marketer of the month

EPISODE 133: Marketer of the Month Podcast with Nicholas Thompson

Hey there! Welcome to the Marketer Of The Month blog!

We recently interviewed Nicholas Thompson for our monthly podcast – ‘Marketer of the Month’! We had some amazing insightful conversations with Nicholas and here’s what we discussed about-

1. Strategies for ensuring The Atlantic’s relevance and growth in the digital age.

2. The transition to consumer revenue: The Atlantic’s path to sustainability.

3. Targeting new subscribers: Geographic expansion strategies.

4. Addressing bias in AI Algorithms.

5. The use of AI in The Atlantic’s operations: Current and future applications.

6. Digitizing and monetizing historical content: The Atlantic’s archive project.

7. OpenAI’s rise over Google in attracting top AI talent and implications for the future.

About our host:

Dr. Saksham Sharda is the Chief Information Officer at He specializes in data collection, analysis, filtering, and transfer by means of widgets and applets. Interactive, cultural, and trending widgets designed by him have been featured on TrendHunter, Alibaba, ProductHunt, New York Marketing Association, FactoryBerlin, Digimarcon Silicon Valley, and at The European Affiliate Summit.

About our guest:

Nicholas Thompson is the CEO at The Atlantic. Nick brings editorial expertise from Wired and He boosted digital subscriptions at Wired by 300% after implementing paywalls. Thompson co-founded Atavist, authored “The Hawk and the Dove: Paul Nitze, George Kennan, and the History of the Cold War,” and covers topics like Facebook scandals and marathon running.

From Print to Profit: The Atlantic’s CEO Nicholas Thompson Charts the Journey to Consumer Revenue

The Intro!

Saksham Sharda: Hi, everyone. Welcome to another episode of Outgrow’s Marketer of the Month. I’m your host, Dr. Saksham Sharda, and I’m the creative director at Outgrow. co. And for this month we are going to interview Nicholas Thompson, who is the CEO of The Atlantic.

Nicholas Thompson: Great to be here. Thank you.

Don’t have time to read? No problem, just watch the Podcast!

Or you can just listen to it on Spotify!

The Rapid Fire Round!

rapid fire

Saksham Sharda: So let’s start with the rapid-fire round. Okay. The first one is, at what age do you want to retire?

Nicholas Thompson: 90.

Saksham Sharda: How long does it take you to get ready in the morning?

Nicholas Thompson: Five minutes.

Saksham Sharda: Most embarrassing moment of your life?

Nicholas Thompson: Pass.

Saksham Sharda: Favorite color?

Nicholas Thompson: Blue.

Saksham Sharda: What time of day are you most inspired?

Nicholas Thompson: 10:00 AM.

Saksham Sharda: How many hours of sleep can you survive on?

Nicholas Thompson: Six.

Saksham Sharda: Fill in the blank. An upcoming journalism trend is _____.

Nicholas Thompson: AI data analysis is amazing.

Saksham Sharda: The city in which the best kiss of your life happened?

Nicholas Thompson: Goffstown, New Hampshire.

Saksham Sharda: Pick one. Mark Zuckerberg or Elon Musk

Nicholas Thompson: Pass.

Saksham Sharda: The biggest mistake of your career?

Nicholas Thompson: Trying too long to be an independent freelancer and not joining an organization.

Saksham Sharda: How do you relax?

Nicholas Thompson: Playing with my kids.

Saksham Sharda: How many cups of coffee do you drink per day?

Nicholas Thompson: Two.

Saksham Sharda: A habit of yours that you dislike?

Nicholas Thompson: Checking the Red Sox scores at night.

Saksham Sharda: The most valuable skill you’ve learned in life?

Nicholas Thompson: Resilience.

Saksham Sharda: Your favorite Netflix show?

Nicholas Thompson: Pass.

Saksham Sharda: The last song you’ve been listening to?

Nicholas Thompson: John McLaughlin and Al di Meola in San Francisco.

Saksham Sharda: The last movie that had an impression on you?

Nicholas Thompson: The lives of others.

The Big Questions!

Big Questions

Saksham Sharda: What approaches or strategies have you found most effective in ensuring the Atlantic’s relevance and growth in the evolving digital age?

