Dr. Centola is a professor of communication, sociology, and engineering at the University of Pennsylvania. His research focuses on how ideas transmit and transform societies through network theory and behavior change. He has explored these ideas in two popular books: How Behavior Spreads: The Science of Complex Contagions and Change: How to Make Big Things Happen. Damon joins the podcast to discuss the most effective approaches to social and behavior change. 

Transcripts of our episodes are made available as soon as possible. They are not fully edited for grammar or spelling.

Tom: Damon, welcome to the show.

Damon: Thanks. I’m very happy to be.

Tom: I am really looking forward to talking to you about the ideas from your book, uh, entitled Change, how to Make Big Things Happen. but first I wanna ask you a couple of questions, really getting to know you of the kind of person who’s going to explore topics like this in their adult life.

So I’m wondering for someone who studies social networks, what kind of position did you occupy in your social network when you were a kid growing up?

Damon: that’s a great question. I grew up kind of between worlds in a way. So I, my parents lived in this sort of, commune. It was basically intentional community, but it’s founded by the quake guards and these principles of like interracial, interdenominational, tolerance.

And, you know, in the 1970s and eighties, that was kind of a big idea. as you can imagine, it was a very activist oriented population. So there are a lot of topical issues at the time.

Um, there was mobilization for women’s rights there, there’s mobilization for anti-nuclear perforation. There’s mobilization for, racial justice and equity.

So there was just a lot of kind of social activity around this kind of stuff, and it felt normal. and so I didn’t really approach, you know, social networks and mobilizing, from an academic perspective until I started reading articles in graduate school. And it was like a revelation because these things I observed as a kid had like a real structure to them and they seemed for the first time that kind of thing that you could actually do a predictive science on.

And that, that really, I think, stimulated the juices for me.

Tom: Yeah, so kind of pulling back the curtain and trying to see like what is the plumbing underneath the things that you saw in your childhood.

Damon: Totally. And I think every kid’s, you know, running around with this little, you know, mini logic, trying to like, figure out the world. Like what are the rules? What are the rules? And you know, when you go from that kind of community where it’s so based in principles of, you know, moral rightness and ethical justice and like, you know, trying to write the world and then you go to middle school, it’s like nothing about middle school is fair or just, or you know, it’s just, it’s more about just getting grades and getting into college.

And it seemed like they were just radically different value systems.

the big questions in those situations is, why are different communities, so in entrenched, in different values, and what would happen if these communities interacted more? would everyone start believing in the same thing? Would certain values from one group spread to another?

and that’s just kind of like a mental exercise as a kid, but then to see it, there’s like serious research science, asking that kind of question was just fascinating to me.

Tom: Yeah.

Was there, a particular teacher or class you took that really like, set your heart on fire for exploring, trying to better understand social norms, social change, social networks,

Damon: I did this kind of unusual college when I started out, which is called St.

John’s, where you basically read the classics. it really opened my mind just in terms of like the pedagogy of your relationship to science. Because instead of having a teacher be the kind of, interlocutor between you and the text, the teacher was there basically in the room as another student.

And we were all learning from the text. And so the teacher was like, quote unquote the best student in the room. But the conversation was like between us and the author. And I think more than anything else that like really kind of woke me from my dogmatic slumber when it comes to like how I approached education in terms of the model of learning from teachers and trying to figure things out.

It really stimulated the, kind of research gene where all of a sudden it was this question of now you’re reading Aristotle and you’re supposed to respond directly to Aristotle as opposed to write a paper that your teacher likes. I think that really got me, got me off and running.

Tom: Yeah. Great. Want to, at this point, pivot to some of the ideas you explore in your book change, which, I really enjoyed reading and reflecting on, and I encouraged to our listeners to read it for themselves. I can’t do justice to the whole book, but I picked four or five different themes in there that I thought, Damon, I’d love to ask you further questions about and give people a taste of, of what they could enjoy by reading it themselves.

So I wanna start by asking about communications technology and how it relates to social change. So my background is as a historian of science and technology,

So I, I like to really think about, the long game, and how things have, have changed on the, on the big scale. So thinking about social change, and how humans communicate. obviously for most of human history, as long as there’s been humans, word of mouth is the primary and sometimes only form of transmission.

