EP 03 – Karen Nelson-Field, PhD – Founder and CEO of Amplified Intelligence – When a Pattern Generalizes, It’s Real

See the full transcript below:

Michael Waitze 0:02
Okay, we’re on. Hi, this is Michael Waitze, and welcome back to the Data Driven Podcast, sponsored by Xpresso.ai. Xspresso.ai is a lifecycle management platform for artificial intelligence and machine learning applications. It is built on an integrated set of frameworks and accelerators to help data scientists build cognitive solutions. Quickly and easily, If I could only pronounce that word it would be better. On today’s show, we are joined by Dr. Karen Nelson-Field, the founder and CEO of Amplified Intelligence, Karen, how are you doing today?

Dr. Karen Nelson-Field 0:35
Great. I probably can speak more clearly than that.

Michael Waitze 0:42
Thank you. I am…I’m tired. Actually, I woke up this morning at four o’clock, which is kind of a normal thing for me, How about you?

Dr. Karen Nelson-Field 0:50
So I set my alarm for 04:00 AM started my day at 04:30 AM. Welcome to our world people.

Michael Waitze 0:57
It’s this weird world of entrepreneurship. Right? I always feel like I’m planning today for what’s going to happen three or four days in advance, maybe even a week in advance if that makes sense.

Dr. Karen Nelson-Field 1:07
I just find is just not literally not enough hours in the day, you know, and I have always deadlines. And yeah, I’m not sure I’m a planner like you. I try to be but usually it’s every day, I just have to deal with one foot in front of the other.

Michael Waitze 1:21
Yeah, exactly. But how do you decide what to say “No” to?

Dr. Karen Nelson-Field 1:26
That’s an excellent question. So at the beginning of my accidental entrepreneurship business journey, I didn’t really say “No” to much, if I’m honest, because I wasn’t very clear on where we were headed. I knew what I was interested in. But I didn’t have a lot of “Nos”. And what that does is it gives you a bit of an understanding and all the different parts of the ecosystem that we’re playing in, which at the time was just research, and media research. But now, it’s different. So now we have a really clear path around where we want to be. It’s much easier for me to say, “Actually, no, here’s a different vendor for that. This is not our core, this is not the area we want to be in.” And I’m very clear about that.

Michael Waitze 2:18
Yeah, it’s really interesting. So I kind of did the same thing. When I first started this, this was maybe less accidental, I had a vision in my mind about what I want media to be, which will make this a really interesting conversation, I think. But I said yes to almost everything because I didn’t know what it was meant to look like. I didn’t know what the final shape was meant to look like. But now I think kind of like you, I am at a stage where now I know exactly what I’m doing. And now when someone comes to me and says “Hey, can you do this?” I just say, “I can’t do that, actually. But I know someone who can.”

Dr. Karen Nelson-Field 2:47
I love that you say now you know exactly what you’re doing. Because I’m not sure I think I know exactly what I’m doing. I know where I want to be. But I’m probably being hard on myself. But yeah, it’s a complete learning curve every single day, I feel pain in my head from the learning curve in my head.

Michael Waitze 3:06
So I said to you offline, “I think entrepreneurs are the greatest people in the world.” And I think your exact response was, “I think they’re all mad.” In a way. I don’t disagree with you, though.

Dr. Karen Nelson-Field 3:15
Oh, you know, I came from a tenured professor position and went, “Oh, no. That’s way too easy. I’ll just do something crazy. Like, you know, I have no clue on a day-to-day basis how I’m going to feed myself, I might as well do that.” So I but in all seriousness, you know, I even back then I knew, I won’t go as far as to say, I was born to be here to be solving a problem. But I knew that I had some expertise. And I knew that I could do something with that. And I kind of went, you know what, here we go. Let’s do it.

Michael Waitze 3:47
Can you talk a little bit about what that background is? How did you get to here? You said you were a professor, but you weren’t always? Yeah.