Nicholas Thompson: So, the most important thing that we’ve done is transition to a business model that’s primarily driven by consumer revenue. Meaning the majority of the money we make now is from subscribers, and we still have a thriving advertising business. We’re working on trying to set up a thriving TV and film business, but we are making much more money from subscriptions than we used to. So then the question is, how do you do that? Well, you have to figure out what makes people subscribe. It’s partly what they think about the brand. It’s when they read certain stories, how they feel about those stories. But the main lever that we control is the paywall. And so figuring out where we use the paywall, how we set up the paywall, how we optimize the paywall to interact with our advertiser and inventory, how we tell people the features of the Atlantic once they subscribe to the Atlantic, how we get them back, how we get them to renew. There’s a giant math problem where you want to put friction in front of people who are likely to subscribe. You don’t want to put a paywall in front of people who are not likely to subscribe. You want to make sure with each person. You are giving them things that make them satisfied with their subscription so they’re likely to return. You want to make the subscription process as fast and efficient as possible. Each one of those steps is extremely complicated, with hundreds of questions embedded in each of them. So my two years as CEO so far have been to improve that, and we’ve seen incredible growth. We’ve seen extreme economic benefits to the publication, and I hope it will lead to its long-term health.

Saksham Sharda: And is there a particular segment demographic that is very likely to subscribe?

Nicholas Thompson: You know, we have a plurality. You know people who are more advanced in their careers, who are in positions of leadership, who are highly educated are more likely to subscribe. But it’s our view that one of the challenges is to find pockets of readers who don’t know about the Atlantic who would be likely to subscribe. So we’re looking right now in geographic regions that have high Atlantic affinity but low knowledge of the Atlantic. So places where people who know about the Atlantic think it’s great, but we’re not. A lot of people know about it. And then we’re going to advertise. We’re going to run Facebook campaigns there. So New Hampshire, for example, New Hampshire is a state where a lot of people are drawn to the Atlantic. They like the idea of lots of opinions of no party or click-free thinking of different ideas. It ties into the way a lot of people in New Hampshire think about the world. So the people in New Hampshire who know about the Atlantic like it. But we don’t have a ton of subscribers in New Hampshire. And, if you survey people in New Hampshire, not enough of them know about the Atlantic. So looking for areas and pockets like that where we can reach new people is one of our goals.

Saksham Sharda: So you recently talked about the risk of biases in AI algorithms. Could you talk about your theories regarding the mitigation of AI biases when training future models?

Nicholas Thompson: Yeah, so any AI model is going to potentially have the biases embedded in it of the data that it’s trained on. So if you train an AI model on the criminal justice system and you ask it to sentence people and court, it will be racist because, historically, sentencing has had some racial biases in it. And so one of the things you need to do is you need to figure out what all the biases in the data are. What are the consequences of the biases, and what do you do to mitigate them? Now the idea isn’t that you need to remove all biases because, essentially, biases are one of the key features. You would like the algorithm to be biased against guilty people, right? So you need to be able to identify what are the things that you are willing to have the algorithm consider and what are the things that you are not. And it gets to extremely complicated ethical questions, extremely complicated philosophical questions, and extremely specific use case questions. So coming up with a general rule and a general framework is pretty tricky, and pretty hard. But there are a couple of principles that you should follow. One is as much transparency as you can see. Secondly, checking your results, it looks like this happened when we used this algorithm. Do we understand why? And is that an outcome that we like? And then third, try from the very beginning to make sure that the data you feed it is as pure as possible.

Saksham Sharda: And to what extent has the Atlantic been using AI in its articles or for research or co-authoring? Is any of that happening?

Nicholas Thompson: Not really. I mean, AI is embedded now in all software. So any software that you use has AI, right? So we have spam filters at the Atlantic that filter our email. Those are using AI, thank goodness. We are trying to figure out how to use AI to make our ads more interactive. And we have figured out cool ways of using AI to help our audience team identify what stories to promote. We’re trying to figure out ways to use AI to send emails to readers that will give them the Atlantic stories that they’re most likely to be interested in. Personally, if I’m writing, I might use AI to help me research something or understand something. I might go into GPT 4 and say, you know, help me understand this process that I’m trying to make sense of. But we don’t have, just as far as I know, we don’t have writers who are using it in an intensive way in the reporting process. Individuals may use it as a copyediting tool, but right now, the editorial team. It’s very much The Atlantic, a magazine by humans for humans made by humans.

