Pull Up a Chair: A Conversation with Steen Rasmussen

Speaker A: Analytics Friend, a podcast. So good morning, good evening, or good night, wherever you are. You're just, uh, starting another episode of Analytics Friday Today. Today you have an awesome, uh, guest. Uh, dear guest, we are here presenting Stien Rasmussen. So Stien is uh, analytics leader, uh, in the Nordics, in Europe, in the world and beyond that. Right, Stien?

Speaker B: That sounds like me. Yeah. So at least a part about going beyond.

Speaker A: So Sting, can you present yourself for the audience to know you better? Most of them for sure, they know you already. But uh, you can put another angle on your site.

Speaker B: Okay, so, um, I think the main other angle to start with is saying that my background comes from business and that has actually impacted my approach to analytics and data massively along the way. So yes, I have done my Google Analytics certification and I can set up stuff, but at the end of the day I think there's people out there that's probably faster and more efficient in doing that part. So my secret sauce in the analytics context is really trying to show uh, you the money, saying, what is the return on analytics, what is the business cases, why bother and why do we fail? Because very often that's the sad story as well. There's a lot of risk and challenges around analytics where, and I think this is my current standpoint, basically we're not failing as analysts, the companies are failing us. You can ask me about that later because I think it's really a strong talking point now, uh, that the organizations are not supporting it well enough. And I guess, um, I've been working out of Denmark. I started co founded an agency 20 years ago called IH Nordic that we built up to the uh, thought leader analytics company in the Nordics, I guess. And I've been traveling spreading the gospel around commercial analytics. IH Nordic1, um, best analytics agency in Denmark, uh, 12 years in a row. We got nominated five times by the Digital analytics association as the best analytics agency in the world. Uh, I got nominated four times as best practitioner. So yes, I'm that type of nerd.

Speaker A: Yeah. So you have all the things that uh, are ready to talk to us. Talk to me in this podcast. Um, and I thought that um, you are not the guy that uh, are very technical, but you look at the things with the side of business and um, that's my take too. I prefer this. Okay, so you do an investment, you do a tracking for what, what you are wanting to take out of this. So um, I, I see similarities with me, of course, I'm very much younger than you, so almost it's uh not

Speaker B: like I'm a thousand years old or something but it's.

Speaker A: No, no, no, no you are, you are uh, you are new, you are a uh, brand new person and your, and your mind it's very focused and very straightened the experience that we get that for the years that we've passed by so that we should take on that um, we are on the. I um think uh, we are on the crossfire of many uh roads to go. So we went for everything. You can track uh then you get to GDPR and you have to track with careful, with consent and now we get. Okay so the browsers went off, Apple went off uh, about tracking. So it's more difficult, difficult to track. Um but the question remains uh, what companies can do nowadays to do with analytics. Because uh, I see small smaller companies, sometimes big companies looking at um, uh looking at their uh, campaigns for the sides of the ads and not for the sides of the business. All agents out of some are giving click through rates impressions and that's not the take for if I have a business I don't care about it. I only care about uh, I'm reaching the right person, I'm converting for my business. In the end of the month what is the uh, the long stake that I have to tackle, what is the investment, what is Roy and so to speak. So give me your take because on that our listeners will be glad to listen to you.

Speaker B: So I think there's been a major shift in analytics right because and it's partly Google's fault. And it's Google's fault in the sense that they um, somehow, well not somehow they failed with the rollout of Google Analytics 4. Right. They were dominating the market with universal analytics and then they rolled out Google Analytics 4 which is a good platform but at the same time it's a much more complicated platform so there's a lot more choices that you need to make. And I think for companies it opened up their eyes to okay but if I'm going to do uh a new set of tracking is this actually the right tool? And Google Universal analytics was uh, kind of a one size fits all. You could do most things with it but it was not the amazing tool mediocre for B2B tracking. It was uh, not really amazing for customer lifetime. It was really strong for E commerce. But if you had like a complicated business process then it was not good. And I think what we've seen now is a fragmentation of tools so the preferences has really moved in a lot of different directions based on the businesses and their objectives. And I feel this is super healthy.

Speaker A: So um, um, you see amplitude and you see other tools because of the gdpr, uh, rising and uh, it's okay with that. But um, what you see about um, the customers, they are seeing the value of that or um, they are constantly silos about the data that is in marketing, that is in support. All the data, it's not tied together. I think analytics, uh, tell me if I'm seeing these things correctly and give your take. Do you see analytics, um, um, be a part of the data team of the data that the company has and um, the data all tied together to give, to know better the customer to know better all the process for the customers. Like uh, it's a good customer. It's, it's going to, is a very uh, large complaint is always complaint in that Take um, analytics and not only analytics because you only do analytics if you get more investment into analytics. Otherwise you don't care about analytics. It's, it's. Am I, am I, am I seeing correctly?