Dr. Karen Nelson-Field 3:53
So I’m actually not a career academic. I was a media girl when I was young. So I worked for News Corp, I worked at Diagio. I did all the, you know, the FMCG and all those types of things. And, you know, every Australian works for Rupert Murdoch at some point. But then I’d already done a few degrees. And I was, you know, I love media. I’ve always loved media, and more so than creative if I’m honest, from an advertising perspective. You know, here’s my actual story, I had a couple of babies had them really close together. So it meant that I really was home. I couldn’t go back to the executive. I had lots of staff at that point, 100 staff or something, and I couldn’t go back to the job that I had with very, very small infant children and was offered a Ph.D. scholarship. So I’ll run an Australian Ph.D. scholarship, and I thought, well, I could, I could do that while they’re sleeping, you know, as you do. So I did that. And I decided to look at a media topic. So I wanted to understand where the targeting worked, if I’m really honest, so and it was in the early days, sort of pre-social. So just before you know the likes of Facebook and early, early YouTube came on. And so I was looking at whether retargeting was an efficient way to drive return on investment. So it was a segmentation Ph.D. And yeah, I went alright, “I’ll do that.” And, lo and behold, I was actually pretty good at it, I was really passionate about it. And the key thing for me was it led me to my postdoc, and my postdoc, I, I, this is when, you know, the likes of Facebook just started coming in, and I went, and they were selling this dream, this dream that you know, if someone likes it, they will become loyal, and they will, you know, buy more from you. And it just made me question, you know, I was trained at Ehrenberg-Bass, which you know, is very much about, you know, penetration over loyalty, and, you know, advertising is not persuasive, and all this sort of stuff. And I went, Oh, I wonder if I could, you know, test the laws of brand growth, and how that might relate to new media. And over the course of my three-year postdoc, I did that. And I had a look at, you know, what engagement actually means, and, you know, sort of tried to disentangle some of the fluff, that was digital metrics at that time, it’s sort of skyrocketed because the research was really solid. We found some sort of controversial findings, you know, I mean, I made my way to New York and started presenting that kind of work, and yeah here I am today. So it kind of catapulted me as a media researcher, because at the time, you know, even the likes of Facebook, as you might remember when they went to IPO, really couldn’t clarify their commercial position. So it was that’s kind of how I got started.

Michael Waitze 6:46
Yeah, I mean, I remember, obviously, I was not in your space, I don’t understand what media trading is, I don’t understand the analytics around it. I’d love to know what you learned, not just in your Ph.D., but more. You know, in your postdoc, you said, you found out some really interesting things that were slightly controversial. I’d love to know what those things are. But I do remember when Facebook IPOed, and I was wondering, is that really going to be that sticky kind of thing? Do you know what I mean? Like, is that really gonna work?

Dr. Karen Nelson-Field 7:12
Yeah, that was an interesting time for me, because I did actually even in looking back, I feel well, “Did I really say that?” So I, I published some work during the quiet period of the IPO, you know, how they just before actually rings, the bell. And my findings were so hugely controversial that it was noted as having a bit of an impact on their less than stellar price. So I feel a bit guilty, but they’ve bounced back a little bit. But, you know, some of the findings in the early days, and it sort of still holds that, that at the end of the day, reach is not free. And just building a bunch of likes or followers or, however, you want to define communities, doesn’t mean that it’ll nudge people to buy more. So there were, there were a whole lot of findings around things like, you know, in an average week, so at the time, it was, you know, the Unilever’s of this world, and others that were spending a small fortune, trying to acquire reach, sorry, to acquire likes. And we kind of looked at the top 200, I think from memory over a course of two years, and found that in an average week, less than 1% of the fan base, even bothered to go back to the page. So it was a time when Facebook was really transparent with their metrics, right. And we were able to use the metrics that they published, then sort of disentangling on sharing to likes to engagement and things like that. And I don’t think they had really thought through it, that someone like me would sort of sit there and try and work it out. So those were the sorts of findings and then, you know, following on from there, you know, a couple of years after, you know, the whole wave of free reach. So the concept of viral kind of became a thing and the research that I did, I wrote a book on this, but the research idea at the time was that you know, and this is kind of YouTube’s era, that, you know, just because you build something that’s interesting doesn’t mean that it will diffuse, like a pandemic. And it actually is the other way. So what we kind of found was that you actually have to pay, you have to, you have to seed some, you have to save the content upfront for the long tail to kind of, you know, give you more reach, if you like. So it’s kind of the opposite of what an average person thinks of viral most people because the word viral, I mean, it’s a horrible analogy now, but

Michael Waitze 9:46
I’ve often wondered, and I have not read your research, but now I’m inclined to do so actually, I want to get this book because I want to understand this better because I operate in that space. And I’m often told you need a page that has 100,000 likes or 200,000 likes, but I never thought that that drove engagement or stickiness, which is really important. And to be fair, if I understand what you’re saying, and I want to ask you a question on a specific thing that happened on YouTube, so hopefully you’ll remember this, I’m sure you will. But that virality itself isn’t actually a thing. Things can be purposely spread around, and that they can get paid for. But the things don’t just spontaneously combust into virality. Do I understand that correctly?

