targeting at each stage of that funnel?

Maegan Trinidad: Yeah. So a full-funnel campaign takes into consideration an entire view of the customer journey. So we can use different channels and optimization events to appropriately drive users from the awareness stage all the way down to becoming repeat purchasers and even brand advocates. Full flannel campaigns really are a good resource for building first-party data audiences and then we can engage with specific users at different points of the consumer journey that way. Starting at the awareness stage at the very top of the funnel, first-party data can be used to suppress existing customers and the impression data that we create as a result can be used to lift brand awareness and recognition with frequency targeting. And the ad engagements and leads that happen as a result can be used as well as we move further down. The second stage of the funnel is intent where we take the first-party impression and engagement data that we generated from the first part of the funnel to reach users who have already seen and are familiar with the brand by now. This is really helpful in generating first-party traffic audiences. At this stage, we take the messaging and make it more personalized to really help them move further down the funnel and drive them to specific content on the website. And then we take segmented retargeting audiences to drive purchases. Again, we can personalize messaging. Be more persuasive and direct as they’re moving further down the funnel as they’ve already visited the website and have even more familiarity. When we generate more sales data, that brings us down to the bottom portion of the funnel, which is repeat purchasers and brand advocates. Taking into account the purchase data and really trying to give them reminders and different messaging that would encourage them to purchase again, or to really encourage them to purchase more if not something that has to be repurchased frequently. 

Adrian Tennant: Maegan, you’ve defined first-party data for us as any information that a company collects directly from its customers and owns. So I’m curious, in what kinds of ways has first-party data been most successful for our clients at Bigeye? 

Maegan Trinidad: So for first-party data, of course, we can use that information to retarget users who we already know, our existing customers, or people who have already visited the relevant websites. But, something we’ve seen increasingly perform well is lookalike modeling, because of the quality and accuracy of first-party data, since it’s coming directly from the source, it makes it really the ideal foundation for look-alike models. We’ve utilized cookieless audiences based on our first-party data such as website visitations or specific interactions through our preferred vendors. 

Adrian Tennant: So Maegan, in the case that a client doesn’t have first-party data themselves, how can we get around that? 

Maegan Trinidad: So, thanks to our close partnership with survey and first-party data vendors, we’re allowed to leverage market research data for audience creation and campaign activation that’s not exclusive to what we own. For example, Amazon DSP, Amazon famously owns quite a number of things, um, and that gives us access to purchase history, web, and mobile app behavior, things like content viewership on Amazon’s OTT and CTV platforms, going as far as Twitch and even IMDB. We also have partnerships with other vendors. A major one that we do partner with frequently offers first-party data tracking to track the products added to virtual shopping carts and from there we can see the category and product preferences of consumers and their shopping habits and even their planning tendencies for shopping.

Adrian Tennant: Well, in addition to analyzing the performance of clients’ campaigns, you also work very closely with me and the other members of our strategy team, often designing and programming quantitative research studies. In what kinds of ways can primary research work in concert with secondary data and help marketers achieve the targeting objectives in a cookieless environment?

Maegan Trinidad: I mentioned a little bit about this earlier, where we’re able to supplement primary and secondary data to really make a more holistic picture. So if we create questions within our surveys and questionnaires to drive us in a certain direction and really see what might inform our campaign as far as what types of media outlets do you consume from, or where do you purchase from? That really lends itself well to our end goal in making a really strategy-infused project from creative all the way to campaign. 

Adrian Tennant: Maegan, thank you very much for being our guest this week on, IN CLEAR FOCUS. 

Maegan Trinidad: Thank you for having me.

Adrian Tennant: We’ll be joined by Bigeye’s VP of Media and Analytics, Tim McCormack, after this short break.