Saksham Sharda: What are the challenges and benefits of digitizing historical content dating back to 1857 and monetizing it in the digital age?

Nicholas Thompson: Yes, this is one of the most fun projects we did at The Atlantic. We have this incredible archive. The magazine was created in 1857 by abolitionists trying to preserve America during the Civil War. We have all these stories, and when I came in, the vast majority of them had not been digitized. You couldn’t read them on the Atlantic Archive. You couldn’t search for them on So we said, well, we gotta do this. And, of course, the costs of doing it in any given year will far exceed the benefits, right? Will cost a million dollars. It will cost a lot of money to go in. Because you have to scan, you have to verify, you have to make sure you’ve done it accurately. The costs come down over time. But we had never done it because it was expensive. On the other hand, it’s a one-time cost for a benefit that will continue as long as the Atlantic is out there. So we chose to do it, we put an investment in, and now there are a lot of challenges, right? So a couple of challenges. One copyright, right? So we own the rights to the vast majority of the stories in the archive, but there could have been contracts that were written in the 1950s that limit our rights. And so, going back through and identifying exactly how the rights work, right? There’s a complicated question of image rights, do you have rights to the image if you display it separately? Or do you only have rights to the image if you display it in the context of the article? Do you have the right to the article if you display it as its entity or only if you display it in the context of the entire magazine? So the lawyer spent a lot of time working through it. Then the other challenge is any publication’s been around since 1857, you’ve probably published some things that you’re not psyched about, right? So I was recently going through the archive, and I was looking at the stories that had converted readers to subscribers. And I saw this weird blip. There’s a story that had converted 28% of the people who had read it to subscribers that struck me as wild, right? Usually, it’s, you know, 0.1%. How do you get 28%? So I look at the piece, and it’s a story suggesting that the earth is hollow. And, you know, there’s a big hole in the sphere, right? And it’s from like 1880. It’s not and hasn’t proved to be correct. Now we digitized the archive. We made that story available. People are finding value in it. I don’t know who subscribed because of our hollow molten sphere story. But they’re pieces in the archive that no one can go and read all 40,000 stories. We don’t know. So we’ve put all this stuff out in the world, but in general, the Atlantics archive is amazing. It’s a great historical resource. We’re extremely proud of it, and I’m thrilled we’ve got it out there.

Saksham Sharda: So how do you present something like that to the modern world? If I were to look up that news article on the Atlantic today, am I going to see the date? Does it say it’s an archived article?

Nicholas Thompson: Yeah, it says the date shows the issue you should be able to figure out from a long time ago. Fortunately, the style will also be another tell. You’ll read it, and you’ll think this doesn’t seem like it was written in 2023. But yeah, there is almost certainly going to be a case where someone goes and reads a story from the Atlantic in 1937 and says, you know, why is the Atlantic arguing X, Y, Z? And we have to respond to it and say, well actually that was the Atlantic in 1937. We’re a different publication. We’ve more recently written about this issue and said, you know, ABC that the real problem hasn’t come up yet, but it will.

Saksham Sharda: Is there any danger of making all this archival material available to any AI scanning language model that is just going to go through it without paying any royalties to the Atlantic?

Nicholas Thompson: Yeah, so this is a huge question, and you can look at it both ways. Interestingly, we released our archive after OpenAI finished its scan of the internet. So our archive is not included in GPT-4, but in future large language models, we have made a huge corpus of Atlantic material available. On the one hand, you can think of this as a benefit, right? We’re proud of our content. We have an amazing history. We’re founded by the best human ideas and the best writers. So in a way, we are making the large language model smarter. You can think of that as a plus, right? The Atlantic has always existed to help America understand itself. If we are one of, I don’t know, the top 40 sources in Google’s large language model training data. If we are making it better and making it more accurate and making it more understanding of the American idea, maybe that’s a social good. There’s also a potential economic benefit we could say to the large language models, Hey, we have this great corpus. It’s digitized. We’re only going to license it to you and not you. Right? And we could prevent some large language models and some companies from crawling it. We haven’t made that decision. It’s something that a lot of people with valuable data sets are going to use. But you could also make the case, well now wait, a lot of these companies have crawled it, will crawl it are probably crawling it right now. And so all of this knowledge that the Atlantic and the Atlantic writers and the Atlantic as an institution created all this value is being scraped and included in the software made by these companies that are going to capture all the value. And that’s an argument that the media has been trying to figure out with the tech companies. The media has created very valuable content over its history. Tech companies have built platforms that have made vastly more money than the media has off this content. Is it going to be a situation where maybe the Atlantic reaps 1% of the economic benefit of the archive, and the use it has in large language models will be a situation where we reap more? So that is an open question, but it’s one of the big economic questions that we face.