Speaker B: So, so I think, and this is, it has been one of my talking points right now, right, Saying that a mature organization, uh, will do this. So, so. Well it's, it's not true. You have different types of organizations where analytics is important in different degrees. Uh, and you have some organizations where it should be more important. Uh, but it's not. It's like a health check that they're not using or they're gathering the data but abusing it to not being data driven and not being data developed. And from that perspective then analytics is a waste of time. Then it's just an alibi for making other decisions. So you can. So I'm doing, I'm traveling now with a presentation talking about um, um, the prediction paradox and something I call decision laundering. That how things have changed in the sense that people in organizations are getting really good at using analytics to justify decisions they have made without data. So they decide, okay, we're going to run this campaign. And then at the end it's going to be, they're going to come to the analytics team and say, hey, how did my campaign perform? And the analytics team will give them some numbers. And then if they don't like the numbers they say no, no, no, these are bad numbers. Give me some better numbers that I can show. I cannot show these numbers to management. I need better numbers. And because analysts are nice people, we give them better numbers because we don't have the mandate to push back. Uh, very often we're sitting A place in the organization where it's like you shut up and do what you're told. And that is one of the reasons why companies fail. Getting value out of the data.

Speaker A: You brought a very interesting point that um, uh, should. Analysts with AI will have more time to do other things. One of these things can be more strategically to the company and to help um, the marketeers and the campaign managers and so on to give a better side and a better cohesion of the data to get uh, the data that they'll need to be successful.

Speaker B: Yeah.

Speaker A: What's your take on that?

Speaker B: I think it's 100% valid. So right now I'm basically helping organizations find people like you and me to sit in the analytics team and proactively go in and go to the organization with recommendations. So instead of being the passive function where we're sitting waiting for somebody coming asking a question, then it's being the ambassador that goes to the marketing team or the TikTok specialist and say listen, I have some information that you need to know because what you're doing has this impact or it's working in this way or uh, going somewhere else and saying okay, there's a challenge with some of the adwords. They're not performing or they're having an undesired effect. So having this storytelling and the ability to go in and actually proactively doing data driven business development, that is a huge um, opportunity. So yes, I really feel that it is so needed.

Speaker A: So like the Mandalorian said, this is the way.

Speaker B: Yeah, yeah, yeah.

Speaker A: So um, but um, there's a lack of culture because agencies give um, the numbers that we are talking CTRs, impressions, um, conversions. Oh, I don't know if this is a conversion or give them m. Give the numbers that um, they are not real tied to the business of the customer and the customer are internalizing all these campaign managers inside because uh, with AI and Google and other platforms are doing that, it's very fast to come up with uh, a campaign. So um, the brains that you need, it's for strategically to know better your customers to do uh, strategically campaign with creativity, with data to give your better thing and your better thing to your customer. The better results. I mean.

Speaker B: Yeah, absolutely.

Speaker A: What do you think about it? Because you are talking about the paradox of um, that I like too. This is another question inside the same. Sorry for that. Um, you are giving the lecture uh, of the paradox of prediction, um, uh, with bad data to justify decisions. Um, and then they go to analysis and say this is not the um Numbers are correct. I believe that as well. And I know that as well. So um, how to shift this paradigm? Because the paradigm is um, are we all together in the same team, in the same objectives to give better business, better customers?

Speaker B: I think part of this situation is that um, in a lot of uh, organizations the mentality has been that analytics is kind of your online finance team. It measures what happened and it's supposed to be a very strict science and everything is supposed to be really well documented and statistically correct. The challenge is that in all organizations, well not all, but in most organization, uh, you will not go to the finance team and ask for better numbers. Finance are numbers that are non negotiable. You have an accounting principle and this is how it's structured and this is how we use the numbers. And if you file it wrongly, then you get to the message to file it correctly because the numbers need to be correct.

Speaker A: Yeah, our data.

Speaker B: Yeah. The challenge with analytics data is that somehow we ended up in a box where analytics data is negotiable. It is not a fixed standard. If I give you a report and you don't like the report, you can tell me to give you some other numbers. It's not like saying that you can go to finance and say yeah, I spent too much money this month, but if we change the currency then suddenly, then I didn't spend too much money so can you please change the currency so I look better? Then finance will say you must be insane. And ah, they will go and tell your boss that you're insane. Right. Because those are.

