Understanding Audience Intent Through Content Consumption with Joetta Gobell of Dotdash Meredith

Key Takeaways:

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(02:31) Leveraging the power of brands to help people in their moment of need.

(04:14) Joetta’s background in math, psychology, and cognitive science shapes her approach to data.

(06:09) Publishing has constantly evolved, requiring adaptability.

(08:58) Human needs haven’t changed — only the way we deliver information.

(10:28) Prioritizing user experience leads to better long-term success.

(14:07) Targeting needs and behavior is more effective than using user data.

(19:25) Data is not the only source of insight — context is more powerful than identity-based targeting.

(24:50) Balancing AI and human teams by understanding each other’s strengths and weaknesses.

(31:05) Understanding content meaning is key to effective advertising.

(40:26) Interpreting data is more valuable than simply collecting it.

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Joetta: [00:00:00] And so internally here at DDM, we really talk a lot about The way we're going to succeed long term is what are the user needs? What are they coming to us for? And why are they coming to that brand? 

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Anthony: Welcome to Data Masters. I'm Anthony Dayton. And today we're diving into the fascinating intersection of media, audience insights and data strategy. My guest today is Joetta Goebel, Senior Vice President of Data Strategy and Insights at dot dash Meredith, the largest digital and print publisher in [00:01:00] America.

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If you've ever read People, Better Homes and Gardens, Investopedia, or my personal favorite, All Recipes, any of the other 40 plus brands, you've engaged with the work of her team, whether you realized it or not. Joetta has a unique background spanning cognitive science, audience research, and media analytics at DDM.

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She leads efforts to harness data driven insights to better serve audiences. While helping advertisers connect with readers in ways that feel natural, relevant and valuable today, we'll talk about how DDM navigates the evolving media landscape, the power of intent driven data over traditional audience targeting, and what all this means for the future of content, privacy, and advertising.

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So let's jump in Joetta. Welcome to data masters.

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Joetta: Glad to be here. 

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Anthony: I think a good place to start. Uh, and I sort of alluded sort of to it in the [00:02:00] introduction, I think many people listening have heard of the spruce and they've heard of a lot of the brands that they interact with from a media perspective, but they don't know what dot dash Meredith, as I've been calling it DDM, they don't know what that is.

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so maybe talk a little bit about, uh, the company and the business how it's organized and in a sense, how you, how you, think about it as a business.

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Joetta: Yeah. So dot dash Meredith, you mentioned a lot of our brands and I think that that is really the way we think about things is we are about using the power of our brands to help people in their moment of need, to get them information, to inspire them, to answer a question for them. And the reason I think it's important to lead with the brand is that yes, we have websites.

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Yes, we have print magazines with an avid subscriber base and, but we also have many other ways that we can use those brands to reach people in their [00:03:00] moments of need to reach people and inspire them, including things like real world events, including things like social presence, all kinds of touch points with newsletters, you name it.

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There are ways to bring these brands to life out in the world to. Achieve that meeting people in their moment of need with high quality vetted expert content and guidance. And that's really how I think about it. And how I think about my role is how do we understand users in that moment of need and give the guidance internally and to our advertising partners on how to make those experiences and engagement, no matter where you're meeting, the brands actually have an impact.

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Anthony: Got it. And. It's not, uh, obvious, uh, from your background, uh, as a math major, what would have brought you into media and publishing. So maybe share a little bit about your personal journey, uh,  into the space.

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Joetta: Absolutely. uh, I'm not going to go through the whole lifespan, but I [00:04:00] did major in college in math, but I also majored in psychology. And admittedly, the reason for both of those majors was not some grand strategic plan, it was just those are really the only classes I liked going to, so it worked out that way.

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So I ended up a psych and math major having no idea that they could actually interact. But then decided that I wanted to continue to grad school and ended up going and getting my PhD in cognitive science, which is really about using math to understand human behavior and information processing. And for me, that's where the magic is and that's what's driven me all the way through to where I am today is how do you use information?

