In this week’s In-Ear Insights, Katie and Chris address pressing questions about the ethics of marketing analytics, data collection, and consumers’ right to privacy. What should marketers be collecting? What shouldn’t they? What are the implications of unused, personally identifiable information laying around in marketing analytics, marketing automation, and CRM systems? Tune in now to learn how to mitigate your risks.
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What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for listening to the episode.
In today’s in In-Ear Insights, we are talking ethics and marketing data, I was having a conversation with a friend on LinkedIn about the different ways that you can use data with artificial intelligence and and AI and machine learning and all that wonderful stuff. And one of my friends said, there are still ethical questions about all this stuff. Namely, should marketers even have all this data? How ethical is it to use it? And what about the pending legislation that hopefully criminalize a lot of the common data acquisition methods? And I said, I think those are really solid questions. We’re definitely gonna do an episode on them. My immediate, unfiltered answer, and this was like, 6am this morning, and I was really tired. Is that data collections like sex as long as somebody is getting informed consent? It’s all good. It’s when you don’t do that, or it’s not informed. You have ethics problem and the response back was, I agree, but marketers get real Really shifty, with, quote, consent in the sense that you get these privacy notices. And then you go and read them. And it’s, it says like, here’s a list of 300 websites that all get this data and no links to any of them. So you have to manually researched and and tag each one of those go into each one of those to opt out. And even some companies are saying, we’re not going to honor do not track in your browser because we don’t know if the user or the browser said it. So he, my friend says in the sense in your analogy, it’s like, we’re doing what we want, because we don’t really know what you want, and we don’t know that you are opting out consciously, so we’re just gonna do what’s good for the marketer. Now, obviously, from an ethics perspective, that’s kind of a crap answer. But Katie, in terms of what you’ve been seeing with marketers behaving ethically meaning there, I guess we should say we’re using utilitarian ethics doing the most good Doing the least harm to the world in general? What do you see marketers doing right or wrong with their marketing analytics?
You know, I feel I think, you know, if it was sort of a universal across the board, the GDPR. And the California laws are good, but they only extend to those specific areas. So you still have the rest of the world to contend with. And it’s not a it’s not a small world after all. As as I was saying it I realized how it was going to come out. So you just kind of have to go with it. But you know, yes, California is the large is one of the largest states in the United States. And yes, GDPR covers a lot of the EU but it does not cover everybody. So there are still ways, especially if you are legally, you know, incorporated in a different state but you are working out of California. Like there’s ways You can like squint and get around these laws. And so I think that if everybody was sort of at the same playing field of like nobody had any data, okay, then we’re all on the same page. And we all have to figure out something different. But you’re in this weird hybrid space where some people have data, some people don’t. Some people are trying to figure out how to script the laws and find data so that they can keep their competitive edge. And I think that that is where rules being broken, and things are being done really poorly is happening. I think that that’s where people are panicking a bit because they’re like, Oh, crap, I’m based in California, we know have these laws, but I still have to get the data. What can I do? And I think that consumers are starting to get a little bit more savvy about what that means. There’s still a lot of education that needs to be done, but I think it would be better if everybody had sort of the same level playing trialed, have no data at all. Now, that would be problematic for us. We are a data analytics company. But we would figure out something else.