Saksham Sharda: So speaking of AI, based on the recent news about a top AI researcher returning to Open AI after leaving Google, what are the key factors that allowed Open AI, a smaller company to surpass Google in attracting and retaining top AI talent, despite Google’s initial contributions to the groundbreaking research that transformed the field? And do you think Google will be able to catch up in the future?

Nicholas Thompson: Yeah, this is one of them, if I had a Harvard Business Review class, I would assign a case study on how Open AI got ahead of Google. Because Google is a leader in AI, it’s researchers at Google who came up with the architecture of the transformer network, GPT, generative pre-trained transformers, Google came up with a key idea, the founder of AI, of backpropagation, the underlying technology works at Google. The CEO of Google is all in on AI, Sundar Pichai says it’s the most important invention since fire. He says that maybe five years ago. So you have a company with all the data in the world, all the computers in the world, all the computing in the world, all the money in the world, all the AI talent in the world. And yet somehow they get surpassed by Open AI, which puts out a large language model that is superior to Google’s, at least initially. So why did that happen? A couple of hypotheses. One, small companies are more innovative. They can take more risks, right? That’s more hypothesis two, Google was extremely hamstrung because they care about regulations and they have risks, right? If you have a large language model and it teaches someone how to make a bomb, and they set off a bomb, Google has much more liability than Open AI does. So Google was much more cautious. A third hypothesis, Google had a lot of really smart researchers but kind of working on a bunch of different projects, whereas OpenAI said, you know what language transformers we’re all in. So it’s possible that Google, even though it had all the computing, all the money, all the researchers never made as big a bet on what turned out to be the thing that got us to the incredibly large language models of today. Or there could be some other different explanation for it that somebody will give, but it’s some combination of that. I think then to the last part of your question, will Google be able to catch up to Open AI? You have to think it’s possible. Right now, we’re still very early days. We’re six months after the launch of GPT 3.5. So Bard is underperforming, right? People are using it less. They spend less time on it. It’s less satisfactory. There are classes of questions where Bard can exceed Open AI. The question is whether in two years, I mean this stuff is going to be with us for the rest of human history, will Google catch up to Open AI? You’d be a fool to fully bet against Google.

Saksham Sharda: And what do you think of Facebook instead of having focused on the Metaverse all this time and suddenly realizing that AI is taking off?

Nicholas Thompson: Yeah, I think Facebook bet early on AI they made some very strong hires. They have a philosophy around AI, which is quite different from the other companies on AI. They’re much more into open source. They hired Yann LeCun, one of the three people who’s credited with founding the fundamental research that underlies AI. But it’s true. They bet completely despite being, having been built on the text and then moving to images and having, again, more data than almost any other company on Earth. They could surely have built a large language model that was the match. Again, Facebook had a problem with risk and perception. So they launched a large language model that would help you write a scientific paper. About a month before G PT 3.5 came out, chat, GPT came out, and Facebook got raked across the coals because they’re destroying scientific knowledge. And you know, Facebook has huge reputational risks. They’ve stepped in the bare traps so many times that they’re a little bit wary, but it is also clearly true that they, it seems from where we sit today in, you know, the summer of 2023, that Facebook overestimated the power and potential of the metaverse and massively underestimated the power and potential of large language models and generative AI.

Saksham Sharda: Speaking of your investigations into Facebook, can you share any key takeaways from your investigation into Facebook, and the impact you hope it has on shaping conversations around social media?