Dr. Karen Nelson-Field 10:25
You are absolutely spot on. And it’s very, very, very, very, very rare that it is that case, but even then, the basis of virality comes from other platforms or other media celebrities that actually talk about it. So. So for example, if Justin Bieber got a hold of your video, and he plays it, or he tweets about it, or whatever, his followers, you know, are into the millions, hundreds of millions. So, theoretically, it’s still diffusing negatively, which means that you need more eyeballs, and there are fewer that share it. So you’re absolutely spot on. And that’s kind of what the research showed. So the concept of virus, which again, it’s horrible timing, is that it’s one person and it spreads to many, which is naturally what it is in a pandemic, and, you know, marketers as they do steal from other sectors, and they’ve stolen this concept. But if you actually have a look at how content moves, it works the opposite. So, you know, 10, people will view it, eight people will share, right, you know, five people will view it three people will share. So there’s like this reverse, there’s a negative distribution. So it’s the opposite. You’re 100%, right.

Michael Waitze 11:49
So when I think about virality, I think about Gangnam Style…I do because this had over a billion or a billion and a half views. But if you listen to Psy interview, he said there was a massive strategy, both a paid strategy and an unpaid strategy around making it go viral. I’m wondering if you did any work on that.

Dr. Karen Nelson-Field 12:11
Yeah, that was in my book. So that’s a classic example. And we knew that. So we actually talked about that. So there was this paid strategy that sat behind it. And then the other one that people always sort of talked to me about is the Ice Bucket Challenge or the ALS. So that went insane for a little while. And I’ve been interviewed many times about that one. And it’s a bit similar in that it wasn’t a paid strategy, like Psy. But because it had, again, after spin, you know, it’s been 10 years since we talked about it. But I just remember, it was actually a charity that was published years before, but it didn’t get any traction. And then what happened is, I think from memory, there was a golfer, like a fairly famous golfer that actually had the disease. And then Oprah picked it up and talked about it. And then she got her friends involved, which actually, I think was Justin Bieber, and people like that. So you know, you get, you get five celebrities who have 100 million, you know, followers, so to speak, then by default, that is the pay distribution. But if you look within that content, it still would have diffused to nothing, which is exactly what happened.

Michael Waitze 13:22
It always tails off, right?

Dr. Karen Nelson-Field 13:24
Yeah. So that’s, so that’s kind of the next phase in my academic research. And then the third phase was sort of when, you know, going back to media proper, when the MRC sort of came in and made some, you know, regulations around what is deemed a saleable piece of inventory. So what you know, the two seconds of time and 50 cent pixels, and you know, that I was right in the thick of it at that time, and really felt that, you know, in fairness to the MRC, I get that they’re kind of between a rock and a hard place. But I really felt…

Michael Waitze 14:01
The MRC?

Dr. Karen Nelson-Field 14:03
Media Ratings Council. So they came in as US-based. And they came in and said, you know, trying to regulate a very unregulated thing called the internet, in terms of how to charge ads, they said, you really only technically should be charging, if your ad is 50% pixels on screen, and also for a continuous for two seconds of minimum two seconds of time. So it brought some sort of regulation to this wild west, that was, you know, money being thrown out of the door and for nothing. So, you know, for advertisers, that meant there was some sort of ability to say, “Well, at least some people might see it.” But for publishers, it was a bit of a kick in the teeth, but at the same time, you know, it wasn’t 100% pixels. So So my point is that at the time I challenged that because I went well, you know, if an ad’s 50% on screen versus 100% on screen, surely the one that’s 100% on screen will get more engagement or whatever the measure that is an ROI type measure, which led me to, “Okay, well, what’s the top of the tree measure?” Well, it has to be human attention. And it has to be a verified opportunity to see if you like, and that’s kind of the rest is history. So from there, I started to wonder if, I was actually employed on a big contract, and I can say it now because it’s out of embargo by Unilever, and they wanted to, they were challenging the MRC standards. And they were like, well, we don’t even know if YouTube, you know, delivers more ROI than Facebook, and Twitter, and Weibo, and they asked me to start to think about how I might measure cross-platform effectiveness. And that’s what led me to well, how the hell am I going to do that? Okay, I need a measure that someone isn’t sort of stating like, it’s not self-proclaimed like a typical academic, I need, I need something that can go into because it was three countries, I need something that’s scalable, oh my god, I might need to think about how I could incorporate technology. And the best thing I could think of was, okay, some of the best studies are when you film people in their home and sort of watch them during the day, you don’t get them to say what they did, but you watch them through, you know, camera, could I possibly integrate some sort of computer vision at scale, and that’s when I went, “Okay, I need to do this for a living and not be an academic.”