Dana Cassell: I’m Dana Cassell, Bigeye’s Senior Strategist. Every week, IN CLEAR FOCUS addresses topics that impact our work as marketing professionals, often inspired by data points reported in consumer research studies. At Bigeye, we put audiences first. For every engagement, through our own research, we develop a deep understanding of our client’s prospects and customers – analyzing their attitudes, behaviors, and motivations. We distill this data into actionable insights to inspire creative brand-building and persuasive activation campaigns – with strategic, cost-efficient media placements. If you’d like to know more about how to put Bigeye’s audience-focused insights to work for your brand, please contact us. Email

Adrian Tennant: Each month, in partnership with our friends at Kogan Page, The Bigeye Book Club features interviews with authors who are experts in marketing, consumer research, and customer experience. Our featured book for September is Using Behavioral Science in Marketing: Drive customer action and loyalty by prompting instinctive responses by Nancy Harhut. IN CLEAR FOCUS listeners can save 20 percent on a print or electronic version of the book with exclusive promo code BIGEYE20. This code is valid for all products and pre-orders and applies to Kogan Page’s free ebook offer. To order your copy of Using Behavioral Science in Marketing, go to – that’s K O G A N, P A G E dot com.

Adrian Tennant: Welcome back. You’re listening to IN CLEAR FOCUS, and we are discussing how to navigate the cookieless future of digital marketing. Our next guest is Tim McCormack, Bigeye’s VP of Media and Analytics. Tim, welcome back to IN CLEAR FOCUS. 

Tim McCormack: Thank you. Glad to be here.

Adrian Tennant: Before the break, we heard from Maegan about what cookieless targeting would look like in the future. Tim, what other changes are likely on the horizon with the deprecation of third-party cookies? 

Tim McCormack: Yeah, this is a great question because although it’s gonna have a major impact on audience targeting, there’s a lot of areas that this is going to really, spin out to. So one of the first ones, unsurprisingly, is going to be media planning. So of course we’ll have to plan for reaching users in a different way. But it’s also gonna change, I think, how advertisers and agencies look at putting together media plans. That’s because there’s going to be an even further increased preference for the walled gardens, like Facebook, Pinterest, in some ways Google as well, where users are logged in and they’re able to really get in-depth information on their users. There’s going to be a major impact on tracking, and then I think it’s really going to push more and more advertisers to focus on opt-in advertising, which is very different from what we’ve traditionally done.

Adrian Tennant: With so much at stake for advertisers and publishers, how should brands and agencies look at encouraging consumers to opt-in to advertising, especially when over a third of users are reportedly already using ad-blocking to remove ads across the internet?

Tim McCormack: Yeah, I think that this is one of the things that, that maybe firstly, I’m most excited about. When I look at the huge percentage of users who are using ad-blocking, that says to me that right now we’re doing something wrong as advertisers. We have a system where we can be giving users pretty much the content that they should be interested in, the messages that should resonate with them and so many of them are still choosing to opt-out of it. I think by forcing users and advertisers to think about opt-in advertising, what we’re doing is we’re moving digital advertising away from the extremely short-term, performance-driven landscape that it’s heavily been in to do a lot of the brand building, that we’ve heard a lot of consternation about advertisers moving away from. I think this is really a chance to reset and think about what can we do to provide value to our consumers so that they want to hear from us. And that allows us to then get to the personalization and segmentation, to give them the messages that they’re most interested in. It’s really interesting, because this is something that we’re seeing now on the consumer side. But obviously, this is really something that the B2B side has done successfully for quite a long time, given that it has those longer sales lead cycles. So I really think consumer companies are going to have to start thinking about where they provide that value, and how they can convince their customers and potential consumers to be loyal and opt-in. 

Adrian Tennant: Tim, how does the cookieless future impact how we’re going to measure advertising effectiveness?

