In this podcast episode, we interview Steffen Hedebrandt, Co-founder and Chief Revenue Officer at Dreamdata, a B2B revenue attribution platform.

Steffen shares his journey to co-founding Dreamdata, and how the platform is solving the problem of attribution and focussing on understanding the customer journey to support multi-touch in the B2B world.

He also shares why it’s important that B2B marketers start digitalizing their customer’s behavior today, and how they can get started with attribution.

Transcript: Interview with Steffen Hedebrandt – Dreamdata

Mike: Thanks for listening to marketing b2b tech, the podcast from Napier, where you can find out what really works in b2b marketing today. Welcome to the latest episode of marketing b2b technology, the podcast from Napier. Today, I’ve got Stephen Haider Brandt, who is the co founder and chief Revenue Officer of dream data. Welcome to the podcast, Steffen.

Steffen: Thanks a lot, Mike. I’m happy to be here.

Mike: Fantastic. So can you just start off by telling us a little bit about yourself and how your careers taking you to found dream data?

Steffen: Yeah, happy to. So ever since I came out of university, which is now more than 10 years ago, I’ve been working in you can say digital b2b companies in roles related to grow, sales, marketing, etc. Before starting.co, founding dream dinner, I worked at a company called air team, where I was the head of marketing. And then we went through this journey of like 15, to a little bit below 100 employees and zero in ad spend 200,000 euros of ad spend every month. And that really got me into this whole attribution journey, which I’m now 100% committed to, because at the time we were selling to schools and businesses, and I really, really I come from, like a line of thinking where like, if you do marketing, you do marketing to drive more revenue. And since air team was selling to schools and businesses, we typically saw that a journey was would easily be like three, six or nine months long. And there would be several stakeholders involved in the journey. And I desperately wanted to understand every time I put in another 10,000 euros into the machine, what came out on the other side. And I just have to admit that that was super hard to see anything reasonable about given the tools I had available at the time. which ultimately led me to joining my two co founders last Nola who I got introduced to from local dc in Copenhagen, saying that, hey, these two guys are actually solving this problem you’re having. I think I read literally replied this guy. Sure, I don’t think they can solve this problem. But I’m happy to meet them. And that’s kind of that’s kind of how I met my my two co founders said the dream data.

Mike: That’s interesting, because that sounds like a lot of that’s about the kind of startup community in Denmark, and particularly Copenhagen, which I believe is pretty strong.

Steffen: Yeah, I definitely think there’s, there’s this kind of the first spark is important, because then, you know, the first success is important, because then it kind of brief people who’ve seen what a startup is like and know what’s working. And then suddenly, they have their own idea. And then they get together with other people that have their own ideas as well and have the experience to actually see a company going from just a few employees to Yeah, 50 or hundreds.

Mike: Cool. So I mean, Dream data was was obviously started to solve the problem attribution, you want to talk a little bit more about exactly what you’re trying to do at dream data?

Steffen: Yeah, so I think there’s the topic of attribution is basically try to define it a little bit. It’s basically understanding all the all the things that influenced somebody making a decision on whether to buy or not, that’s at least how I see it. And if you understand this, then you’re able to repeat what works. And that’s pretty nice in business, because then you have a money machine, put in more money, and you get more money out on the other side. And this attribution pocket in my world then has three different pillars. There’s the companies who are trying to understand what happens on a mobile phone, or like in this app download environment. Then there’s a b2c solution where it’s more like typically ecommerce focus, kind of if he buys this pair of running shoes, can I get him to buy more at a later point, and then there’s this pocket of b2b which dream data sits within and this bucket is different because here we are trying to attribute actions to An account, a company taking a particular action. And a company is a result of two or three or four or five people taking part of some kind of buying committee, that all do several different actions, moving towards them being close to one buyer salesperson in in the CRM system. So what we’re trying to explain is really what what takes place when one business is purchasing a product from another business.

Mike: And presumably, for you the challenge, and the really interesting thing is, is this complexity in b2b?