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Research, well constructed questions, like observation. How do you use all of these things that generate all of these signals in a meaningful way to tell stories about humans so that we keep the human at the center? And, you know, I do like to joke with my team that humans are absolutely the [00:05:00] best and my favorite, and we are absolutely the worst.

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And this This role in particular and, and my career trajectory in general has really brought me there. 

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Anthony: And that you're speaking to someone who also was a math major, uh, as an undergrad and,  uh, is now spending a lot of time in a way not using that, uh, math degree, but also very much to your point, very much using that math degree. I always make this point that Uh, at its core, every business is a data business, and I think that's actually kind of particularly true, almost like acutely true in the publishing world.

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Um, and publishing as a, you know, as a business has changed. A huge amount, uh, recently, and, and then if you open the aperture a little bit thinking of our slightly longer arc of history has changed tremendously,  uh, from, the literal mailing of print magazines to people to where we are today. So maybe if you don't mind stepping way back, share a bit about how publishing has changed and what

[00:06:00] makes things so different today in the digital era than they were, in the days of magazine subscriptions.

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Joetta: first of all, I have to call out what you said, which is true. It's changed a lot, a lot, a lot, a lot recently. Um, but that is not a new thing in this space. This isn't a space that's been incredibly stagnant. And I feel like any involvement I've had with media companies and business has throughout my career has always been about.

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Adjusting to change again and adjusting to change again and updating how we think about things and to me that's what keeps it interesting because if you've solved the problem then you just start turning the crank but like if the problem keeps shifting and if the goal and the challenge and the way you can succeed keeps changing it's really interesting to me and I think um it has changed so much I'm gonna give very general high level sort of sense of things where I think there was a lot of you know In, in the days of a few media channels that were very, very, very mass reach.

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And, [00:07:00] like you said, print subscriptions going to your home, which actually is still a very viable desired outlet, just not for everybody, for every topic and for every kind of content and new ways of reaching people have opened up new ways to think about communicating that information and new audiences to reach.

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So, there was a time where. You know, it was billboards, I'm simplifying, billboards and newspapers and magazines, and you know, if you had a subscription, we knew about you, we knew a lot about you, we knew where you lived, we knew what you were interested in, we knew what offer you chose to fill out the little form in the magazine and mail in to get that information or product back, um, and I think as, as, things have evolved, you know, then there was digital arriving, and digital arrived with a promise I think, as all new technology does, that it will solve every gap that you ever had in pre existing solutions.

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And now, digital is the only way to go [00:08:00] because now you can track every interaction and know exactly what people are doing and what they're going to do next. And, as anybody who studies humans knows, no you cannot. Um, I once had an old boss who specifically asked me, Well, if we know all of these things about human behavior and why they're behaving this way, Can't we just predict the stock market?

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And I will admit my answer was like, I mean, if I mean, if I could do that, I wouldn't work here. Like,

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Anthony: There's a hedge fund with your name on it. Exactly. 

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Joetta: but, but so I think there was this evolution and then it kind of kind of became this sense of like, oh, only if we can then measure it in this digital way. Is it meaningful only if we can attach an identity or a number to something? Is it a meaningful thing? And then I think. Then it broadened to, like, we can reach people through social, we can reach people through, and it keeps diversifying because of evolutions in how we get information into people's hands, how we reach them with that information.

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But the underlying human [00:09:00] needs haven't really changed. Like, you're still trying to figure out, what are you going to feed your children for dinner tonight? And how are you going to, redecorate this living room now that that that couch has fallen apart and you have to rethink the whole thing? These questions are, are,  still we just come to them in many different ways now.

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So each person actually has the opportunity to receive the information. And I think this will continue to evolve in the way that works best for them. And that's been that diversification, but the fun thing about. Putting the human at the center is that the human needs haven't actually changed. So it becomes, what does this make possible to do that I couldn't do before, but how do I continue to meet the core human needs even though I'm moving into this new space?