Speaker A: Let me ask you another follow up question that is uh, it's tied to your speech that um, at same point we don't get all the data in analytics. It's impossible. We never take all 100%. So it's not um, in the sense that um. I agree with you with finance and the numbers. In another sense we don't, we, we in analytics we are not um, an accounting system because we don't have only 100% but we have uh, tendencies to have 85% or we don't have all data. But people think too that uh, I get that in customers, that oh no, no, if I have 100 orders in the system, I have to be 100 orders in the analytics and I talk to them. Sorry, but maybe your system um, grab that. But technically um, can be a problem with um, with the script, with the machine, with an accounting system with analytics that they want not to be tracked by that. So if you don't want to be tracked. You don't get that kind of information. What do you think? It's another, another technical way of speaking.

Speaker B: So there's two dimensions to it. Right? So, and then one goes really back a long time. And then I think from Finalytics is saying that the cost of the next percentage of perfection, uh, is increasing. So saying going from 80 to 81% that cost uh, something. But going from 81 to 82 that costs more. And so the cost of the next percentage is exponential and the cost of the last percentages will be so extreme that no companies would be willing to pay it. So it would be like, like a magic moment. You have hundred percent for six seconds and then something breaks again because there's so many external forces depending on it. So it is like you're saying, um, finding the exceptions is saying when is it good enough? When is it actually uh, good enough for us to make decisions on and say okay, let's aim for 85 and then work from there. So the important thing is with analytics is saying that uh, what's the, your, your data is always wrong. The important thing that is that it's equally wrong all the time because then the trends are correct.

Speaker A: Yeah, uh, that's, that's the way.

Speaker B: Yeah.

Speaker A: So um, okay, we are, you are pretty aligned on that. I think the same way. So um, and I, I'm glad that I'm aligned with you. So um, there is another point.

Speaker B: Can I look back to that? Because there's also the other thing. And this is, so this is a Jeff Bezos moment, right? Bezos talks about the 70% saying, hey, when you have 70% of the data, what would the last 30% have to say for you to make another decision? Right. So he goes in and then, so instead of uh, looking at the data quality first and saying, okay, I need 100% to make the decision, he says, okay, when I have 70% of the data, what decision am I going to make?

Speaker A: Yeah, that's true.

Speaker B: And uh, would the last 30% actually change anything from the decision that I'm making? Because then you can actually speed up the decision making process. And I think that's really a positive approach nowadays.

Speaker A: Nowadays we have to be speedy, speed enough to get the decision, the opportunity to make business are increasingly uh, so the time it's increasingly became thinner and thinner. So you have to be very fast to move up with confidence. So yeah, I agree with you. I agree perfectly agree. What do you think about the um. So uh, now the industry is moving to mmm, models, uh, Google is going to Meridian now is integrating on the Google 360 with the news that we see on Google announcement. What you think about it uh, and what is the stake that uh, brands can take by that?

Speaker B: I would love to say that I'm unconditionally for it. I think that the biggest problem is that when I go and look at most client setups, um, the biggest problem they have uh, in general is that they can. I'll say it, I'll. They suck at campaign tracking. They're really bad at using UTM codes and so, so it means that their traffic will be classified based on Google's uh, setup and that will then be the information that gets put into the mmn. So so the problem is actually most companies do not have the data quality in analytics to do MMN data. Uh and now it just looks like they can do it and they get an idea and it will be provide over representation from some channels that are not necessarily worth it. So we need to.

Speaker A: It's like a carrot. It's like a carrot.

Speaker B: Yeah, yeah, yeah. It's the lazy man solution, right? Saying yeah, no, no, you don't have to do anything. We'll just take your data from here and put it in and then you don't have to think and then you get the same thing as you did back in the days when they launched, um, saying okay the Google channels are really important uh, which they are but it's kind of just setting yourself up for being you know the mmm says

Speaker A: yeah, yeah, yeah I see, I see your point. So I and I agree with that. So um, the major problem that we have on the customer side is that the quality that is enough for working with these models and um, the change of the data because we have to be some historical part of the data to be meaningful to these analysis. So everything is changing so fast uh, and the data will be changing as well because some customers don't know what is a data layer means, uh, what is important of they are changing their websites constantly in the apps and uh, they are forgetting all the time that they have to put on the process to measure to the measurement as well. So uh, on that take uh, what is uh the hope that we analysts, we analytic guys have on these trends today? AI Mmm. Lack of measurements and poor quality sometimes and or uh, only seeing a part of the Google channels as well.