Obviously got writing came about a few thousand years ago, but maybe with a printing press, you start to see a new form of, of mass communication where words can spread very rapidly from someone influential like Martin Luther, and then boom, run off tens of thousands of copies of certain pamphlets

But then of course, with the centuries moving forward, we have not just mass communications through printing, but instantaneous communication through telegraph telephone.

and then moving forward, television, radio. And I think maybe that next wave is then internet, email, social media. Not only do you have mass communication, instant communication, you also have sort of the, democratizing the universality and that anyone could at least theoretically rise up, become a US YouTube star and, broadcast their ideas to the world.

So momentous changes in communications technology, I wonder from your vantage point, do you see how deep social change happens? Is there something fundamentally different about how social changes happen in an age of this mass communication versus how it’s happened historically?

Damon: I think that’s one of the more important questions to ask because it sort of tells whether or not the technologies are shaping the potential for society. I would sort of take two prongs in this. One is, you know, to what extent do these technologies shape the potential for our science to understand this process of change?

And so maybe we’re seeing things we didn’t see before, but they’ve been there all along. But now we have data, right? So there’s this sort of, you know, epistemology of like, do we do science differently now?

I think the answer is yes, we actually do, do science differently now.

And there’s the other question, which is, are the fundamental principles, whatever they are, economic tensions or, geographic, Mobilization patterns or networks of, of personal influence? Like what is it that that triggers? social mobilization,

I actually think that that is not that different. but it, it’s very telling the way that the world has been kind of reorganized online, that some of our, I would say worst intuitions about how this is supposed to work actually have become easier and easier to believe because of some of the ways things are structured.

And sothe machinery that actually makes it work is, ironically, it’s easier to study, but on an everyday way it’s actually harder to see. so I’ll say a little bit more about that. I would say my version of that history is to just talk about media communications and start off with like. Radio

So the very first big discovery, this is by, Lazarsfeld and, Katz.

And Katz is the, you know, the sociologist for whom my chair is named at the University of Pennsylvania. And they were doing originally the study of voting behavior. Um, this is back in 44 and 48. And looking at the way in which, advertisements on radio actually influenced people’s discussions and their choice about which candidate to vote for.

And the subtle inference that they made that no one else expected was that actually what was happening was radio signals were going out, they were hitting the population, but it wasn’t as if it was kind of this blanket covering where everyone was getting the radio signal directly and then changing their decision, but there were a small number of people who were pretty attuned to that sort of mass broadcast. And then those people were acting as kind of dissemination agents into the population. then Kasen Feld refined this in the mid fifties in their famous study personal Influence in which they looked at the same exact process. now shifting in from, radio television, looking at the dynamics of how mass. Communications or mass marketing reached populations and it was the same result. It was that it would reach a couple of people who were really attuned to the media and those people would then act as dissemination changes to the population. They invented the term opinion leader. Right? And that was the person who was like this, this linchpin between all this media, machinery and the rest of the population.

And that stuck for several generations. Everyone talk about the opinion leaders who are the opinion leaders, and that is like the latter day term for that is influencer, right? Is like the person who’s sort of responsible for then influencing large amounts of others.

What happened though between then and now was this sort of understanding that once you know either a media machine or the person who mediates it, the opinion leader starts communicating with people in the network. The pattern of relationships among friends and friends of friends in that network can have different shapes, different geometries, and the geometry of that network actually determines how far. Some kind of new idea or some influence process spreads and whether it keeps cascading level upon level, layer upon layer deeper and deeper to the network, or whether it kind of just hits a few people and stops.

And so that question of like how far does it spread and what determines how far it spreads really is where kind of network science in, you know, is this group in Cambridge in like the sixties, but really it was, it was around Harvard and my team in the seventies was where a lot of big ideas, this is where Milgram’s famous small world study where he should have said, you know, how far are people in the US from each other?

Like, if you were to say, how many steps does it take to get from me to, you know, some surfer in California, how would I figure out how many intervening social steps there are to get from me to you know, me to that person?