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Anthony: I think that introduces, uh, an interesting tension, uh, um, that we haven't talked about, uh, which is who's the customer, uh, with DDM? Is it the advertiser, uh, or is it me, the reader? Um, and how do you think about those? and. You mentioned [00:10:00] filling out the little card to subscribe to the magazine, which typically involved paying for the magazine. 

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Uh, that was an important part of the transaction. And then there's also, of course, most magazines are very, uh, advertising heavy that's shifted with time as well. But, um, maybe at a more basic level, this question of like, who's the customer for DDM, the reader or the advertiser or both.

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Joetta: Yeah, and, and, there's, the tension is exactly the right word. And so we talk a lot internally about reinforcing this perspective because it's very tempting to chase We know advertising revenue is very important, right? It's, it's the bread and butter of the business. There are many sources of revenue, but, but advertising  is, is not an unimportant one.

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But if you put advertising revenue before the user, well, we've all had that online experience where you go to look up an answer or read [00:11:00] a story and you have to work really hard to get through the advertising to get to the thing you wanted to learn. And so internally here at DDM, we really talk a lot about how.

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The way we're going to succeed long term is what are the user needs? What are they coming to us for? And why are they coming to that brand? There are a lot of websites out there about home content. How is BHG going to make its mark and convey its point of view in such a way that people want to come back, create experiences that are rewarding?

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And I would argue that a rewarding experience is not A few minutes of closing all the ads so that you can try to find the content. And so, you know, it has natural implications. If you say, look, if we put the user first, then we are going to benefit and our advertising partners are going to benefit because we are going to take advertising.

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and move it out of the bucket of this terrible price you have [00:12:00] to pay to get to the website content and put it in the bucket of actually something additive and informative because I don't work in advertising holding my nose against the whole concept. I actually love advertising and marketing. I think it's really helpful to help consumers understand why they should, how they should think about a product, why they should consider it.

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Who it's for, what it does, because there's so much out there that without that assistance, what are you going to go read the back of every box in a brick and mortar store? No. And so this is a way of helping, but we have to remember that it can very easily, like all things become a way of not helping if you get the priorities upside down.

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So we really do think about if we put our users first. And then we think about why do our advertisers care about reaching those users as the second tier, then DDM will be fun because we will be delivering powerful brands with helpful content to our users [00:13:00] and getting our advertisers in front of the right audiences.

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Anthony: And I really love this idea of thinking about the advertiser, um, as enhancing the experience as for the reader. Um, and the, the challenge, if let me put the words in your mouth and tell me if you agree, the challenge is, um, understanding. The reader and then also understanding  um, what advertisers message and content would be relevant.

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It's finding that connection between the two. So that to your point, I think the reason people are closing these advertisements is because they're not relevant there. This is getting in the way of the thing I want, which is the content and content. If you're doing your job right again to put words in your mouth, you're putting it in front of the reader, you're meeting them at their time of need with relevant advertising that really is adding to the experience, not taking it away.

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So is that a fair way of framing it?

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Joetta: Yeah, absolutely. And it, and it's actually, I mean, it is. It is that [00:14:00] way of framing it that really led to the development of Decipher, which is our intent targeting tool. And the idea behind Decipher is we took a look at, okay, here we have all of these brands and we have all of this data about how people are reading the content, where they're going, and what questions they're asking, how long they're spending, and all of those kinds of questions.

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And are they clicking on a link to go to Amazon to buy those sheets? We recommend it. All of those kinds of things feed into an understanding of what moment of need the reader is in. And we really at dot dash prior to becoming DDM, we really were very focused on, and now with all these brands, we have rich signal to really blow it out.

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We were really focused on. The signal we have is content consumption patterns, because. If you are reading an article on parents. com about how to potty train a toddler, I do not need to know how old you are, what your [00:15:00] gender is, how old the children are in your household. None of that information, if I can know it accurately at all.