Steffen: Yeah, it is. And first of all, in b2b, you’re selling to a team, and you’re selling as a team. Which means, as I said, when when you’re selling to a team, there’s multiple people involved. It takes a lot of time. And this completely breaks all the traditional tools that marketers would be using, being Google Analytics, Facebook ads, Google ads, etc. All of these platforms are built to understand what, what are the actions of an individual. And the problem about this is that marketing very typically ends up just looking like a cost centre, because the people who are starting the research that are starting this journey for your product, they typically always have a boss who have a credit card. And when the torch passes between those two people, all your spending loves looking at I just put your cost because it was some other person who came in and bought your product directly. Does that make sense?

Mike: Yeah. So I mean, you also talked about the idea of the buying committee. So I mean, I guess what you’re saying is really the problem is, is that there’s a lot of people who influence the decision, but probably only one person who makes the purchase. And quite often, that’s not the purchase the person you need to be marketing to.

Steffen: Exactly. And we’re then also a dream that we’re particularly talking about revenue revenue attribution, as opposed to just the traditional marketing attribution. What we mean by revenue attribution is that we mean, we feel that in b2b all touches matter, it’s good to understand which ads started the journey. But if there’s three months of conversations with customer success, and sales people in between the deal being one, then is relatively stupid to just sign all the credit to the Facebook ad, or the Google ad, and so forth. So we want to understand, if any digital touch that touches the accounts before they become a customer of yours, we want to see that. And then you can make a decision on what kind of attribution model is important afterwards. But because essentially, all attribution models will be wrong if it’s applied to 10, or 20%. of the whole picture.

Mike: And when you talk about customers, are you thinking about, you know, potentially, not just an entire company? I mean, because obviously, measuring impact on a global multinational is very hard, because typically, suppliers working multiple deals, but it would be groups within a large company would be your, your definition of a customer.

Steffen: Oh, that’s a good, good observation, Mike, actually, so. So here, we are kind of touching kind of one of these b2b marketing quintessential that our defined ideal customer profile ICP, which is popular call this like 50 to 500 employees companies. And that’s because of the reasoning you’re seeing there, Mike, that, like, if it’s a 10,000 person company, then to grow this extremely complex, and it’s maybe not, it’s hard to judge what’s actually going on, what we’re looking for is scenarios where you can see kind of a closed loop attribution as possible. Meaning that companies who do their marketing and acquisition of customers online, they have the salespeople who have sit in inside sales teams and called customers, and then they deliver the product digitally as well, because then you you have touches on all of the journey, as opposed to somebody who does some digital marketing, but then ships boxes through a reseller of some sort afterwards, because then the journey sort of breaks and then you cannot explain what’s going on. So that’s why the best fit for attribution are companies that has the opportunity to do some sort of closed loop attribution. Does that make sense?

Mike: Yeah, absolutely. It sounds like you’re saying that there’s still areas where you’re not able to solve the attribution problem. So very large, complex suppliers with you know, third party supply chains is still something you can’t really address is that

Steffen: Yeah, like Essentially, it’s attribution is about knowing more. And you could probably lift those people, as you mentioned before, from knowing 10%, to knowing 30%, or something like that. But ideally, you want to lift them to knowing 6070 or 80%. So that when they make decisions upon your data, they make more money. And, you know, in some instances, it’s just too little insight that you get.

Mike: Makes sense. Makes sense. So you talked about your, your ideal customer, being that being this sort of mid size company. And he also said, typically delivers digitally, because I assume that means that everything gets delivered direct to the customer, rather than through a channel.

Steffen: Yes. So like we like if we get really narrow, we actually prefer software as a service. Because here you have people logging into your product online as well. So now I’m getting a little bit technical, but the way we kind of solve attribution is that we we hand a script for people’s website. And this scripts assigns anonymous IDs to every visitor of the website. And then it keeps a small log book, anonymized about what is every person doing on your website, when this person then identifies themselves, meaning that they submit a form. And that form can be a newsletter, sign up a demo request, or it can be a login to the product, then we get consent to go back and look at what did you do while you were anonymous. So it could be that somebody who was actually a big influence on this journey on this account, did not identify themselves before the product was bought, and they locked into the product. So that’s why it’s really good for us to work with people who have some sort of online login, because then after the fact, we can go in and correct the journey.