And the famous result is that, well, some, you know, these sort of trails took 17 steps. Some of them took two steps. but there was an average number of six, right? So you got six degrees and there is this sociologist grad student, mark

Gran better at the time at Harvard who was there when Milgram was doing this. And he had this like deep insight, which was that people tend to know a small cluster of folks really well and the people that you know really well, your trusted sort of,intimate, strong ties. Also tend to know each other because you’re all interacting in the same spaces.

And so that cluster of people has a lot of little triangles in it of, I know you, you know me, friends of friends know each other, but there’s this occasional person that’s not really connected to your friendship or family group. And that person maybe travels in occasionally, or you know them from some previous setting, or maybe you’ve met them at a conference.

And that person is what he refers to as a weak tie because you’re not very close to each other. But his big insight is that that person is also socially speaking very far away. They live in a different social cluster. They have totally different friends, different, information, different experiences.

And so that person is in a position to transmit information across a very far social distance, just through that one interaction. So even though it’s a weak relationship, it’s strong in terms of like the structural pattern of ties in the us. And so if you wanna look for like what kinds of ties are gonna allow us to jump from group to group to group and get six degrees of separation, it’s probably gonna be the sequence of weak ties.

That became kind of a very deep insight. And it built in some ways upon the classic idea of the opinion leader, which is that the opinion leader is also someone who’s gonna know lots of different people. And so some of the people they know will be strong ties, but a lot of the people they know will be weak ties. They’ll have like this vast array of network connections. And then we can imagine that in the way of the modern influencer, which is someone who has like maybe a million ties on a social media network and they don’t really know any of those people. and so the idea that like these ties that don’t mean a lot to us personally, but kind of reach out in all directions are the key conduits for transmission of ideas and behaviors.

That’s an intuition that’s been around now for half a century and it, it lives large in our,imagination, in our media marketing strategies and our political strategies, this was certainly a strategy. They used to try to, up vaccination levels in the conservative community. They got high profile, media influencers, Dolly Parton to like get vaccinated

And the point is that every attempt to use that strategy of the high powered. High Lee connected, weak tie influencer is always inconsistently ineffective when it comes to any kind of social change process.

Potential music cue It works great for selling coconut water. Um, you know, Kim Kardashian can sell lots of coconut water, but when it comes to saying, Hey, why don’t you change your values around vaccination, well winds up happening something really interesting, which is that not only does it not work, but that that person actually loses status as an influencer because social norms are not that easily shifted.

And people who have them actually wind up pushing back and saying, wait a minute, maybe you’re not a member of our community even though you’re so high profile, because we don’t believe that.

And so the question is, and this is sort of the big, the big punchline. Well, okay, if all of that knowledge from, you know, now we’re talking about 75 years of serious science by famous people, leads us to a conclusion that not only doesn’t work, but backfires. Where are we, you know, in terms of the science, and this is where my work really picks up. And with the data, really the best data that we have fromthe mid 2010s up through today. So like just over a decade of really good data, Every single one of these sort of behavior change technologies or movements or, social change campaigns spread by taking hold, not in the center of network, not with highly connected people, but actually taking hold in the periphery of the network where people are much less connected and their connections tend to be embedded in these strong tie networks.

Potentiall music ends

And so what we see here is a pattern of mobilization that contradicts everything we think we know about how networks work, but then once we see it operating really clearly in the data from Arab Spring and the data from Black Lives Matter, right.

then we can look back to all the cases from the, you know, the fifties, sixties, seventies, eighties. And we see actually the same exact mechanisms at work. And it tells a really like deep and consistent story about how networks operate and have always operated. And I would say the hopeful aspect of that is that the mechanisms and mobilization strategies that worked so well to shift, um, social policies really do work equally well even when those networks are online.

Tom: Yeah. Excellent. Thank you.

Another concept that we regularly hear is about things going viral,

and I’d like to explore with you, how is it the virus metaphor for the spread of ideas helpful or not helpful to what you’re investigating?

Damon: Yeah.

It’s a very intuitive way of thinking about things. It turns out that epidemiological approach is also mathematically very tractable. So scientifically it’s nice. but like a lot of human cognitive features, there are some unfortunate biases built in.