Michael Waitze 16:37
That is an amazing story. And I remember, although the details are still fuzzy to me, and this must have been like six or seven years ago, although I think you’ll agree that sometimes the years just kind of blur together, it’s hard for me to remember like, even what day it is sometimes. But I remember a bunch of big advertisers Procter and Gamble, Unilever, some of your biggest advertisers globally, even JP Morgan, started saying, Okay, stop, we’re gonna stop these DSPs we’re gonna stop the RTB because we can’t measure whether they’re actually being effective. And there’s so much fraud in that ecosystem, that we don’t know what we’re paying for anymore. And they actually pulled it and they found it something like, I think it was JP Morgan, who said, like, they were paying 400,000 different websites, all this money and not getting any ROI on it. Do I remember that at all correctly? Yeah,

Dr. Karen Nelson-Field 17:25
I mean, that’s ongoing. So that’s not new. That’s a continuous thing that happens, you know, every six months, some big advertiser says enough. I mean, there’s so many sides to the story. And we’re just one part of it. So we don’t play in the fraud space. We play in the, you know, if an ad gets served does someone even look space. So we play in, putting aside the bots and fraud, if there’s a human, assuming there’s a human, are they even looking? And does this vary across platforms? And is there a way we can predict that and you know, why some are looking on one platform and not another? And over the course of the last sort of four and a half years, what we’ve worked out and, you know, what our businesses kind of jumped forward with is that there are actually predictive factors. So we know that there are factors of or functional factors of the platform that actually deliver or foster inattention versus attention. And we can pretty much predict it now. So fast forward four and a half years, our technology is quite seamless, and we’ve dropped it into six countries so far and collect attention data across multiple platforms. And the patterns are there, which is great, because when a pattern generalizes it’s real, right?

Dr. Karen Nelson-Field 18:47
So yeah, we pretty much can predict which format so you know, with all the new, all the new formats that are coming out from the different socials, we can we can pretty much hypothesize which ones will get more attention or which ones don’t. And we’re usually pretty, right, because it’s pretty consistent.

Michael Waitze 19:04
Can you define ‘Attention’ for people?

Dr. Karen Nelson-Field 19:08
Okay, so what I like to say is, “I can’t read your mind.” So attention in the true sense of the word is when someone actually stops focusing on the outside community and literally focuses on the stimuli or whatever it is in front of them. But, let’s be honest, what we’re doing is not understanding cognitive processing. And I think that’s a really important distinction. So as a vendor of attention, what I’m doing is I’m sort of trying to understand if someone is looking at something, whether they’re half-drunk, or whether they’re, you know, thinking about their morning, I can’t tell you that, but you can’t have a currency measurement, using, you know, MRIs and things like that because it’s just not scalable. So we made a decision, what’s the next best thing we know that someone has to see an ad or has to see something for them to be focused on it. So that’s what we chose to do. So for us, we collect data that essentially is its facial footage. So if you were using Facebook right now, essentially be filming you through the device camera. If you were watching TV right now, I’d be filming you through a provided camera. And that then that footage comes back to where internal machine learning stacks. And it transposes that to whether you’re looking straight at it, whether you’re looking around it, or whether you’re not looking at it at all. Now, like I said, you might, because I can see you’re looking straight at me, but you still might actually not be listening. You are a man, after all. So, I know I’m sorry, I didn’t mean to say that.

Michael Waitze 20:52
Come on! I think it’s hilarious…keep going.

Dr. Karen Nelson-Field 20:54
But my point is, you know, that’s a far cry from the poor proxies that are out there at the moment. So some of the measures of attention that are out there is, you know, things like time-in-view, you know, scroll speed, things like that. But we can see in our own data, because we collect those data points as well, that we can see that action looking at an ad compared to device variables, like time-in-view, are very, very different. So you can have an ad in view but be talking to your partner to the left, but the ads right in front of you so so yeah. So that’s what we consider attention.

Michael Waitze 21:31
So if you can measure whether I’m looking at something right? So you said you want to measure, I want to make sure I get the terminology right here, If I see something, can you measure if I hear something as well? And does it matter if I see something and hear something at the same time? And the reason why I ask is because even though it’s a tactic, you can tell in a way if someone’s listening to you if they can mirror back the things you’re saying to them? Does that make sense?

Dr. Karen Nelson-Field 21:55
It does. And we have evolved our technology overtime to do that. So just bear in mind, I’ll say this upfront, we’re GDPR compliant, and we don’t film you and listen to you unless you ask, you’re happy for us to. The technology is designed to understand whether the sound is on or off in that platform for the ad format. But it’s also designed for volume. And we also have just recently changed it so that we can tell if someone’s wearing EarPods or is connected via some sort of headphones or some earphone jack. So it does make a difference. So sound is what we call an ‘attention trigger’. And it definitely sort of helps the return on investment in terms of, you know, the uplift or whatever the measures are at the other end that you want to connect it to.