Mike: So it’s all about getting up, you know, to a higher percentage of knowledge really as high as you can get. Yes, exactly. Interesting. And you talk a lot about journey. So it sounds like your view of attribution is is really based around understanding the customer journey. Is that fair?

Steffen: That’s very true. Yeah, so that reflects back to what I said before. The first of all, you need all the touches that has a digital touch mapped, because if you are applying an attribution model, or looking at attribution only at on 10%, or 20% of the journey, like whatever conclusion you might come to, then afterwards is probably wrong. So if companies are sitting out there listening to this, I would say the first and most important thing to do is to, to start digitalising your behaviour more, all the way from simple things like if your salespeople are just Cowboys, wood phones, today, they should start using our phone, like a calling software that tracks every time they call a number, they cut it straight to the account, and it’s tracked to the person that they’re calling. So at least the digital trace, the same thing. If you’re if you’re doing your customer success in in some random mail inbox, you should probably move that into, you know, our customer success software. And like, little by little, you start to create traces of all your actions, because it’s when you have all these digital touches, that’s when you can start to analyse what’s the meaningful touch and what’s not so meaningful touches.

Mike: Interesting. I mean, I’m intrigued because you’re building what sounds like a very customised approach to, you know, to the attribution model. I mean, people talk about standard models, like first touch, last touch linear, you know, and more complex ones. They just wrong, or do they provide some sort of approximation? What’s your view on that?

Steffen: So, again, let’s, let’s think about it as a, as a b2b looking at distribution models. Well, I can see. So in b2c, I think, like a less touch model, what was the very last click before somebody bought something is can be quite relevant. Like, if you’re buying a pair of running shoes, you want to see what ad put you on your website to buy that pair of shoes. But this is just never ever going to happen in a b2b scenario, because it’s not a single touch world. It’s a multi touch world. So the very last touch of a journey of 555 100 touches. Yeah, I don’t know whether it’s interesting or not. My point being is that in this first and last touch discussion is that if what you attract appeared as the first touch of a journey might actually be the 20th touch on that journey. You know what I mean? So it’s, the more his most important thing is to capture it the whole journey. Because if that what you think is the first touch is actually the 10th or 20th touch, then you’re actually not able to go back and replicate what God that journey started. Now you’re making a decision on something that is leading you in a wrong direction.

Mike: Interesting. I mean, it sounds like dream data’s view is much more understanding what matters at each stage of the journey and optimising that rather than necessarily trying to do a, an accountancy exercise of putting a value on each touch. Is that a fair assessment of how you view attribution?

Steffen: Yeah, so it kind of there’s different layers to it. So if we’d say like getting the data, that’s step one. Step two, is that you can try to flip, I would say, every time people is asking me what’s attribution model to us, it’s always saying you should use all of all of them before making any decision. Because each model is just representing different parts of the truth. And then lastly, then then there’s the economic value, which is like, we’re very running businesses in a capitalistic world. So we need to do more of what actually has a positive return on investment, a positive return on adspend. So the money component is extremely important. The credit component is very important that, that you actually make decisions that are profitable for you and not lead you into like, a wasting of, of money. But it kind of comes in a hierarchy that you don’t want to just assign credit to some touch, if that touches an irrelevant touch. Think Does that make sense?

Mike: Yeah, yeah, absolutely. So I mean, I think the simple answer, basically, is it there is no magic number for value of each touch or what you do. It’s about looking at from different points of view. Is that fair?