Nicholas Thompson: Yeah, so I spent a long time in 2018 or 2019 trying to figure out the culture of Facebook. The way decisions were made at Facebook, the way Facebook responded to the 2016 election, and the way that Facebook responded to the backlash that came after the 2016 election. I think it was a seminal moment in the history of Facebook, and I think Facebook was at the center of a seminal moment in the way Silicon Valley saw itself and the way the world perceived Silicon Valley. So I wanted to tell the story of Facebook to try to get to, kind of, the heart of where Silicon Valley was at that time. My general hypothesis was that Facebook had made a huge mistake where they had built an algorithm that was optimized for attention and for stimulating the lizard parts of our brain, not the more powerful parts of our brain. They had built that, and it created a whole bunch of problems. It had found itself in this political pickle. And then because it didn’t want to upset Republicans, it had kind of turned a blind eye to a lot of stuff that was happening on the platform that was not a Republican or Democratic issue, but in the summer of 2016, happened to be more beneficial to the candidacy of Donald Trump, right, than the candidacy of Hillary Clinton. And so Facebook kind of turned a blind eye, it allowed the propagation of fake news, and it allowed the algorithm to kind of spin out of control. It allowed, you know, Russian disinformation artists to run their campaigns on the platform. All of this then blew up. You know, in Facebook’s hands after the election, it led to an employee revolt. It led to backlash from the media. It led to a lot of chaos. It led to problems obviously in Congress, and it led to Facebook’s economic performance being fine if you were invested in Facebook in 2016, you know, maybe not your best investment, but certainly totally reasonable. But it’s led to a real perception problem for Facebook. And so the goal of those stories was to understand exactly how they’d made those mistakes, what mistakes they made. It’s funny to think back, you know, in 2016, Facebook had a reputation that was roughly the reputation that Apple has now, like a fairly pristine reputation. A place where, you know, one of the best places in the world to work. Like EV Smart, everybody wanted to work at Facebook. The perception of the company has changed grammatically since then. They still create, you know, really smart products. They still make very good decisions. People still use WhatsApp, Instagram, Facebook Blue app Oculus. But it’s a company that has had a very rocky road since then.

Saksham Sharda: So I see it seems that a recurring theme here is big companies need to be more aware, can take fewer risks, and need to be more aware of integrity. And you feel that also holds to journalism as well. Are there smaller media outlets that get away with a lot of media attention? Compared to big, you have to be more careful about the story they’re putting out.

Nicholas Thompson: Well, I think it’s true that if you are a larger entity, whether you’re a bigger celebrity or whether you’re a bigger publication or whether you’re a bigger tech company, you have to be more aware of the risks of making a mistake. Now, this doesn’t hold for everybody. Elon Musk doesn’t believe these rules apply. He will say anything. He will do anything. He will take any risk. He will tweet whatever is on his mind, right? And he’s been fine. Some people can avoid the laws of gravity. Elon went out there and, you know, made up all kinds of crazy statements about Tesla’s self-driving capabilities as we’re now seeing as, you know, court cases move forward about autopilot crashes. And it hasn’t affected him, you know, because he’s such a visionary. After all, he’s such a product genius because he’s made these incredible companies because he’s built this, you know, love of his personality. So I will say that it is true that many tech companies have to be worried about these forces and these risks, not all of them in the media. Yes, absolutely. If something happens in the world, right? So there’s an insurrection in Russia. We don’t know exactly what’s going on. You work at The New York Times, and you work at the Atlantic, you have to be much more careful, right in the sort of fog of misinformation. You have to spend a lot more time verifying. But are we sure the Persians are doing this? Are we sure the Persian is in Belarus? Are we sure there’s been a deal? Are we sure that the tanks have turned around? Are we sure that tanks are coming to Moscow? If you’re at a smaller publication, you can take more risks. You know, there’s less of a consequence if you get something wrong. If you’re an individual on Twitter, even less so, doesn’t mean one is better than the other. It’s just, you know, different worlds that institutions and entities live in.

Saksham Sharda: So could you tell us now, pivoting a bit, what inspired you to write The Hawk and the Dove on Cold War history?