And one of them is that. The epidemiological intuition actually really leads us astray when it comes to understanding behavior change because dynamics of behavior, If you come into contact to something you don’t like, you don’t adopt it. You show resistance. Right? And we saw that, for example, the perfect, uh, contrast is between something like the COVID-19, virus versus. Face, masks, right? COVID-19 spread really effectively across social boundaries and political boundaries. National boundaries, face masks did not, right. So face masks, like there was the hard stop when you hit like a political boundary. So much so that it was like you’d see someone from the opposite group wearing a face mask. And so you’d make sure that no one, you know, would wear them.

And that sense in which adopting something is contingent upon your group believing it’s legitimate, that’s not there for simple contagions. Like if a virus is gonna spread, it doesn’t matter how many healthy people, you know, you’re gonna get sick.

but if you’re come into contact with someone wearing a face mask, it really does matter how many non-face mask wearers, you know, because they create this sort of implicit, countervailing influence.

Yeah. And so that’s a, that’s a big way in which the sort of viral intuition has really gotten in our way of our understanding to really the, sort of the policies and the approaches that are best gonna be used to spread social change.

Tom: You mentioned the shotgun strategy. So I’m imagining, lemme take out a, I don’t know what it is, $6 million Super Bowl ad. The shotgun blasted out to all the people watching it and hoping that a tiny fraction by my product here of my idea, whatnot.

You mentioned the silver bullet strategy of let me not do the Super Bowl ad, let me instead find. Dolly Parton, Oprah, whoever, pay them a big fat sum and have them tell the people. So the, the silver bullet where I have a very precise aim, invest all my resources into one person. and then there’s a whole bunch of things, that don’t work either with a shotgun or with a silver bullet. I’m kind of curious, when you look at the variety of ideas out there, in thinking of these different theories of social change, what works best for the shotgun strategy, what works best for silver bullet, and then what are just, really, really difficult and need another approach, besides these perhaps two most intuitive ways of, going about sharing ideas.

Damon: Sure. And the third way is called complex centrality, and that builds in the complex sensation idea, but. The core insight is this, and it sort of requires a little mind bending, but when we look at a social network and we kind of draw the picture, basically imagine a lot of dots.

And then in the center, they’re all kind of draw connected together by lines. But the, the the.in the center has like a lot of lines coming out of it, going in all directions. And that’s our influencer. And not only is that person thought of as highly central in like a mathematical sense and a lot of the, chains come from them or any path goes through them. but in a visual sense, when we do our sort of graph rendering visualizations, the, the bias of those algorithms is to put the most highly connected people in the center. ’cause it makes for a pretty picture.

So now we have like a really strong reinforcement of this cognitive bias of centrality. So what we found is that when we’re talking about something like a virus, then that is the, right concept.

Centrality, we call it degree centrality, basically means the most connected person is really the, the center of the network. and then also works for gossip. And, you know, lots of things that. Follow from that on social media. but when it comes to changing social norms, and again, talking here about support for same sex marriage or joining it for Black Lives Matter, or, changing your political position on something, or even adopting, a kind of technology that’s not well adopted yet, you don’t wanna waste your time doing it unless other people are doing it.

In those cases, the central person is often among the last people to adopt, and there’s two reasons for this.

One is the central person, didn’t become highly connected by ignoring their social ties, right? They became highly connected by being really attentive to who, like the universe they’re connected to. And so if a thing shows up and it’s like only, one or two small people in the periphery, who notice it or are using it, sure they know the central person, you know, can discover that really easily. But they can also notice that like the vast majority of people they’re connected to are not using it.

So it means they’re kind of conservative in that respect of like, you know, waiting till something is proven to be legitimate before they adopt it.