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is necessary because you are reading an article about potty training a toddler. I know what moment of need you're in, and I can understand that. And usually when we talk about that, like, all of us recognize that as kind of instantly contextual. Oh, that's contextual advertising. So you guys are just doing contextual to reach users.

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Contextual is the input to Decipher, and what Decipher looks at is people who are reading this content around, let's say, potty training a toddler. stick with that example. What else are they across all of our sites? And you mentioned a lot of the brands. We have finance, we have travel, we have food, we have all kinds of other areas home that we can then understand, not Whether when you read an article about potty training a toddler, what you read next, because [00:16:00] frankly it's probably going to be about how to make a cocktail, because that is a journey to go on.

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But, everybody reading about potty training a toddler, what are they sharing in common in terms of what else they read? And, you'll see things like, oh, they also tend to read content on parents about, um, disciplining children. And they also tend to read content on all recipes about feeding a family and quick and easy meals or fussy eaters or planning family travel.

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And so Decipher surfaces those content connections. And then that that's one of my teams is the team that focuses on using those signals to recommend targeting. And targeting is Specifically not targeting you, because I know you read that thing. It's targeting that content.

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Because I know people reading that content are in that moment of need. And then we can broaden that, because contextual always suffers from like, yeah, but we only have so many articles about potty training a toddler. Like, how many can you write? How do you broaden that to [00:17:00] get the reach you need? Will you understand from people's behavior every day?

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And it's like, 30 to 45 million interactions on our people coming to interact on our sites and brands every day. We use that information to understand the themes of that moment of need, which is insight for our advertising partners. It helps our editors tell better stories and help people, and it lets us know where we can run that campaign. [00:18:00] 

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Anthony: So really important idea there, I think, uh, or at least one really important idea there is this idea of scale that any individual content website. Publisher, if the publisher was narrowly defined by its, um, uh, content, um, this wouldn't work that you don't have enough signal to start understanding, um, who the, who the reader is and what they're interested in.

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So scale sounds like is a really important part about this or part of a part of the, of decipher. And, and, um, but the, the second piece feels like. understanding the, the meaning of that content. It's not enough to say, uh, this is an article that has these keywords in it, or, you know, it was narrowly about potty training to use your example, but talk to me a little bit about, um, how you've, uh, engineered a solution to like, in a way, [00:19:00] understanding the written word, like what, what is the real meaning behind, around these concepts.

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Joetta: Yeah, yeah. And I think that that's that's a really important point. Like, you don't if you want to reach people who are planning family travel, you do not need data at all to know that you should probably run on the articles on trip savvy and and travel and leisure that are about family travel. Like no one.

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I sometimes there's too much of a reliance on Oh, but do we have data for that? like, But data is not the only source of information you have, you know, that if someone's reading about planning family travel, they're probably in the family traveling mindset. So what, what we do and what we rely on to understand that broader moment of need is actually two different things.

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The first is we say like, like, okay, obviously you should run on the articles about family travel. No one's going to be impressed by this recommendation, but I can also tell you, and this is especially important with 40 plus brands, because there's no way any one of us can actually keep track of all of the content that we do have and [00:20:00] write.

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And it's constantly being updated. And so. We look in the first signal, the decipher signals surfaces for the team and my team is verticalized. So I have people who are subject matter experts in travel and subject matter experts in like family content and finance and health to be, make sure they really understand those dynamics too, and they take a look at those signals and they say, Hey, I want to, I'm interested in family travel.

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And then Decipher surfaces the first signal, which is basically, Hey, here are other content groups, because all of our content sits within a high, a structural hierarchy of content. So that articles about gardening are all together, and articles about celebrity relationships are all together, all of those kinds of things.

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And Decipher says, Hey, here are some other content groups that So I have a lot of overlap with what you told me you care about. And for instance, that could be, you know, for family travel, we have content areas that are specifically about family travel. We also have content [00:21:00] areas that are specifically about amusement parks.

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That's a very aligned to the mindset of planning family travel. And one of the exciting things is now that comparison and that tool is actually powered by, um, large language models by OpenAI because of our partnership with them and what that has allowed us to do. And look, I'm not a big fan of take the new tool and slam it on everything.