Steffen: Yeah, I think there’s so now that’s another point is that it the value component is, is tricky, because we’re like, what we’re doing is statistics, you can see. But some touch might be more important than others, you can try to highlight that through different kinds of analysis. But essentially, only that one person that made the decision will be the one that can actually answer the question. Like, I really liked that illustration, or that salesperson did a really good sales presentation, all of the touches will just be recorded as digital touches, not weighted on the quality of the touch.

Mike: So so just unpack that, what you’re saying is, you can have a touch, for example, a sales presentation that could actually be different in terms of impact, depending upon who’s delivering it, you’ve got kind of a human factor there.

Steffen: Yes. And then that that’s the part where computers and digital analysis will fall a bit short. And that’s why I’m saying you should think about it as a statistical framework more than necessarily representing 100% of the truth. Because you’re never gonna get to 100% of the truth. You can only strive to know as much as possible.

Mike: Yeah, and I think that’s a really great point. I mean, we see that a lot with digital, you can get numbers that look super accurate, you know, to three decimal places, anything else has got to be right. But actually, there’s, there’s precision on the number and then there’s accuracy of the number and procedures wrong.

Steffen: Yeah, let’s say you’re all the website metrics looks super good one day. And you didn’t change anything. But you did have like, a super big interview in the guardian or something like that. That will never be any digital touch for The Guardian, if it was just printed in the newspaper. But all the metrics on the website looks looks better. So it’s just not everything that is caught in these digital calculations.

Mike: Absolutely. So when you go and see or talk to a new customer, I I’m interested what sort of stage they are, are they typically, you know, do they have a model they’re hanging on to that’s not working for them? Or do they come to you and say, Look, we really have no idea what’s working.

Steffen: So then once we deal with are typically beyond the stage of having a website and having Google Analytics installed, but still, like let’s say 90% are still still operating in a single touch understanding of the of the world. Which in b2b with end by single touches that they look at only the first record, or the last record, like first or last touch, which might not necessarily be the first or last touches just what it says in the original source field in the CRM. But all in all b2b purchases are in a multi touch world that the several stakeholders, there’s calls, there’s emails, there’s chats, and so forth. And almost nobody has a really as a legit multi touch setup. And that’s a complex way of saying that the data that they’re making decisions on is just wrong. Because like b2b is not single touch. It’s, it’s a lot of touches on a lot of different people. Interesting.

Mike: So I mean, the obvious follow on question to this, as I assume people are doing single touch attribution, because it’s easy. Presumably, one of the roles of dream data is pulling in data from all sorts of different systems. So that might be CRM, marketing, automation, your chat software, presuming that that’s quite a big part of the product. Yeah. So talk about, you know, where you pull data from, and, you know, maybe where sometimes you can bring in insights that, you know, perhaps someone hasn’t seen before, because you’re aggregating data from multiple platforms?

Steffen: Yeah, so there’s two components here, I think, let me just, there’s the website and what goes on there. And then there’s all the tools that you’re using. If we start with the website, just getting through a multi touch approach on the website is hugely important. Because typically, you’d see that a personal visits your website, three, four or five times, before they actually convert to like a newsletter, or demo sign up or something like that. If you’re looking at a single touch, you’re looking at him typing directly dream data.io into the browser, and then converting to a demo call. But that person actually started his journey from an ad on LinkedIn, or an ad on Google or something else. But that was the first visit he had to your website. And ask that person now. types in during the.io directly in the browser, it looks like he came directly to your website. This makes you unable to actually do more of what actually starts doing this for your companies. And that’s a huge loss. But that’s just the multi touch approach to the website. We then also plug into essentially every tool that touches your T account journeys, which typically will be the CRM tool, Salesforce, Microsoft Dynamics, HubSpot, etc. And then some sort of marketing automation tool that sends emails to the leads and the customers, then it can be like a customer success or like chat software on the website, it can be an outreach software that the BDR so using, to contact new potential customers. It can be a webinar software, any kind of software that touches the journeys and are generating its own data silos today. We want to plug it in, plug into them, and then pull all the information out of it.

Mike: So you kind of building a effectively a data warehouse of all the touches with those customers. Is that a fair way to describe it?