Speaker B: I think the first thing from my side would actually be saying getting management to realize uh, how valuable the correct data is and uh, how big a difference it can actually make for your Business if you have the correct data. So I've been talking to a lot of leaders that are complaining, saying they cannot make decisions on the data, they don't trust the data and but going ah, to sound rude, but it's very often their fault. Uh, I just posted an article, um, where I talked about continuity in data, that it's really critical to make sure that if there's no continuity, if you keep changing your setup, then your historical data will be worthless. So you need to protect the setup and then give the organization the mandate to well, uh, point out the people, uh, who are not doing their part of the deal, who are not adding their campaign codes, who are running things, uh, um, outside the rules. So the challenge is that it's probably more of a culture problem than it's an analytics problem. Uh, so all the good people in analytics have to admit are doing a good job, but it's an uphill battle because they're not getting the support that

Speaker A: they're supposed is needed. Yeah. For the process. So I think, um, what's your take about. I think we need the data governance in the companies that, to have all this data that is they are piling up and it's critical information to know to construct another product sometimes to give better support, to get more about your typical customer. So what is the take really? So I agree with you.

Speaker B: Yeah. Last year I did a presentation where I talked about how um, if you looked at what analytics data could do beside uh, uh, measuring your campaigns and it's actually one of the best, uh, thermometers you have in relation to your market situation. Because it really, if you look at it like that instead, so you get an idea, what are people interested in, in uh, our products? What is moving now? Uh, what is not moving? So as a market indicator and then by adding a level of data around the competitors as well, then it's an amazing tool to understand the market situation while it's happening. Right. But we don't. Everything is so reactive. And, and for me the magic is if I can help management understand this saying this is not a bi tool because it's actually here and now this is showing you what is going on in the market now in this second. So one of the big trends right now I see is this, um, entire conversation and analytics moving from tracking to measuring, uh, intent signals. So going in and looking at what is it, what, what, what is the intent of the users that we have on this site now and how is that intent changing in relation to where we are as a Business. I think that's, yeah, that is the, probably the, the best thing because that could be tied into an AI to help you interpret the, the intent signals in real time. Where do, what do you need to do now? What are the decisions you need to make? What are the choices that you're facing based on the intent that you see? So analytics to the forefront of the decision process instead of being somebody doing a monthly report or a dashboard.

Speaker A: Yeah, yeah. When you do a monthly report you are really out of the game because only reporting, not giving information. Yeah, yeah.

Speaker B: The monthly report in my book is, is kind of a, it's a data theater. Then you go in and you do, you go in and everybody spend an hour talking about the numbers, what happened this month and then we say okay, we'll meet back next month and then we'll talk about what happened next month. Right. But you don't make decisions on it.

Speaker A: It's not actionable.

Speaker B: No.

Speaker A: Right. I ah, understand your point. I understand the degree. So another, another take that um, that we have here in analytics and the uh, analytics side. If we have Steve, if you have a crystal ball, what you say, what will happen in two, three years? Because I don't say five years. Because I think it's too much.

Speaker B: Yeah, yeah, I can't, I can't predict five years. I think one of the big shift that we're going to see is the, that that we need to somehow be able to uh, track agents better. Because right now what I see is some of the trend is that the online behavior is going to um, be much more uh, controlled by non human. So if we don't know if we cannot track that. Uh, so basically you're losing insights in your customer journey because more of them, the steps are not being performed by customers, they're being performed by agents in parallel systems. So you won't see. A classic example I'm using when I talk about this is saying that so you're a shoe, ah, manufacturer and suddenly an order comes in for a pair of shoes and that's it. And it's even being sent to one of these uh, anonymous addresses. So you cannot even determine uh, you don't have any idea who bought the shoes. And that's the only uh, the purchase signals is that a purchase happened and that's very late in the process if you want to be able to plan and manage it.

Speaker A: So what you say is you have to be on the, to track the agents as well to see if our website, our content, our business gets uh, a degree of openness, uh, to these. Like Google is moving on the ecommerce site. Right. And the agenting.

Speaker B: There's this super interesting lawsuit that just started in the U.S. i don't know if you saw it but the lawsuit is, I think, I can't remember who put it up but uh, they have made a lawsuit against OpenAI because uh, they were sending ah, they were allegedly sending the search strings that you were entering into your uh, uh, to meet her at Google. So they. Yeah, yeah. And then I think the idea was saying that by having that then they could determine where you were in your process, what you were looking for. And so even if they didn't get the full query, because that was also part of saying that they were sending all your data and they couldn't. That would be preposterous because the idea was that they were sending this data to Google Analytics which is, would be such a blatant violation of Google's own rules that it would be an embarrassment.