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I really think you have to think about what does it make possible that you couldn't do before or make better. And in this particular case. We used to look at that just as comparing the content using natural language processing, which does focus a lot on the word choice, the vocabulary, the structure.

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What ChatGBT allows us to do is look at those overlaps and find similar content based on the actual higher order meaning of the content, which is very exciting. Now, granted, like 70 percent of the things are still the same things. They use the same language because they're talking about the same thing.[00:22:00] 

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But then there's this other group of stuff that you discover connections in meaning because of the power of large language models. Now that, sorry it's a very long answer, but that, that, is actually just the part that helps us actually identify All the most contextually relevant stuff. And then we have a data structure where we keep very careful track of all of the content consumption down to the URL level and how they're grouped together and be are able to say people who are reading all of this content, family, travel, amusement parks, then our team in decipher gets.

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a signal back with indices so we understand the strength with the size so we understand the magnitude of like hey here are other things that people reading about family travel are very likely to read about for instance on life wire they're very likely to read about the nintendo switch and tablets Because if you've traveled with children, you know, one of the main challenges is how do you keep them entertaining?

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But we didn't take that assumption and impose it. We let [00:23:00] people's behavior create that emergent connection. And then we essentially divide and compile a list of all of the content areas that we would recommend that you run on in order to reach people in that mindset. And it can give you surprises and teach you things about that mindset.

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And it also should frankly confirm some of the things you think you know, because those come from information too. And so those targets become lists of content areas versus humans that you can reach. Because if you're in the mood, mindset for family travel. That's great. Two days later, you may be reading about planning a romantic trip to Paris, and you don't need to be getting hit with all those family travel ads, because that's not the mindset you're in at that moment.

all have multiple mindsets.

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Anthony: I think the exciting idea here, uh, is, uh, and tell me if you would agree with this. In the past, uh, to build a system like this might have required a lot of human [00:24:00] intervention. Uh, somebody would have to read the article and think to themselves, what's this article about? What keywords would be relevant here?

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And in a way, do what humans are good at, which is understand the meaning of the article and then try to place it in a hierarchy and think about what the concepts inside that are. And now, With vector databases and using the power of the large language model. Again, tell me if you would agree with this.

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We can now have the data tell us what the meaning of this content is, and then fit it into, automatically fit it into the hierarchy, and then connect it to the other browsing habits of that reader. Is that a fair way of summarizing it?

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Joetta: the only slight modification I would make to that is, um, it makes the human be able to do their job better with a smaller set of options and a smaller set of decisions. Because so everything, every [00:25:00] single article and where it sits in our hierarchy is editorially driven. What that hierarchy is is Is is editorially driven by their understanding of their users decipher.

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I always make the joke that I decipher that we built is basically a parasite on top of all this amazing work that everyone else across DDM has done to create this information and structure that we can use. But you're right in that. If someone's writing an article and then they're like, which of these 1 million different things, we have 1500 structural taxonomy nodes or more and asking a human for each article at the volume of content that we have is just unsustainable, but a partnership where we start to bring in, and I think this is, this is a.

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This is still an ongoing learning of what is that right balance because we don't want to lose and we do not want to lose the editorial expertise because personally have a very firm belief [00:26:00] that you get into dangerous territory when you rely entirely on your research team to tell you what the numbers are telling them because that is pretending That whatever numbers we have, first of all, we all know they're noisy because they came from humans in the first place, just because we translated them to numbers doesn't remove that.

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And secondly, that's not the only source of information we have. You know, we have Our travel and leisure editor in chief is, like, travels everywhere and talks to everyone and talks to people in the business. Like, just because she doesn't translate that into a number that goes into the system doesn't mean it's not meaningful.

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And so we're always looking to make sure we balance  like, the, like, assistive work that can come from data analysis and things to this and AI and all kinds of ways of looking at things with that subject matter expertise. Because that's, that's the intangible. That's the real value of the brand is that there are people who really know about travel who are working on this and finding a way to bring those [00:27:00] together.