Michael Waitze 22:48
So you said you learned a lot about which platforms or which styles of content delivery worked, and which ones don’t? You said you’re operating in six countries right now? Yep. I have so many questions. Are those six countries similar? In other words, is it just like a bunch of Nordic countries or a bunch of you know what I mean? Like I said, Australia, New Zealand, the US, England, you see what I’m doing? Right? All very similar types of people all speaking the same language? Or is it like Indonesia, Singapore, Vietnam, China? Or where the people that are just so different? And their lifestyles are different? Or does it work anywhere?

Dr. Karen Nelson-Field 23:21
So the technology that we have at the moment is iOS based. And we have done that for a reason. So if you were to be a part of a panel, for example, the accuracy to which our gaze works, it works, because we’ve trained 80 iOS devices against the mathematics of the camera, to the endpoint, for example. So anyone who tells you that they’ve got a really accurate solution on mobile is largely lying unless they’ve done it for many, many years because it’s a lot of training data. So we’ve done it on iOS for the minute, but we are literally in the throes of training it. So we’ve collected over four years of training data, we’re literally training Android devices as we speak. So the short answer is they are similar countries. So it’s Germany, Austria, Switzerland, England, or the UK, US and Australia. So I would agree that they are sort of similar. Within that though, the ethnicity of the groups is quite large. And if I’m really honest, we do you see some differences with different ethnic groups within the attention and I’m actually planning to publish something off the back of that soon. The next phase for us all to be going to go to Asia, but I don’t see it so different that I think what will happen is they’ll either pay slightly less or slightly more attention, but the mediating variables so the stuff that happens on the platforms will still be constant. So I don’t predict that to change. I think there’ll be overall slightly less or slightly more attention, but not so different that it’s the opposite.

Michael Waitze 25:14
Yeah, I mean, it’s the nuances that really and the subtleties that interest me, right? I love those small differences. For somebody who’s been living out of his home country or birth country for now, more than 30 years, I just find those little things really interesting.

Dr. Karen Nelson-Field 25:28
Aw, look…that’s what helps planning to, you know, media planning. So, we know that different types of different times of the day, attention changes, we know that different demographics do make a bit of a difference. But what I will say is that marketers do have the wrong notion of how much attention people pay to advertising. So if you think these differences, you know, it’s the difference between five seconds and 20 seconds, you’re wrong, it’s probably the difference between five seconds and six seconds. And you know, but in the world of advertising, if you get an extra second, it adds value, because we know that the amount of seconds more or seconds leads to memory. So you know, the longer an ad is in front of your face, the more likely it is for you to remember it. The longer, right. So you know, for me, an extra second is still very valuable.

Michael Waitze 26:22
Well it has to. I mean, it’s simple math tells you that one second added on to five seconds is a 20% increase, and 20% of anything is huge. Right? Yeah. You don’t have to you have to be a mathematician to figure that out. But doing a little bit of math wouldn’t hurt. What’s the downside of attention? What’s the downside of trading on it?

Dr. Karen Nelson-Field 26:39
So the downside of trading on it is that our systems aren’t quite ready for it to be 100% a currency at this point. So how are we, so just by way of background, so when I went into this business, as a researcher, I sort of worked out that I needed to build technology for me to be able to get the data that I needed, right. And that’s done and dusted. But about a year and a half ago, I made a decision that I wanted to be a part of a change, and the change is needed, because not all reach is equal. And there’s no transparency that sits behind that. That’s true and advertisers are in revolt over it. And you know, the whole world is going, you know, reach metrics, rubbish. And, you know, it’s all broken. And we went, well, we’re sitting on this data, that’s pretty valuable. And it’s telling us that this platform and that platform are different because of these reasons. And we made a decision, we should actually push for, to trade against the data that we use. However, given my academic background, I didn’t want to rush into it being the Holy Grail. And that’s the only measure you should use forever, I’m in. So my approach is it needs to be a layer. So how we approach it is you can use this data as a weighting layer against your planning and your buying. Because at the moment reach and frequency is the trading currency. And that’s as pure, as simple as it is. And it will probably be like that, quite frankly, for a very long time. So attention is, attention is, I know it’s a weird word, but a relative value metric. So it sort of says, if 1000 eyeballs on this platform is not the same as 1000 eyeballs on this platform, if we use attention, that will give us an index. And that’s, and that’s how we play it. So it’s a, it’s a metric that’s designed to fit within systems to just kind of be a relative value proposition.