Speaker A: Things about privacy. Right. Because if OpenAI will be. I saw an article for um, saying um, that um, information like email and so on, a lot of information is going to these advertisers. So it's critical at the point that we see this is, this is going um, the wrong way again because yeah,

Speaker B: so a lot of people are after the European Union in relations to uh, consent and compliance and data privacy. But I must admit that very often I have the feeling that it's probably a good thing because it helps ah, us be other things than consumers. There's the system where all the data is being transferred to the market so the market can sell us things. It only gives us, it makes us very one dimensional at people and the only thing is the focus on um, how they can get our money.

Speaker A: That's true, that's true. So um, yeah, I think the same way. I think sometimes it's too many rules but we have to have rules on AI. Otherwise will be a uh, complete nonsense. Uh people doing everything that is not on that way. I think we Europeans are doing a good job on that side. Okay, let's simplify some things that we have to do it. Don't overcomplicate it. But the values and um, that Europe uh stands for must be um, um, gathered and protected on that way. Yeah, not be like.

Speaker B: Because in the US you have like this, that uh, basically personal data is being traded as a commodity on the

Speaker A: same level as a currency.

Speaker B: Yeah, yeah, yeah. It's just a product. Right. Saying okay, you want people who have this disease Sure, I can give you those like, but that's kind of not something I want in somebody's marketing plan.

Speaker A: Yeah, it's not. It's a nonsense. You get um, all in the states. Right. You get and uh, other states that uh, get all the information that you want and uh, all the private uh, things are going wild and every company can sell information. So. Okay, sin. This was a very fast conversation. We started a minute ago and it's almost half an hour and our conversation was really, really, really good. Um, can you give a recommendation to our audience, um, and um, how we can connect to you as well. Just um, to heads up to see your presentation and sometimes you can see you here in Portugal to do a presentation as well.

Speaker B: That would be perfect. So I'm very open. I like to travel and I like to evangelize and spread the GOSP. So um, um, LinkedIn is my uh, go to channel. I just. So find me on LinkedIn. That's the easy thing. I have a newsletter that I like, but I'm also moving it to substack because I'm so talking about trusting data. I feel that LinkedIn is not necessarily serving my audience well enough. So adding a substack dimension and then I think, um, for all analysts out there, uh, it's very much getting out and meeting other people. So if you can attend Measure camps, go to measurecamp.org. that is Ah, an amazing opportunity to actually come out and get a voice and be part of the community.

Speaker A: Yeah. Right.

Speaker B: So maybe it's time for you to arrange a Measure Camp, Lisbon.

Speaker A: Yeah, I have on that way because. But uh, I have to move some sponsors otherwise it'll be difficult to move on. At the time, uh, um. In 2018, 19, I was thinking about the colleagues to do a um, major campaign but was uh, difficult then Covid. And then we stop everything.

Speaker B: So.

Speaker A: But uh. Yeah, but we should uh, go there because um. Always, always good conversations happens on Measure Camp. I saw it. I went one here first. Ah, in Portugal. Was in. Was in the Algarve in Faro. Was the first Measure Camp here in Portugal and was uh, really good because we met a lot of guys that are uh, doing things uh, are doing really good stuff on the. On the analytics and they visualize a lot. Not only the analysts but uh, other people that come to the um, to the Measure Camp. Like marketeers that know what should they need to be educated as well to give a uh, proper uh, management of the marketing and campaigns and digital and so on. Yeah.

Speaker B: And then just to back So I left, uh, ih, uh, Nordic. So I talked about my story that I, uh, started IH Nordic, but I actually left it in September. Right. So now I've kind of taken an independent role. So if. If, uh. Yeah. So I'm open to talks, but I'm not looking for a job. I like being Steen. I came across this wonderful Steve Job quote saying it's better to be a pirate than to join the Navy, so.

Speaker A: Yeah, true. Yeah. I'm working for myself, uh, since 2012 with the highs and lows. Everybody got it. But, yeah, I'm 54. Just you to know. Yeah, yeah, yeah. And I think, uh, I'm, um. Yeah, we got more independence, what you say and what you can say. And, uh, it's better to have an independent, um, company or a role or something.

Speaker B: Absolutely.

Speaker A: It gives you liberty to do other things that you cannot do when you're tied to a company. Yeah, true.

Speaker B: So it's easier to be the pirate than to follow somebody else's rule in the Navy.

Speaker A: Yeah, true.

Speaker B: Cool.

Speaker A: So, Steen, thank you very much for, um, your time and attention, uh, and go to. Let's talk. Let's record right away. Let's book. And it was an awesome and very, very straight, uh, answer. And I like it very much. I like it very much the episode. And, um, so thank you very much, uh, audience to take care. We'll bring another great as Steen as another great guest to, uh, our podcast. Thank you very much. See you next time. Analytics Friday podcast.