Whereas people who are out in the periphery, have fewer connections. So like the, standard of social proof is, is much easier to reach. but more importantly, when they sort of receive those social connections, they can coordinate with their peers to create overlapping reinforcement for the people next to them.

and what that means is that for those kinds of mobilization campaigns, The center of the network, like where you’re gonna get the most bang for your buck in terms of where to invest, is actually not the highly connected people. It’s actually these little tiny clusters of nobodies out in the periphery that have, it’s not a feature of them personally, but a feature of the network ties among each other, which I refer to as wide bridges, but essentially reinforcing ties from like one part of a little social neighborhood to another part of a neighborhood.

and the, the sort of example that you’re bringing up was, an economist, said, I like this idea, and I know that we all have the shotgun idea of like, let’s just get as many people as possible. And we also have this silver bullet idea of let’s just target the charismatic influencer. So what she did was to say, I wanna see how effective these strategies really stack up against this sort of complex centrality idea of grabbing just a couple of neighbors in the proof of the network and getting ’em to start doing something.

So she partnered with the government of Malawi and divided the entire country into like 50. Village units, and then ran an experiment, a nationwide experiment where like 50 villages got the shotgun approach and 50 villages got the silver bullet. And then 50 villages were controlling 50 villages, got the,complex centrality seating when just these little cluster of neighbors.

And the results were stunning, like by far, like 300% increase in adopting of new farming practices just in the villages that use complex centrality. And it’s really the sort of neighbor to neighbor effect that you’re harnessing. And the irony is you’re starting off what seems like in, in the least advantaged position because you’re starting in like a small cluster in the periphery and it’s got much less exposure throughout the network.

But you’re not thinking about exposure. What you’re thinking about is adoption. And what you really want is the people who adopted to convince other people to adopt and convince other people to adopt. And when you shift your thinking from. Exposure and awareness to like really convincing people to adopt something. It changes the whole logic of how networks operate for social change,

Tom: what’s the reason that most people join, like major social movements, revolutions, other things where the cost is very high? Like, why, why did they do it?

Damon: because their friends did it.

Tom: that’s the

Damon: yeah. That, that is, that is the answer. Yeah. And this is, you know, I give these anecdotes about, you know, ’cause people, you see this research, the great story of, of Karl Diop, who’s this fantastic German sociologist. And right before the Ben Berlin wall fell, uh, people were coming out to these protests.

And I think it’s hard now to remember just how scary that was. But like, the guards at the Berlin Wall, the, you know, the. The Soviet troops, I mean, their guns were loaded and they were aimed at citizens and they were, as far as they’re concerned, you know, a foreign enemy. And the citizens were mobilizing by hundreds of thousands against this wall with the guns were aimed at their heads and it was really tense and very scary.

And, Carl Dieter opt is like, why are people showing up? And the longer this went on, the more people who showed up, it was like, this gets more dangerous day after day. And more people are showing up. It just seems the logic is like hard to understand. And to a person it was like, because their friends were coming, because their friends were coming.

And this is how just a small cluster can grow. And interestingly, the best study ever done this is Doug Mc Madams work on, the growth of Civil rights movement. a lot of the intuitions, because it grew nationwide were that, oh, it must have been these weak ties. It turns out the entire growth of these sort of very, powerful movements in which as we know, people suffered, physical abuse and some people were murdered for participating in these marches. that participation was mobilized through strong network ties. Friends of friends of friends. That’s why people came to these things. and so yeah, it’s, it’s interesting to think of something at such a large scale being governed by something so intimate, but that is the power of social networks for sure.

Tom: maybe we’re not all that different from teenagers, whether regardless of age of if my friends are doing it, I’m gonna do it. It’s a

Damon: Yeah. Well, I think that, it does, it’s not just sociology, physics too, everyone’s looking for the counterintuitive thing, right? Because the stuff that’s intuitive is like well understood by our existing science. So if you’re gonna try to push the boundaries of knowledge, like look for the stuff that doesn’t fit a pattern,a really interesting case was Black Lives Matter, where, you know, originally, I think in nine, in 2014, this is just prior to Ferguson, there were the original like Black Lives Matter protests right around that time, and there was a national poll. And the vast majority of US citizens, this is like in the like eighties, high seventies, eighties percent, said that the protests were not justified and there was not a problem with police violence in black neighborhoods. This was just some bad apples complaining, right? And so that’s a pretty strong sort of national pushback on this, what seemed to be kind of urgent political movement, um, and it didn’t really have much traction nationally.