Well, I and I think that raises a really good point with it, which is, maybe we’re paying attention to the wrong data as an industry. And I had the example I keep coming back to this My Little Pony. So if you rely on traditional data, demographic, psychographic household zip code, all the stuff that we’ve we know where our tried and true to some degree, and you were the marketer in charge of the My Little Pony franchise, you would say, Okay, my target market is typically human females between the ages of eight and 13, right? And you’d say, okay, yep, that’s it. So we’re going to get our analytics st collect consumer data, we’re going to get all our cookies and by our lists and stuff to target that market. Now, we know from a cultural perspective, behaviorally, there’s an entire segment of men 26 to 40, who happened to really love my little pony and have way more disposable income than the 18. Eight to 13 girl market. And if you rely only on that demographic data, you miss that market segment you missing a lucrative market segment. Whereas if you pay attention to behavioral data, what do people do? Regardless of who they are, you’re going to get a much more effective look at the way people might want to do business with you. When I when we look at things like our most valuable pages report that we use Google Analytics to identify which pages have value on a website, we don’t care who you are, we don’t need any information about who the person is. We are looking for patterns of behavior that indicate, you know, this page tends to nudge people towards conversion more than any other page on your website. So feature it. I don’t care if you’re a 78 year olds, Hungarian Jewish person, or you’re a 22 year old Old Angolan person, it doesn’t matter male or female skin color race All I care about is that you’re doing the actions that lead to conversion and and so I think that’s one avenue to solve this don’t you?
I do and you know it’s such an interesting thing that you know if the shady practices of how data is collected a route about people go away. There are other ways and people will willing you will willingly give you data people are not short on opinions. If you start asking people opinions, you will collect so much data more than you ever thought you would need it because people love to give their opinions good, bad, indifferent. And you’re absolutely right, Chris, that kind of behavioral data versus demographic data is probably more valuable because I think that what we’ve seen over time is that demographics are good. They’re a good starting place, but they very rarely are indicative of a specific behavior. And I think the My Little Pony is an excellent example. Great documentary on Netflix, by the way on that whole subject, it doesn’t mock the culture at all. It’s actually just really informative and interesting. But I think the behavioral data is the way to start to solve that problem. Now, the reason why because I’m sure you’ll ask like, Well, why don’t more companies do it is because it takes longer? It’s because it’s not necessarily just numbers. You can’t just crunch it and come up with a, you know, numeric answer. It takes a lot more time. And it’s a different skill set. And it’s qualitative data. It’s subjective, its opinions, and it has to be representative. And that does take a lot more time. But if you start the process of collecting some of that information, then you’re going to have a much richer data set and you will be able to do some of that customization you know, getting started with something Like a Google consumer survey is a great place to start. And they actually do. They run their surveys all the time. So they have a lot of bite sized pieces of information already about people’s opinions about things like devices and, you know, other tech things that you don’t necessarily have to rerun that study in order to find out that information. If you have Google Analytics built into your website, because of the types of places that people come from, or the types of sites that people spend their time on, you get some of that information, some of that demographic information, but also some of that behavioral information of, you know, where do people spend their time? What things are they interested in? But also Chris, to your point, you know, what are the things that lead them to make a conversion that behavioral data so the behavioral data doesn’t necessarily have to be me asking you why did you do that thing, you have some of that already baked into your systems? So you can sort of see like, this is what’s going on.
I think that raises another really good point for marketers too, which is, you’re collecting all this data, but you have absolutely no idea if it’s relevant or not. And you alluded to this earlier, we’re collecting all this information. And maybe it’s a good starting point, but it is not indicative of conversion. And I think if you’re not doing advanced marketing analytics, if you’re not doing stuff like, okay, let’s put all of our data that we have access to into a essentially a giant table, a giant spreadsheet and run a regression against conversions or completions or purchases. You don’t know what data doesn’t does not matter. And so I think there’s a really strong opportunity for a marketer to do that with their data and go, Oh, all this data that could get us into trouble PII demographics, protected classes. Look, it has no relationship on conversion whatsoever. Let’s stop collecting it because it is mathematically just not relevant. If more marketers did that. I think they would have better outcomes because be focusing on the metrics do matter, but also potentially removing a whole minefield of liability. But to your point earlier, the reason people don’t do that is that advanced regression analysis is kind of hard.
Well, it’s, the methodology is hard. But the data collection also, it just takes a little bit longer to do, you know, you have to have a rich enough data set to be able to do a regression analysis on it can’t just be well, I collected data for one day, therefore, I know why people are doing what they’re doing.