Michael Waitze 28:44
So for somebody who used to traded stocks and bonds in an automated way, right, one of the things we did was used to go back and take 10, 20, 30 years of data and backtest the things we thought were going to happen against what had already happened. Right to try to find out, barring you know, the economic or the sort of profitability of any particular company, just look at what the trading told you about it. Can you do things like that with attention as using attention as a weight, right? You said it’s not the only metric you look at. But you mentioned sort of reach and frequency, but if you weight it with attention, and then go back? And look, is it possible to do that? To see if it even more verifies what you already think?

Dr. Karen Nelson-Field 29:21
Yep. And we are doing some of that. So good idea to go backward, actually, what we are kind of using it for his attention-adjusted metrics. So things like budgeting. So you know, share-of-voice, share-of-market is a big way that, you know, advertisers make some decisions around what their budgets should be next year. So my call out is that you know, anything that uses ‘Reach’ can have an attention-adjustment metric applied, and one of that that we’re working on at the moment is budgeting because for example, if you, if you look at what your competitors spend, let’s just say it’s a million bucks, but they spend it on platform ‘A’ and your million dollars is spent, spent on platform ‘B’, if platform ‘B’ is poorer performing your million dollars doesn’t get you the same return. And so your market share will likely decline or your underspending. So those are the sorts of metrics that can be used.

Michael Waitze 30:28
Have you seen situations where you take some just existing data as you said, reach and frequency, you take ‘Reach’ and frequency data, and that data tells you very obviously, you must be on this platform, you must budget this amount of money again, with all the other things being equal, right? And then when you weight it by attention, do you see like really, kind of well-known places or well-known strategies just go, that’s not working? You know what I mean? where the weighting just goes like this (Two hands moving vertically away from each other)…and surprises your advertisers?

Dr. Karen Nelson-Field 30:57
Yeah, totally, and 100%. And so we, so without telling you too much. We, only in late November, built out a planning tool, a beta trial of a planning tool, and we’ve got a long way to go. So the data was delivered. It’s fairly simple. And we ended up that ended up in 21. countries, Michael, but well, one of our customers who bought a subscription to that data has come back and said, “Oh, my God, I have to show you some of what we’ve done and how we’ve adjusted our planning.” And we, we want to write a paper on it. So there is something coming out on that. But I mean, we see that all the time. And you know, it’s the sad part for me is the constant proving out that someone who that, that if you do see an ad versus if you don’t see an ad, it has an impact. That’s the thing that stresses me. To me, it just seems bleeding obvious. But you know, the proof points we’re going through a major change in our measurement. So I think even a few years back, it was predicted that this cycle of measurement is changing. And measurement, version 5.0 is coming. And no one could really pick what that might look like. But now, you know, the attention economy, particularly in the last year has been sort of in hyperdrive, everyone’s kind of coming out and going, Oh, this is what it is. But I think, you know, I think getting it to a point where it becomes a stand-alone is coming. But we’ve got some work to do. So for example, I don’t personally like the concept of an attention CPM, I think CPM is, is decided, essentially by the average by the publisher. And when I was young CPM was a relative like it was relative to performance was relative, if you want more reach, pay more money, pretty simple, right? And what we see in our data is that that CPM is all over the place. So it doesn’t relate at all.

Michael Waitze 32:59
Anyway, go ahead.

Dr. Karen Nelson-Field 33:00
So I’m feeling like we’re too early for an attention CPM. And I think that’s a little bit like it’s not very, it’s not thinking about the future, what to me that says that we’re trying to trade on money and pushing the ecosystem down. Whereas I’m still thinking, actually, we should pay more if it’s high attention.

Dr. Karen Nelson-Field 33:23
So so there’s a little bit of cross purposes in the industry at the moment about bringing an attention CPM in.

Michael Waitze 33:29
So there’s a two-sided marketplace here. And again, tell me where I get the definitions wrong. And I’m gonna make it very simple because it’s just easier for people to understand, there’s an advertiser over here, and a place to advertise call it a platform call, whatever you want over here, these advertisers use, I guess, they’re using amplified intelligence to try to study that data and figure out where they should be doing it, weighting the stuff with the attention that you’re talking about. But the other side of that is that the media companies can also understand how to better build a platform that gets attention to what I mean. So if there are three outlets over here, where they can do this, sorry, and there were two advertisers or one advertiser in the world, they have to choose between these three platforms. Is there a technological arms race that’s going on between the platforms to create the most attention? Is that possible to learn as well and change?