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But yes, it reduces the noise. It helps create more consistency in application. It has all of those opportunities.

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Anthony: Right. And so it's the human and the machine working together. And, uh, again, um, allowing the human to do the, the, piece of the work, which they are most well suited to, like last I checked large language models, don't travel and have a hard time with that sort of experience. So The real human being is having real experiences, but asking that thoughtful editor, for example, to spend time, you know, categorizing documents, he or she likely would find that to be uninteresting work and more interested in understanding the latest travel.

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Um, Uh, trends and so giving them an opportunity to take advantage of data and machine where, uh, it's, it's just as good as they are, or even better or, and, and, and also kind of checking their work, like finding a way to, validate that the machines are doing the right thing 

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Joetta: Yeah. Yeah. it's, Yeah. I feel it. I think [00:28:00] it's, it's really like, it's a like, collaboration in a lot of ways, which is a weird thing to say, but it is a collaboration.

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Anthony: So let's shift a little bit, um, to the future and what. Your team is working on and acknowledging for a moment that what you've already built with decipher is very innovative. The idea of using machines to categorize content, to find a latent meaning in it, connect that where the reader is in their, in their, uh, journey through content, uh, I really love the idea of showing people who are interested in a trip content about.

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Uh, Nintendo Switch like that, that linkage is not one that I think, you know, one would intuitively come up with. And it's a great example, but where does it go from here? Uh, you know, the extreme version is, we, we don't need any one writing content. The machine just generates the content and we're all, you know, we all, I guess we all go on a trip with our Nintendo Switch and hang out on the beach.

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I don't know. Uh, but, but. Yeah. Where is this really [00:29:00] going? What, how do we think about the future here?

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Joetta: Well, I think the first thing is that DDM, like, Humans will always write our content. AI will never write our content. And now I can't remember the clever phrase that they have for this. So please forgive me, but this idea of if. And AI is writing the content and then another AI is training on that to write the content like that's a spiral and it's not going in the direction we want it to go.

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And so that human nuance experience and creativity is really important. And I think that's, that's foundational and how we think about it is that we, we see the value in particular in something like AI and it's not just AI, but it's really the topic that we're all very. We like talking about right now because new it's exciting.

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We're still figuring it out, but the the value there for us is in how do we, we, we already have all this amazing expert content that we update regularly. How do we, thinking [00:30:00] about the user, create the best experiences for users to take advantage of that information? And I think, um, in terms of where that heads in the future, I think  the toughest, the toughest part about this job is that there are probably like 20 amazing ideas that we could do right now that I really want to work on and it becomes prioritization so that you don't do, you know, 20 crappy things and you do a couple really powerful things and then do a couple more interesting things.

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And so where I think it is in the future in, in that regard, not specific to Decipher, is, is, um, really fully exploiting, fully understanding how technologies like AI can help us create even better, easier, more engaging experiences for users that are rooted in expert human written content that will always be human written. 

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Um, I mean, Um, um, so one of the exciting things in the future for [00:31:00] us, and that, and future as in we have campaigns live right now, is We can use that same understanding we have of human moment of need rooted in our content to understand the moment of need of other content that is out on the premium open web.

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So we can actually say we understand what kind of content you should run on to reach people in looking to plan family travel. We can now help to your earlier point about scale being so important and also not having to go to 45 different places to get the thing you want. Also, we humans love lower effort.

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Um, we can We can actually help identify the right content and help make happen that your campaign, we take our understanding from DDM content and decipher and basically look out at the open web and its content and can actually help our advertising partners know where to run their campaigns there as well.[00:32:00] 

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Anthony: That's really interesting. So now you're as a data asset. Yes. You have this very proprietary set of data about, um, readers on your properties and, uh, Again, thinking about the advertiser as the customer in this context, thinking about actually providing for them. Uh, it's almost like you know, you might not agree with this, but like almost sending traffic to the competitor, like, like you should also be running over here, but to your point that that deepens the relationship you have with that advertiser who now trusts you to infer intent more accurately than, than the competitor, is that fair?

