Cookies are out, context is in. People Inc.’s Jonathan Roberts joins The Big Impression to talk about how America’s biggest publisher is using AI to reinvent contextual advertising with real-time intent. From Game of Thrones maps to the open web, Roberts believes content is king in the AI economy. Episode Transcript Please note, this transcript may contain minor inconsistencies compared to the episode audio. Damian Fowler (00:00): I'm Damian Fowler, and welcome to this edition of The Big Impression. Today we're looking at how publishers are using AI to reinvent contextual advertising and why it's becoming an important and powerful alternative to identity-based targeting. My guest is Jonathan Roberts, chief Innovation Officer at People Inc. America's largest publisher, formerly known as Meredith. He's leading the charge with decipher an AI platform that helps advertisers reach audiences based on real time intent across all of People Inc. Site and the Open Web. We're going to break down how it works, what it means for advertisers in a privacy first world and why Jonathan's side hustle. Creating maps for Game of Thrones has something for teachers about building smarter ad tech. So let's get into it. One note, this episode was recorded before the company changed its name. After the Meredith merger, you had some challenges getting the business going again. What made you realize that sort of rethinking targeting with decipher could be the way to go? Jonathan Roberts (01:17): We had a really strong belief and always have had a strong belief in the power of great content and also great content that helps people do things. Notably and Meredith are both in the olden times, you would call them service journalism. They help people do things, they inspire people. It's not news, it's not sports. If you go to Better Homes and Gardens to understand how to refresh your living room for spring, you're going to go into purchase a lot of stuff for your living room. If you're planting seeds for a great garden, you're also going to buy garden furniture. If you're going to health.com, you're there because you're managing a condition. If you're going to all recipes, you're shopping for dinner. These are all places where the publisher and the content is a critical path on the purchase to doing something like an economically valuable something. And so putting these two businesses together to build the largest publisher in the US and one of the largest in the world was a real privilege. All combinations are hard. When we acquired Meredith, it is a big, big business. We became the largest print publisher overnight. (02:23): What we see now, because we've been growing strongly for many, many quarters, and that growth is continuing, we're public. You can see our numbers, the performance is there, the premium is there, and you can always sell anything once. The trick is will people renew when they come back? And now we're in a world where our advertising revenue, which is the majority of our digital revenue, is stable and growing, deeply reliable and just really large. And we underpin that with decipher. Decipher simply is a belief that what you're reading right now tells a lot more about who you are and what you are going to do than a cookie signal, which is two days late and not relevant. What you did yesterday is less relevant to what you need to do than what you're doing right now. And so using content as a real time predictive signal is very, very performant. It's a hundred percent addressable, right? Everyone's reading content when we target to, they're on our content and we guaranteed it would outperform cookies, and we run a huge amount of ad revenue and we've never had to pay it in a guarantee. Damian Fowler (03:34): It's interesting that you're talking about contextual, but you're talking about contextual in real time, which seems to be the difference. I mean, because some people hear contextually, they go, oh, well, that's what you used to do, place an ad next to a piece of content in the garden supplement or the lifestyle supplement, but this is different. Jonathan Roberts (03:53): Yes. Yeah. I mean, ensemble say it's 2001 called and once it's at Targeting strategy back, but all things are new again, and I think they're newly fresh and newly relevant, newly accurate because it can do things now that we were never able to do before. So one of the huge strengths of Meredith as a platform is because we own People magazine, we dominate entertainment, we have better homes and gardens and spruce, we really cover home. We have all recipes. We literally have all the recipes plus cereal, seeds plus food and wine. So we cover food. We also do tech, travel, finance and health, and you could run those as a hazard brands, and they're all great in their own, but there's no network effect. What we discovered was because I know we have a pet site and we also have real simple, and we know that if you are getting a puppy or you have an aging dog, which we know from the pet site, we know you massively over index for interest in cleaning products and cleaning ideas on real simple, right? Damian Fowler (04:55): Yeah. Jonathan Roberts (04:55): This doesn't seem like a shocking conclusion to have, but the fact that we have both tells us both, which also means that if you take a health site where we're helping people with their chronic conditions, we can see all the signals of exactly what help you need with your diet. Huge overlaps. So we have all the recipe content and we know exactly how that cross correlates with chronic conditions. We also know how those health conditions correlate into skincare because we have Brody, which deals with makeup and beauty, but also all the skincare conditions and finance, right? Health is a financial situation as much as it is a health situation, particularly in the us. And so by tying these together, because most of these situations are whole lifestyle questions, we can understand that if you're thinking about planning a cruise in the Mediterranean, you're a good target for Vanguard to market mutual funds to. Whereas if we didn't have both investipedia and travel leisure, we couldn't do that. And so there's nothing on that cruise page, on the page in the words that allows you to do keyword targeting for mutual funds. (05:55): But we're using the fact that we know that cruise is a predictor of a mutual fund purchase so that we can actually market to anyone in market per cruise. We know they've got disposable income, they're likely low risk, long-term buy andhold investors with value investing needs. And we know that because we have these assets now, we have about 1500 different topics that we track across all of DDM across 1.5 million articles, tens of millions of visits a day, billions a year. If you just look at the possible correlations between any of those taxonomies that's over a million, or if we go a level deeper, over a hundred million connected data points, you can score. We've scored all of them with billions of visits, and so we have that full map of all consumers. Damian Fowler (06:42): I wanted to ask you, of course, and you always get this question I'm sure, but you have a pretty unusual background for ad tech theoretical physics as you mentioned, and researcher at CERN and Mapmaker as well for Game of Thrones, but this isn't standard publisher experience, but how did all that scientific background play into the way you approached building this innovation? Jonathan Roberts (07:03): Yeah, I think when I first joined the company, which was a long time ago now, and one of the original bits of this company was about.com, one of the internet oh 0.1 OG sites, and there was daily data on human interest going back to January 1st, 2000 across over a thousand different topics. And in that case, tens of millions of articles. And the team said, is this useful? Is there anything here that's interesting? I was like, oh my god, you don't know what you've got because if you treat as a physicist coming in, I looked at this and was like, this is a, it's like a telescope recording all of human interest. Each piece of content is like a single pixel of your telescope. And so if somebody comes and visit, you're like, oh, I'm recording the interest of this person in this topic, and you've got this incredibly fine grained understanding of the world because you've got all these people coming to us telling us what they want every day. (08:05): If I'm a classic news publisher, I look at my data and I find out what headlines I broke, I look at my data and I learn more about my own editorial strategy than I do about the world. We do not as much tell the world what to think about. The world tells us what they care about. And so that if you treat that as just a pure experimental framework where this incredible lens into an understanding of the world, lots of things are very stable. Many questions that people ask, they always ask, but you understand why do they ask them today? What's causing the to what are the correlations between what they are understanding around our finance business through the financial crash, our health business, I ran directly through COVID. So you see this kind of real time change of the world reacting to big shocks and it allows you to predict what comes next, right? Data's lovely, but unless you can do something with it, it's useless. Damian Fowler (08:59): It's interesting to hear you talk about that consistency, the sort of predictability in some ways of, I guess intense signals or should we just say human behavior, but now we've got AI further, deeper into the mix. Jonathan Roberts (09:13): So we were the first US publisher to do a deal with open ai, and that comes in three parts. They paid for training on our content. They also agreed within the contract to source and cite our content when it was used. And the third part, the particularly interesting part, is co-development of new things. So