Yep. But and this is something that came up in a webinar I was doing recently someone was saying, Well, what do you do if you don’t have those skills? You don’t have access to that technology? We’ve had access to mentally the scientific method for five centuries, right? I mean, probably longer about maybe 10 or 15 or 20 centuries. Even if you don’t have a machine helping you out, you can still take a variable tested, and identify over time Yep. That to have no impact on the number of people who are who converted this month? Or this combination? If you have a hunch, and you test it, and it proves you wrong, I think that’s a valuable practice for marketers to get in the habit of as long as they’re uncomfortable with being wrong. But again, that’s something that culturally, I think is a risk tolerance problem in marketing analytics.
I would agree with that, you know, it makes me think back to running surveys for different departments, different teams, and they already had the outcome in their head of what they wanted it to be. And a lot of times what we found was the opposite was true. And but they had already had no I already know the headline, I already know what the story is. And unfortunately, the data just didn’t support whatever their idea was. Now, you recently ran a very quick survey just to sort of test the waters on Instagram stories, and I personally was surprised by the results. And I think it does tell an interesting story because I was going into the study with an assumption that the results would be something different. And they’re not. And so that gives us the opportunity to dig in further, but it takes a little bit longer. We can’t immediately just say, okay, boom, we have the answer we’re done is further investigation. Now, if you’re anything like us, then you’re super curious, and you want to keep trying to understand what’s going on. But I think it goes back to sort of the original start to the conversation. A lot of times marketers aren’t given time to be curious, they’re given these outrageous demands, you know, from the Overlord saying, I need results now. I need them yesterday. And I need us to have, you know, 50% revenue growth by tomorrow. And so there’s no time to do that research. And so it does take some planning and it does take some buy in to say, you know, what, we can get to the Answer, we get to the better answer. But you have to give us time to do it. And I think those are the conversations that are not being had and or not being heard.
I agree and I think at the root of this issue is the fact that ethics in marketing ethics and marketing analytics or anything is dictated by the ethics in your company’s culture. If you are an unethical company, you will use data in unethical ways. If you are an ethical company, you will use data and ethical ways and there’s that’s something that you can’t fix with technology. That’s something you can’t even fix with process that comes down to the people that you hired, the people who you work for and with and if you work at a company that you have an ethical conflict with, it might be time to start updating your LinkedIn profile because if you’re being asked to do things that are unethical. In an unethical organization, you have two choices either comply. lose your job and pert, silly, I feel like you’d be better off. If you care about ethics and values, we better off moving on possibly, what do you think?
I would add the caveat that there is a third option. So your options were comply or move on, I would say the third option is to try to, you know, change the culture. So, you know, highlighting these issues in a way that are non confrontational is a way to start to say, you know, I was looking at some of our practices here, some recent like, there’s ways to start the conversation, maybe suggesting starting an ethics steering committee, where you have different departments represented different, you know, roles throughout the agency represent. So I would say that there are things to try if you were invested before just sort of, you know, either giving in or giving up. You know, it is a problem and as there is more prevalent sense of automation and artificial intelligence and machine learning and deep learning, the problem is only going to get, you know, bigger because it are it is the people programming, the machines introducing their thoughts, their feelings, their beliefs, their biases, their prejudices, their ethics into the machine. So the machines are only as good as we are. So we have to start with ourselves first, which does sound especially in the culture that we’re in currently, it does sound overwhelming and daunting. But within your own company, just start with what am I doing? What do I bring to the table? And then you can start to look around to your manager, your team and say what’s going on within my team and just start slowly making those steps to see you’re not going to change everything overnight. But start somewhere and start with yourself to say what am I doing Am I upholding Right sort of ethics and you know the right transparency with my customers if not start there.
Right is a great place to end there. So if you have further questions on this topic, let us know, to fascinating topics to dig into about what ethics means, in the modern world, especially to Katie’s examples about essentially programming what we consider our ethics into our machines. Feel free to leave a comment on this post over at TrustInsights.ai dot AI join our slack community if you want to have this discussion in real time at Trust insights.ai slash analytics for marketers, I will talk to you soon. Take care
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