Tim McCormack: So apart from audience targeting, I think this is the area where we are gonna see the biggest impact from the move to cookieless. Because currently, we’ve been traditionally looking at digital advertising as an arena where we can clearly see the impact, utilizing cookies of someone who is exposed to our advertising and the actions they took. We’ve had reasonably good ability to de-duplicate conversions, and see down to the individual creative level, you know, what has driven action across multiple steps of the consumer journey. Unfortunately, that’s all really been built on the back of third-party cookies, so we’re going to have to take a step back and really rethink how we’re looking at advertising effectiveness without being able to look at each individual piece of creative and say it drove these actions. The good news is, although we’ve had a fairly good, as I mentioned earlier, ability to do this, it’s never been fully perfect, in most cases. So when we’ve looked at attribution, there’s always been some level of modeling built in. There’s always been some level of noise in the signal. And we’ve grown to really think of it as though it’s entirely deterministic and completely accurate when, to some degree, it never has been entirely. What we’ll have to do now, as we take a step back, is start thinking through how is advertising impacting the overall performance of the brand? Are we seeing increases in sales? Are we seeing increases in brand awareness? And we are going to start having to do things like incrementality testing and medium mix modeling to understand what the drivers are for those increases. 

Adrian Tennant: While preparing for a cookieless future is certainly important, why should busy advertisers care about preparing right now when the date that cookies will be fully deprecated continues to be pushed further into the future?

Tim McCormack: So I think it’s important for advertisers to start looking at this now because, as Maegan noted, we’re already seeing some of this impact in our audiences. So if you’re focused on, specifically cookies, you’re gonna see smaller audiences that are performing worse at a higher cost. Likewise, if you’re relying entirely on cookies for your advertising measurement, you’re gonna start seeing more and more noise in that signal. We’ve already seen Google and Facebook move towards really looking at modeled conversions as opposed to deterministic. So they’re already doing a little bit of machine learning there, more than they had in the past. And most importantly, you wanna start doing this now because it’s gonna take some time to test and learn and optimize and get your new systems up and running as efficiently as the ones that you’ve been running for almost the past decade. And on the advertising measurement side, you’re gonna want to have a good baseline to go back to, when you start looking at this potentially a year in the future.

Adrian Tennant: Why did Google choose to push back the date for deprecating the cookie in Chrome?

Tim McCormack: Without being inside of Google, what we’ve kind of come to understand is that it was most likely driven by competition within the market. It does seem like Google thought they could really set the agenda for what would come after cookies, and they have to some degree, with what they call FLoC’s, which is an identifier of groups of users based on interests and behaviors rather than an individual user. However, there have been a lot of other companies who have rushed into this space coming up with other solutions to provide identity resolution, and some of those have proven to be a little bit more popular with advertisers than what we’re seeing with FLoC’s. We’re also seeing that some of their competitors in the programmatic space, so, other DSPs are putting increased pressure on them in DV 360 by allowing for the targeting of unaddressable audiences. So with those two factors, I think Google didn’t feel comfortable, kind of continuing to push this, knowing that it could impact their bottom line as an advertising system.

Adrian Tennant: Tim, how do consumer data protection laws such as the CCPA and GDPR impact cookieless targeting? 

Tim McCormack: So I do think that obviously, these laws are kind of government’s way of working with the market to drive a cookieless future. Ultimately, they do get at really what is the same point, which is driving advertising to either be mass market, where we’re not advertising to an individual user. Or, you know, advertising that is opt-in based where we’re advertising to users who have chosen to interact and hear from your brand. 

Adrian Tennant: Great insights! Tim, thank you very much for being our guest this week on IN CLEAR FOCUS. 

Tim McCormack: Yeah, my pleasure. Thanks for having me.

Adrian Tennant: Thanks to my guests this week, Tim McCormack, Bigeye’s VP of Media and Analytics, and Maegan Trinidad, Bigeye’s Analytics Manager. As always, you’ll find a transcript with links to the resources we discussed today on the IN CLEAR FOCUS page at Just select ‘podcast’ from the menu. If you enjoyed this episode, please consider following us wherever you listen to podcasts and contributing a rating or a review. Thank you for joining us for IN CLEAR FOCUS, produced by Bigeye. I’ve been your host, Adrian Tennant. Until next week, goodbye.

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