Steffen: Yes. So our our like, the core of our product is, here’s the database. And this database holds all the touches that you have available on your accounts. And then our magical algorithms then cleans the data and sold it so that all of these people who were looking like individuals actually gets sorted into the same timeline, and all the touches that they’ve had as well. Because then you can start to go and say, Hey, we just want one this 10,000 pound customer, what was the actual real first touch of this account? Oh, secondly, this ad, and we actually paid less for this ad that we made on the account, then you can go back and spend more on those ads.

Mike: Right, right. That makes sense. So, I mean, I’m still intrigued about this pulling together all this these digital touches together, it sounds quite complex. Is it a very time consuming process to deploy dream data?

Steffen: It’s not, it’s not anymore, at least you send it you know, when you do start up you do. You start with doing something non scalable, but we’ve actually reached a stage now where it kind of, you can sign up for our free product. Then we create an account for you and then you you connect all your data sources. And the next day you log in with our algorithms have done the first run and And then from there you will will speak to you about how is the data looking? Is there anything we can improve? So, it’s, I think we’re trying to do something that is extremely technically complex, but we’re making it we’re democratising it. So the marketers can actually do this with no code involved.

Mike: So so all these integrations are all baked in now. And literally, you know, it’s 24 hours from signing up to getting your first insights. Yeah, that’s, that’s impressive. That’s really cool.

Steffen: And that’s kind of because like, when you get to know all these systems better and better, you can stand the dice. What does it mean? If this system calls a customer and the other system calls it an account? How do we then join that in, in our database, and that is that process of standardising all these integrations that we’ve we’ve been going through?

Mike: Brilliant, and then, I mean, obviously, one of the difficult things is getting people up to speed with understanding your approach and understanding how to use dream data. Is it difficult to, to use dream data, particularly if you’ve come from a single touch attribution background, which sounds like most of your customers do?

Steffen: To be honest, I think this is one of our biggest challenges that people are used to looking at the world in a certain way, regarding some numbers from some tools as the truth. And now we’re coming and saying, What made you look like a success before it’s not true anymore, or the way you’ve been doing things are wrong? So this education of the market, because the deep b2b marketers are being asked by their CEOs to to explain what is the best ad channel for us? If they start replying this, then they know that Facebook, LinkedIn, Twitter, Instagram, somewhere else has all touched that account. So by replying that one of the channels are better than the other state, they know it’s wrong, but the CEO is still asking, Okay, the next 10,000 years, where do we put them in? Because he’s thinking in a singular, sits in one single touch world. So there’s a lot of education for us to do in making people understand this, I think this is our biggest challenge explaining this complexity.

Mike: Interesting. How do you how do you achieve that with effectively a software as a service product? You? Do you have assigned Customer Success agents. So how does it work?

Steffen: So I think we, first of all, we try to address companies who are a bit more mature in terms of understanding this complexity. But we also are betting heavily on content. So we produce a lot of different content on on the topic, ebooks, podcasts, etc, to try to help people get more educated on it, and they self educate them on what’s the challenges so that when our salespeople meet potential customers, there’s actually a lot of information available on the website before the call. And if the customers are asking particular questions, then we have blog posts that the salespeople can send to the customers afterwards.

Mike: Cool. So combination of people and content seems to be the solution there. Yeah, yeah. Now, you mentioned something very interesting. I mean, you’ve got what is a really complex product, that’s that, I mean, just pulling the data together is a real challenge. And then you said, you have a free version people can try? I mean, does that mean that dream data is actually not that expensive at all?

Steffen: So for us, we have a free tier that that has two purposes. One, it’s for small companies who can get these insights for free. And then it’s for the larger companies to test what we can actually do with the data. So some can stay in free forever. Some will be bound for, for paying at some point. But I’m leaning towards giving a little bit more value selling reply to your question. So the best of our customers are only wasting 30% of their digital ad spend. That’s the best of our customers. And then it only gets worse from there. So if you think about, like a company who’s spending 50,000 pounds and one finance, you know, what is the high cost for like, gaming back 20 or 40% of that spent?