And then after Ferguson, what happens is that, and I describe it in detail in the book, but what happens is essentially a realignment of networks on Twitter that connects communities who previously weren’t connected. So like black youth, but also. White liberal activists and then just pure activist groups like Anonymous, but also celebrities and also interestingly, even conservative commentators, all start to sort of, uh, form these sort of interacting networks where they’re taking each other seriously. And that gives legitimacy to the issue, but also more importantly, helps everyone kind of develop a common language of like, what are we talking about here? And then after Ferguson and the network start to rearrange, and over the course of the next couple years, it becomes a bigger and bigger thing.

And then in 2020, after George Floyd the same. Poll was done. and 78% of Americans, Democrats and Republicans said that there was a problem of police violence in black neighborhoods and that the protests were justified. And I mean, that, that’s a stunning shift in like popular opinion and popular understanding across all these different, social sectors.

and it’s just in six years and that’s just really from a realignment of networks. And so, yeah, it’s not just that we’re more prone to social behavior like teenagers are. It’s that the unification across our, all of our imagined social divisions can be really powerful just by realigning the networks of who’s talking to whom.

Yeah.

Tom: Yeah. as you were speaking, I was kind of imagining a role for social media in these, profound social movements where we were previously talking about how important the, sort of, at the local level, what are your neighbors doing, what are your friends doing? And, and those tight connections.

But then maybe a role for, the internet and social media is connecting clusters to other clusters. So different groups of very tightly knit people can learn of each other’s existence and activities through the internet is that the role where you see, our sort of modern technologies playing a role

Damon: right.

the connection between sort of the offline, the on, on, the online I think is, is best represented in the, the Twitter story, it was very much like, even though obviously it’s internet technology, it was really like a local geographic tech. Like it’s spread block by block in San Francisco. It was like neighbor to neighbor to neighbor. Like a good old fashioned social movement, which is, you know, ironic in 2006, tech bubble. And so, the sort of striking thing is that they’re the sort of friends of, friends of friends are using it to coordinate on things like there was a local earthquake and so people, they, to coordinate quickly and find a way of sort of talking about topical things and Twitter became instantly useful ’cause everyone could like talk about this thing and like say over here we’re getting aftershocks. Okay, over here, nothing’s okay.

And so they were sort of really using it in very real time to understand the situation. And then it became big again when that type of thing was happening nationally, which was during the election. And people need to coordinate really quickly.

But interestingly, the way that Twitter networks operated was that, a lot of people from the Bay Area went to school in like New England. And they were, although they were long distance, they were clustered wide bridges, they were strong ties. And so they had the same network architecture as a geographic neighborhood. But it was just, you know, in the virtual space. And so you had the same kind of reinforcing cluster, sending this sort of, Hey, use Twitter over to Cambridge. And the most interesting thing about this story is when it arrived to Cambridge and people started using it, it once again started spreading spatially.

So it kind like spread out from neighborhood to neighborhood, from Cambridge, from there to Newton to the outer suburbs of Boston, and then jump from there to Seattle.

And so you have like certainly something that transcends geographic space, but it’s still operating along the principles of these sort of clustered networks, which is what makes geographic space so effective. and I think that’s certainly the way in which the digital space amplifies the same kind of diffusion logic we’ve had historically.

Tom: Yeah. I wanna ask you one last question today, and this is for our listeners that have a, there’s a social issue or idea that they’re very passionate about and they just like some practical advice of. Knowing what you’ve, articulated the importance of working on the margins and not with these kind of central influencers, where’s a good place for them to start?

Damon: Yeah, so there’s two parts to this. One is like when you’re working with, you know, um, a company or organization that actually has the capacity to like look at network data, then we were able to, for example, look at the spread of microfinance in Indian villages.

then there are institutions set up that look at the networks, Indian villages and it becomes very, very easy, almost trivial to use this sort of mathematics of complex centrality and say it’s actually these three households. If you just get these three households, you’ll get widespread adoption of microfinance and like that works, in the situation where you aren’t. You know, privy to a lot of network data. Then now you’re pulling back to sort of, I think intuitions that are sort of the neighborhood intuitions, the community intuitions, the block by block intuitions.