Nicholas Thompson: Yeah, that’s a fun question. So The Hawk and the Dove was a book I wrote, and published in 2009, and it was a history of the Cold War told through the rivalry of Paul Nitze and George Kennan, Nitze was my grandfather. And I didn’t know a ton about his life. I knew that he had worked in the American government from the beginning of the Cold War, right after World War II, up through the end, up through 1990. George Bush’s administration book hypothesized that these were the only two men who were involved in the biggest conversations about nuclear war, the Cold War, and American foreign policy from the beginning of the Cold War to the end. So if you want to tell a story about this period in American history, you can tell it through the rivalry and friendship of these two men. Now, the inspiration came in April of 2005. So my grandfather died, Nitze died in 2004, and then Kennan died in 2005. And I was reading Kennan’s obituary. I was at my father’s house, he lived in Southeast Asia at the time, and I was reading Kennan’s obituary in the Times. And I thought, my God I didn’t realize quite how interesting a life he had lived nor how much it had overlapped with my grandfather’s. And I talked to my father, I said, oh yes, George Kennon was at my wedding to your mother. And it was a startling realization that Kennan, despite being opposed to my grandfather, was a dove, right? We should throw our nuclear weapons into the sea. You know, our building up our arsenal, as you know, pushing the Soviet Union to an extreme position is making war more likely. Whereas my grandfather’s hypothesis, no, the Soviet unions have malignant intentions. We need to build up our nuclear arsenal as much as possible to deter them with very different views, both with the same end goal of preventing nuclear war and maintaining America’s position in the world, but with entirely different strategies to get there. I was amazed to realize in that comment my father made that the two men had been close enough friends to come to the weddings of their children. And so that made me wanna start looking into their lives and made me want, and I wrote an essay about the two of them, and it was the rare essay where I was given, you know, my deadline was eight or I was told to write 1800 words, and I filed in 5,000, right? Which is not the kind of thing I do. I’m a very disciplined writer. If you ask me to file 800 words, I will file 800 words you ask me to file on Tuesday. I filed on Tuesday, and I just lost it and became one of those sort of crazy writers who file too much. And I saw that as a sign that I had found a passion for this topic. So I spent it in 2005. I spent the next four years working on the book. I finished it when my wife was pregnant with our first child, and I set a deadline of June 24th, 2008, to finish the book, and that’s when the baby arrived.

Saksham Sharda: Do you find you often have to set deadlines to get something done?

Nicholas Thompson: Oh yeah. I set deadlines. I set goals. I have projects. I have a very refined to-do list that has lists in different categories, the things I most need to do right now, the tasks I need to accomplish today, the other tasks I need to get accomplished, and the most important things I’m working on, writing a book about running a set of tasks, sorting eight different categories of tasks, and moving them in and out through a Trello board to make sure that I’m being as maximally efficient at any given minute as I can be.

Saksham Sharda: Okay. So what do you think are the main challenges for the media industry today, and how can technology help to address them?

Nicholas Thompson: Well, there are a couple of huge challenges. So the biggest challenge is, you know, what will AI do to us? So we are in the information business. AI is an information processing tool, or at least generative AI and large language models. It will completely change the way the internet works. It’ll presumably change the way search works. Most of the people who come to the Atlantic come via search. It will change the way people report stories and write stories. It’ll make it vastly easier to set up competitive publications. Right now, they’re not as good as the Atlantic, but the architecture of the media landscape will change dramatically. So for any given publication, figuring out how to maintain your brand and how to maintain your business model is extremely important, and extremely complicated. So that’s challenge number one. Challenge number two for any individual, for any other writer, for any individual publication, figuring out how you’re going to use it. Are we going to use it on the business side? How are we going to use it? On the editorial side, right at the Atlantic, we’re pretty aggressive about using it to make business processes more efficient and very conservative about ways we incorporate it into editorial because there are such risks. Every publication has to figure that out. Then outside of AI, the question of how you build a sustainable financial model, right? We used to have a fantastic advertising position. You want to reach people interested in big ideas about, you know, foreign policy. You buy an ad in the Atlantic, and you reach them, right? If you want to reach people who care about new technology products, you buy an ad in Wired. That’s a great way to reach them. That’s part of why magazines exist to create this bundle. Facebook came along. If you want to reach somebody who cares about technology, you can micro-target that, or Google, you can target someone who searches for interesting things in technology. So suddenly, they’ve built a product that had a better advertising proposition for many advertisers than we had. So this thing that had built the media industry and made it immensely profitable. Classified ads used to be immensely profitable for newspapers. Craigslist came around, and suddenly, classified ads were not that profitable. So figuring out an economic model as the internet changed dramatically, the way you can support publication, and then doing that as AI changes it, once again, is a huge challenge for the media. So figuring out how to navigate that and then also trying to figure out how to navigate it at a moment where social media has disaggregated trust, it’s disaggregated, you know, it’s created a very different dynamic between the public and media where there’s not a small number of publications who everybody trusts a lot, they’re more publications, people trust them a lot less. They’re multiple information sources. You can rely on some individual whom you may trust more than a publication. It’s changed the nature of trust. The media hasn’t handled that perfectly. So trust in the media has declined. Competition is coming from a whole bunch of different places. So navigating that is an additional challenge. So there’s the AI challenge, there’s the economic challenge, and then there’s the trust challenge.