Dr. Karen Nelson-Field 34:16
So you couldn’t be more spot on. And we’re right in the thick of both sides. So in fairness, there are some platforms that have and I won’t mention them, who recognize that attention is a metric that’s not going away. So they’re going okay, we need to think about how to build formats within our platforms that we can say, you know, here’s a format that’s lower tension, get that that’s just part of the deal. But here’s part of it. Here’s a format that we charge more for. That is still part of our, you know, our sisterhood, but it’s, it’s more premium, and it gets more attention. So, to be honest, that is happening. So we were getting engaged often by platforms for that very reason. And my job is not to be critical of a platform over another. It was a bit more like that in the early days. But it was more me going, you know, check this out, look at the vast difference between platform ‘A’ and platform ‘D’. But now there is, I don’t know about an arms race. But you know, most of the majors are going, “Actually, it’s important.” And it’s important for our ecosystem, I think that’s pretty important.

Michael Waitze 35:30
Can I like guess that something like and again, this is early, early days. But at the beginning, sort of this, these new platforms, Huffington Post was a place where people went, and they had a ton of attention, it seems to me, and then at some point, it just vaporized. I can’t remember who bought it, maybe it was, I can’t remember, I just can’t remember. But then there was BuzzFeed, which again, exploded because it seemed to be getting a lot of attention, but then they kind of just trailed off as well. Are they missing, and not these platforms particular, but are there some platforms out there that are missing this idea of the attention economy and just aren’t paying attention to the type of research and the type of services that you’re selling?

Dr. Karen Nelson-Field 36:08
I think the platforms you’re referring to are platforms that we would call clickbait. Yeah, not your attention. So it’s so my point is the measurement of that kind of attention is flawed, because like I said, human attention and time-in-view is very different. So on average, just on average, you know, an ad time-in-view, that you think someone’s paying 10 seconds, potentially for you lucky if you get two, in terms of real human attention. So I think those types of platforms are really not suited to return on investment proper, because the measurements that they use are proxies and poor proxies that. But you know, I think I think the I think that the industry as a whole is kind of waking up to that. And I think there is some pushback, well and truly, on the ethical side of that kind of attention, where, you know, we’re just being bombarded with rubbish content, and then we switch out from ads anyway. And then that means that we don’t, you know, there’s less reach and you know, it’s completely ruining this is, so we call that, so we’re part of what I’m calling the positive attention economy, which is about, you know, pushing CPMs up, not pushing them down. And offering, you know, humans the choice if they want to subscribe, and they want an ad-free, they’d pay more for the content. I mean, there’s Sorin Patilinet in Mars Global is a fantastic advocate for the value of human attention, but he does it from a creative perspective. So his whole angle is, you know, if you build it, your customers will be happy. And that’s a good thing from ours, you know, we want our customers to be happy. So he, he’s all about, you know, measuring how attention-getting his creative is, but it’s really more about, are we being good to our customers and giving them good content? Or are we just giving them crap content? So, he’s part of that as well.

Michael Waitze 38:13
So this is a little bit of a different angle. But I want to give you two examples. I used to think and I think actually this often that, you know, these guys and gals that, you know, sail around the world alone, or like take a rowboat from one side of the Atlantic to the other, that when they get back on dry land, it’s hard for them to interact with regular people, because regular people haven’t been through that struggle. And I also say that like my architect who built my house in Tokyo, that it’s not his job, right? It’s just his life, and that whenever he sees an open piece of land or an open space, he thinks, what can I put in there that would add beauty to this environment? And I wonder, with you, you’re so deep in this data. And you’re so deep in your understanding of media, can you look at the media without thinking about all the data behind it? And get away because your brain just processes it, you know what I mean?

Dr. Karen Nelson-Field 39:05
Well, it’s so funny. And listeners, this was not pre-rehearsed. What’s a cracker about that is my husband’s a yachtsman and he’s an architect so I just am listening to describe my husband’s you know, Virgo, you know, kind of detail brain that can’t rest because there’s a vacant block of land and what can you do but then he wants to start around the world. So it’s a bit funny, but on the flip side, yeah, I, I do I can’t look at it the same and to me, I feel I sometimes I feel like an imposter. I feel like this is actually really basic stuff. If you build a platform that sort of encourages actually people to watch it, then it’s good for advertising.

Michael Waitze 39:48
That seems to make sense without any necessary research, but yeah.

Dr. Karen Nelson-Field 40:00
So sometimes I feel like you know, you don’t need four degrees for that. But I, I just go, it’s actually pretty basic really.

Dr. Karen Nelson-Field 40:08
There are times when I go, “Am I just the world’s worst overthinker living with an architectural yachtsman?”