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Joetta: And yeah, and there are ways in some cases where we, right now we're doing it as a managed service, like We can do it for you. Like, we'll take this extended and do it for you. There are so many ways it could go from there. And I obviously running the research and measurement teams do not build the business models around this.

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Um, but, but there are a lot of ways to approach, like, how do you make that Capability impactful and meaningful. But again, always back to what I said in the beginning where it's about [00:33:00] tying it to what the user moment of need is and extending that outward into the premium open.

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Anthony: So, um, let's just talk for a second about the user's moment of need. The one keyword there is the user. Um, one thing I've read about in the media industry is this shift and change in user identification, uh, specifically Google, uh, killing cookies, but more generally, I think there's this idea that, uh, understanding.

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And identifying uniquely, identifying the user, uh, is becoming more difficult. I think equally, perhaps, uh, users or readers themselves are thinking about how do I protect my privacy? And on these sorts of, how do you guys think about that? Um, and are there kind of technical questions or solutions that you wrestle with as it relates to decipher and more generally data?

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Joetta: I think that's Okay, first of all, yes, identity has often been used as a, a kind of direct mapping to addressability. Like, Like, if I know who you are, then I can [00:34:00] reach you with the right information at the right time. And I think the thing But what that means is as signal loss proliferates for all kinds of reasons, like you mentioned, like just shifting consumer understanding of the value of the information they're giving up, and brought new emerging privacy laws, and changes in policy by the big players, like Apple did it, did away with it a while ago, and Google is coming to their way of how they're going to be addressing this, and others have been doing this for a while, where in that case, like, Identity can be meaningless in some of those environments because it's not allowed to be proliferated there.

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But that doesn't mean you can't reach them in the moment of need if the content itself becomes the signal that you append the meaning to. And so I, I, I always think of it as this like flip it on its head thing where instead of like Okay, you read content, so now I know something about you, so now when you show up wherever else, I know something about [00:35:00] you and I'll use that.

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It's the opposite, which is, I know a lot about our content and what it means for people that are reading it. So, whoever you are, and whether you're on Safari, or on Chrome, or Incognito, or you're Block All Your Cookies, kind of like, whatever you do is wholly in your control. And what I am doing is not invasive.

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If you are reading an article about potty training your toddler, you are not going to feel that weird ad creep factor that you feel if some Huggies pull ups show up on there. That's just going to make sense. Whereas if you read that article and then for the next six months, Huggies pull ups chase you around the internet, it feels creepy.

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And, and so I think, I think one of the things we really thought about is In the industry, we have tended to conflate identity with addressability, leading to actually really weird economic situations where all the [00:36:00] advertisers are paying more and more and more and more for this shrinking group of people they can identify.

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And Often unintentionally ignoring all of these people who have all of the same needs and have money to buy those things with or are interested in the services you're offering, but because you can't tie them to an identity or a profile, you don't want to spend there. And so we're able to say like, like, no, we can understand that.

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Which opens up the biggest challenge that I think the industry is really wrestling with now is, and now all together, how are we going to make sure that we're appropriately measuring in a world where we historically have over relied on specific individuals? How are we going to come together to solve that?

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Anthony: So totally agreed. And let me just connect this back to where we started almost, which is we talk about, I said, this, uh, every business is at its core, a data business. And when you think about yourself as a data business, [00:37:00] one needs to think about what is your most important data asset. And I think if I put words in your mouth, what you're saying is we used to think, or maybe Some media properties think that the asset is identity that we have this group of people who are, we can identify that these are our readers.