Saksham Sharda: And what do you think of the ban on Facebook from putting out news from websites as recently happening in Canada?

Nicholas Thompson: Yeah, so the Canadian government said to Facebook and their social media platforms, Hey, if you’re going to link to news sites, you have to pay them, right? And the argument is Facebook gets a lot more money by showing news on its platform than the news publications get from having people come to them, right? Lots of people go to Facebook, they absorb news, maybe they see the link, and they see the headline, they don’t click on it. So we run an Atlantic story, you know, there’s like a link in Facebook, it has the headline, maybe it has the art. People see it, Facebook gets some benefits because people spend more time on Facebook. Maybe they see ads on Facebook. The Atlantic gets no benefit unless somebody clicks on it. So Canada said, right, you have to pay the media companies. Facebook then took the natural response, which was to pay the media companies. How do you define media companies? How are we going to pay? This is absurd. We’re not going to do it. And this is blackmail, so we’re going to just cut off all links. The consequence of that is traffic to news publications from Canada is going to plummet. So at the Atlantic means, many more people will click on those links. Many fewer people will click on those links, and we will make much less money, right? When somebody clicks from Facebook to an Atlantic story, we can sell them a subscription. We can show them ads. We can find all kinds of ways of making money. So Facebook’s response to Canada’s law turns out to be something that’s going to be quite bad for the news industry. So now we have to wait and see if there will be a compromise, right? Will we sort this out? Will Facebook back down? Will the Canadian government back down? I guess that this was a law conceived of by people who thought we were in, like, the 2018 2019 News environment. We’re not there anymore. Facebook news feeds don’t require news links, right? Facebook’s newsfeed is now viral videos. It’s been detoxified. So they can probably live without sophisticated news stories. They can probably be fine, like people aren’t going to stop using Facebook because there aren’t, you know, as many wonderful links to the amazing Atlantic stories. Facebook has already denigrated the ranking value of news story links. So I worry that as a consequence, news in Canada will be banned, and then eventually, Facebook will just knock news off the platform. It’s a very valuable source of acquiring new readers for us. So I don’t know where this will shake out, but I’m not optimistic about the outcome. I fear that a law that was created with the intention of helping the media industry could end up having negative consequences for the media industry.

Saksham Sharda: Alright, so the last question for you is a personal kind. What would you be doing in your life, if not this right now?

Nicholas Thompson: Well, so the big change for me, there are a couple of ways of putting it. So the big change for me was shifting from being a journalist, writing, and editing to being an executive, being a CEO. I could easily imagine a life where I hadn’t made that change, right? The change was kind of a steady series of steps that I began about five years, six years ago at the New Yorker, where I moved to run the website, and became editor-wired. And then, I took this job as CEO. So I’ve moved into more bureaucratic, more business responsibility. Had I not made that first move at the New Yorker, I’d still be editing print features at the New Yorker. A different life. So that’s one possibility. Another possibility is I was a musician in my twenties, played guitar in the Subways, and played concerts. Had I been a little bit better and a little more successful, I might still be doing that. And then last, like, let’s say I had made a hundred million dollars and didn’t feel like working anymore, I would just hang out with my kids and go running into the mountains a lot.

Let’s Conclude!

Saksham Sharda: Thanks, everyone for joining us for this month’s episode of Outgrow’s Marketer of the Month. That was Nicholas Thompson, who is the CEO of The Atlantic.

Nicholas Thompson: Pleasure. Thanks for having me.

Saksham Sharda: Check out the website for more details and we’ll see you once again next month with another marketer of the month.

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