Michael Waitze 40:16
No, because it’s all backed up with data. That’s the whole point, right is that you’re backing it all up with data. And that’s what people want. So when your customers or even their platforms look at it, they’re like, Wait a second, this is all backed up with data, which is why I thought this idea of using attention as a weight was really… it’s a coefficient, right?

Dr. Karen Nelson-Field 40:34
Yes, exactly. Yeah, yeah. And what I love about that, again, is because my training was Ehrenberg-Bass, you know, I don’t know if you are familiar with that Institute. But the concept of Ehrenberg-Bass Institute is that ‘generalizability is the building blocks for meaningful results’. So most academics can find a significant P-Value in any single study, right? And you can make some you can “Oh, my God, look what I found. It’s significant. Let’s do a paper.” But when you see patterns that repeat, over and over, even if the data isn’t perfect, but the patterns still hold, yeah, across different boundary conditions. That’s when you know, you’re understanding. And that’s why I’m super confident because I’m always asked, you know, sample sizes, I mean, we have 1000s. So it’s not, you know, small, but do I do four statistical regression coefficients on every single piece of data that we have? No, because you can literally see the patterns in front of you that…this platform has this many pixels and has this much coverage. And, scroll speeds this, and that’s what the attention is. So it’s predictable. So that’s what I love about what we do, because this big data, when you actually step back from it, it’s actually really simple.

Michael Waitze 41:59
Apple announced a couple of days ago, the big changes to privacy and trackability. In iOS 14.5. What is the impact of that? Does that have an impact on the type of stuff that you do and you don’t study?

Dr. Karen Nelson-Field 42:11
So we are GDPR compliant, we have a triple opt-in process. So. So when you as a panel member, make a decision for us to track you. It’s not through cookies, it’s through your device. And the app becomes redundant as soon as you close it down. But you opt-in? So no, it doesn’t actually affect us at all.

Michael Waitze 42:35
Right. But does it affect the other people participating in that ecosystem? In other words, does it matter that they’re doing this or not really?

Dr. Karen Nelson-Field 42:44
So from a panel perspective?

Michael Waitze 42:45
No, not from a panel perspective, from an advertiser perspective?

Dr. Karen Nelson-Field 42:48
Oh, there’s huge implications on all those types of technologies changing for advertisers in terms of tracking and targeting, and, you know, API integrations and all that sort of stuff. Yeah. But from our side, that sort of thing doesn’t really have any impact. In fact, if anything, it’s, it’s not us, because, you know, the cookies becoming extinct, means that, people on an individual level are harder to track. So, the world is looking for the measures that can be layered, right. Yeah. And that’s, that’s kind of the game we’re in. So yeah, we’re, we’re at a really interesting time as a business. The category is just beginning. And we’ve been at with it, you know, I say myself, I feel like we’ve written books on this. And I feel like we’ve had a role to play in pushing this category. But, you know, it’s at the perfect intersection where advertisers are distressed about what’s happening, like you said before, about fraud and, and ridiculous metrics that mean nothing. And then on top of that, you’ve got tracking abilities changing. So, yeah, so, so really, so ask me again in a year.

Dr. Karen Nelson-Field 44:02
Let’s go back and go through it.

Michael Waitze 44:04
So I want to ask you one more thing and then I am going to let you go. I know time is at a premium for you as well. When you’re sitting here thinking like in a quiet moment, which if you ever have one, I’d be amazed, what is the sort of medium and long term vision for Amplified Intelligence?

Dr. Karen Nelson-Field 44:20
I laugh because maybe I’ll need all of your viewers, listeners, to sign NDAs…But no, look so I genuinely think I can play a role in this broken ecosystem. I’m getting old, Michael, I can’t see me around in 20 years being a big player. I just think I’m at a moment in time where the work that we’ve done and the rigor we’ve done, the rigor we’ve put behind it, tells a story tells a narrative that pushes for change. We are doing that. Where the business will play a role is in both the planning and the buying side. So you know, using the data we have, because of the depth of the technology, we can drop into most countries and soon to be Asia, people will be able to use this data and make some change. And that’s kind of what we started to do with this MVP in late November or so. So again, ask me in 12 months, but I see we will play a small role in transitioning our measurement industry into something that’s a little bit more meaningful. That’s what I see us doing.

Michael Waitze 45:32
Okay. I don’t know what else to say. That was awesome. I want to thank you, Dr. Karen Nelson-Field, the founder and CEO of Amplified Intelligence, that was insane. Thank you.

Dr. Karen Nelson-Field 45:42
Thank you.