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And your point is no, uh, because we can build this data asset about our content and again, to connect this back to this idea of meaning and the partnership with open AI and understanding, uh, textual meaning, you could have better, deeper insights. About the meaning of the content on your properties and that actually becomes either as valuable or arguably more valuable asset Than being able to uniquely identify The reader is that a fair way of framing it

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Joetta: Absolutely. And I do think it's really important and you said this that it's, it's not that identity can never play a role. It's not that if I'm a logged in consumer somewhere and I have [00:38:00] voluntarily told you a lot about myself, goodness sake, please use that information. Like,  wouldn't want to argue like, throw everything out.

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I just think we became a little overly reliant on that was the only way to understand how to reach people. And, um, And look, all of this is just a lovely story if it doesn't work, but we, we─ happily works regularly, outperforms other approaches, we have better reach, we can reach into environments where cookie based targeting, for instance, just can't, and we can see that performance and see it really play out.

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And so, It becomes this, like, like, it's a hypothesis until you see it actually work, but it turns out that it, it really actually reaching people in the moment of need is more important and more impactful than reaching someone that you know a lot about.

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Anthony: sure and in your context having better richer deeper more content Uh is the data asset that makes that possible? versus [00:39:00] trying to build a database of people who've registered on your website to use your analogy.

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Joetta: Right, right, yeah. And also the nature of a lot of our content, uh, if you're thinking about the user first, because if you just need identity, then you, you, you can put a login and require people to log in to get access to those. It's all your best content and then you have an identity and you can build that.

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And that has its purpose. I'm definitely not, but the kind of content that we really focus on by and large just doesn't arbitrarily justify, like, if I want to read about how should I think about retiling my bathroom, I'm unlikely to be like, Oh, that's a really good reason for me to have a login to the spruce.

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Like, Like, it's just not a value exchange. So then it becomes, we still do want to understand our users and understand how to engage them. And if we can know more about them, of course, we can build on that. But if you're going to ask someone to give up their information as part of that effort, you're probably going to want to make [00:40:00] sure you're giving them something valuable in return.

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Anthony: And then the value driver there is, is great content. So, uh, I thought I would, uh, leave with one final view to the future or, um, thought about, uh, what could be and. Maybe an unfair question, but if you could make wave a magic wand and get the media industry to understand one thing about data, what would that be?

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Joetta: Okay, I'm going to say this. I am not saying to everyone in data that they actually think this. I'm being, I'm exaggerating. I don't want to insult everyone in data listening to this, but if I could get everyone to understand that the data we have is one source of information and it is also noisy and so what you really have to keep in mind is what are you trying to achieve and long term, how is this going to get you there?

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And so it becomes less about, Collect all the information we can and then figure out how to use it and more [00:41:00] strategically What information do we really have because that's all I mean we looked and we were like, well, we don't have logged in users So what do we have? Well, we have information about what people are reading and that can tell us what they need so that becomes the genesis That's not true of every publisher.

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Not everybody's content is so intent focused. So what I would love is just If we all were like, what is the information you have and what are you looking to achieve? And let's, and let's understand that that's going to be very different and very unique to different perspectives and, and recognizing that that that's always been the case.

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But we have sometimes tended to lean too hard on one single solution as being universal. And this is an opportunity for us to just think about what is it that we're trying to achieve here and how are we going to do it with the signals that we really have? 

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Anthony: I think that's a wonderful point. Um, and it's a very common theme that we hear on this podcast, um, which is connecting the data strategy to a business problem and a business strategy and [00:42:00] ultimately, and, and then I think what you're adding to that. conversation is also then thinking about what are the data assets that you bring to that fight?

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If you, to connect this to your very specific example, if you have a lot of data about content and meaning, how can that be helpful in achieving the business objective of providing world class content and connecting that with an advertiser that can supply and solve a problem, uh, you've really created this straight line between business need my data asset and a business problem, and ultimately that's.

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You know, ultimately what we're trying to do as data professionals.

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Joetta: Absolutely.

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Anthony: Well, uh, Joetta, thank you so much for the time. And this was super interesting. And, uh, I am now going to log into people and learn all about celebrities.

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Joetta: Enjoy.

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