And I would say, just by way of caveat, the thing not to do is what every viral playbook will tell you to do. Right? we have lessons from really high profile organizations who did this wrong. And I, I pull out two cases from Google. I, I think Google’s a great company, but they definitely have run afoul of social norms more than once probably because they kind of feel like technology will solve the solution for us. And that’s why they’re really prominent failures because it doesn’t, when it comes to social norms,

the one case was Google Plus, which less of us saw, but what they did was the kind of thing that we as individuals might be tempted to do, they basically pamphlet the universe with like, Hey, Google Plus is available, and if you have YouTube, guess what? You also have Google plus you have Gmail. Guess what you have? Like, it was like everyone already had it without even having it.

And then the idea was to say, well, now that it’s everywhere, obviously people will use it. But what they didn’t take into account is if it’s everywhere and everyone knows it’s everywhere. But no one’s using it. Then you’re basically manufacturing negative social proof for your technology because people become self-aware of the fact that everyone has it and no one uses it. And then they start inventing reasons. Actually coming up with a logic of like, well, there’s probably something wrong with the interface probably isn’t as good as Facebook and then winds up happening is you, you get this sort of word of mouth effect that’s the exact opposite of what you were trying to do, and the result is with. Google Plus was the entire product line is shut down. and so you would think like, wow, a worldwide company with access to billions of people and they couldn’t do it.

But a great example of like a grassroots way that it did work is the spread of farming technologies in the us. And corn sounds like the most boring topic in the world, but it turned, it turns out to be like one of the most, you don’t even have to be like a geeky scientist to like this story.

Potential music cue

It’s like one of the most interesting stories because, basically, you know, it was the Dust Bowl with the Midwest farmers were dying. The, the Great Depression was in full effect. It was like a very hard time. And at the same time, up in Iowa, the farm stocks were all inbred. So they like weren’t growing properly, they couldn’t be harvested. So like farms were going out of business.

And the US had actually anticipated this problem and the federal government had developed a new hybrid seed that could grow straight and that wouldn’t, Hunch over. So it’ll be very easy to, harvest the point here.

is that, they gave this technology like to everyone, they went out to Iowa and said, here, this will solve your problems, just start sowing this corn. And people didn’t, and they had from, again, this is sort of the similar to the Google story. They had like huge market saturation. I think they had like over 70% awareness. And this is back in the 1930s, like 70% of farmers in Iowa knew about this technology and they were supposed to use it, and adoption was at 1%.

And so all the companies gave up, the government gave up, they packed up and left. And so it’s like this story of like colossal failure of marketing and awareness.

Or maybe music cue starts here

and then just a couple of farmers in this sort of local community tried to sort of. Experiment with, part of their crop using it. And they talked to each other, did this work, how did that work? They started this little cluster, this little kind of farming collective, and they referred to it as a community laboratory.

one season it worked and they talked to each other. The next season it worked, and within five years, the entire state of Iowa was using this new corn. And within 10 years, the entire country, the United States was a hundred percent adopters of this corn technology. And so the beauty of this is like all the traditional marketing strategies failed so embarrassingly that it was largely considered a fiasco.

And then the local networks got involved and turned into larger success in like US marketing history. and so the, the sort of lesson is like, yeah, you can actually do this form little laboratories, little collectives, get people involved talking to each other and then grow it locally, neighborhood by neighborhood.

And believe it or not, that actually can have nationwide impact,

Tom: Yeah. To me it’s fascinating that this example I think is so good because it’s both the example of total failure and the example of total success. and it highlights the huge difference. I think one of the biggest takeaways for me from reading your book is there is a enormous difference between awareness and adoption.

And when you’re thinking, if you’ve got an idea, you could ask yourself, do I want to spread awareness of this thing? Do I want to spread adoption of this

Damon: Yep.

Tom: And depending on what you want, you need to take a very different approach.

Damon: Absolutely. It’s, it’s been a pleasure talking to you and I really appreciate your enthusiasm and your enthusiasm for the book.

It’s a pleasure to hear.

Tom: Yeah. And thanks for taking the time to talk to me today.

Damon: Absolutely.