Mike: Absolutely, yeah, so so the the opportunity to get a positive ROI is is huge, because inherently these companies are spending quite a lot on advertising and don’t know what works.

Steffen: Yeah. And like that’s what’s going on, to be honest, like Google Analytics, Google ads, Facebook ads, LinkedIn ads are all not telling you the truth, because They’re looking at people as individuals. Whereas like the purchases are happening from an account. And that means that the revenue component is always detached from the cost component. Yeah. So, yeah, I think this this thing, I hope that I can find a really, really large microphone and sell off to b2b marketers about.

Mike: Yeah, no, I love that, that concept that that marketing and revenue are detached or somehow split and b2b. It’s, it’s a great way of explaining that the challenge of doing b2b marketing. So I think it’s brilliant.

Steffen: Yeah, that that’s the essential problem. And it’s also why, you know, when a crisis comes, the first thing that’s being slashed is this. It’s the marketing spend, because marketers have too little proof of revenue of their activities. Because we can, we can show to our customers heard that, hey, an average journey from the first touch in an ad until you win an account is 100 days. So by slashing 50% of your ad budget today, then three months down the line four months down the line, you’re going to miss half of the leads that you have today.

Mike: Interesting

Steffen: This information, b2b marketers, for the larger part doesn’t have they don’t have that available today.

Mike: Yep. So you’re giving much more, I guess, much more solid data and more reliable data that’s going to allow people to make far better plans and justify what they do.

Steffen: It’s really there’s a big, there’s two things, knowing it’s knowing what to do next. Because you can see from the data what’s, what’s the best decision. But then there’s also just the proof for the salespeople, for example, that there’s a lot of marketing touches on this journey, or those two, upper management. We spent this much money this is how much how many sales qualified leads we provided.

Mike: Makes sense. That’s, I mean, that’s a really optimistic view, I think of what dream data can do for marketers. Is there anything else you feel we should cover and I think we’ve covered a quite a broad range of different things. And, you know, finishing off by basically ensuring that the market can show their value and keep their job, I think, a real positive way to end but anything else you’d like to mention.

Steffen: I would say, there’s two advices, that I will give to b2b marketers, there’s one, start to always talk about why you do what you do in order to generate more revenue. So you should have a narrative of I’m doing this activity, because XYZ will bring us more revenue. That’s the one part always be able to explain verbally, why what you’re doing is driving more revenue. And then secondly, start building data that can prove that your story is true. So that whenever you do an experiment, you can say, I want it to do this, and this is what happened. If it’s a positive return on investment, you can double that investment The next time you do it. And if your boss is questioning how you spend your budget, you actually have proved that you’ve delivered value.

Mike: I think that’s that’s great advice. I love that. I’m, I’m sure there’s people listening to podcasts, who will be very interested in dream data, and maybe trying it out. I mean, obviously, you mentioned the ability to actually, you know, literally go try it on the website. But if someone has any questions, what would be the best way to maybe reach you and ask you about dream data or anything you’ve covered on the podcast? Oh, that’s just go to LinkedIn and find me. That’s where I spend most of my day. Perfect. Perfect. That’d be great. And obviously, we’ll make sure we put the link to your LinkedIn profile in our show notes. Thanks a lot, Mike. Well, thank you so much for being on the podcast, Steffen. It’s been a really interesting discussion. I think we’ve covered an awful lot about data in a very short time, and I really appreciate your insights and, and, you know, the advice to marketers, thanks so much for being on the podcast.

Steffen: Thanks a lot for the invite my guy, I enjoyed it. Thank you.

Mike: Thanks so much for listening to marketing b2b tech. We hope you enjoyed the episode. And if you did, please make sure you subscribe on iTunes, or on your favourite podcast application. If you’d like to know more, please visit our website at Napier b2b dot com or contact me directly on LinkedIn.

 

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