Guest Introduction
Shilpa Bharti: Today, we are joined by Lucia Vander Brink, someone who’s spent years helping teams figure out how to do experimentation well, not just more often. Earlier as owner and lead consultant at increaseconversionrate.com, Lucia worked with teams running anywhere from one test a month to hundreds, helping them improve both velocity and quality. She’s partnered with brands like EML, British Airways, Indo and Spiro/CXL, building testing teams, setting up experimentation programs from scratch and fixing broken processes along the way. Now, through her new initiative, The Initial, Lucia is doubling down on a clear idea: you can’t rent experimentation, you have to own it. So with that, let’s get into the conversation and hear directly from Lucia. Lucia, thanks for joining us. How are you doing today?
Luca van den Brink: Yeah. Thanks so much for having me. I’m excited.
Conversation
New Year Resolutions and Journey into CRO
Shilpa Bharti: Awesome. Any 2026 New Year resolutions that you would like to share with all of us?
Luca van den Brink: Ooh. You know, I’d like to grow my business and, you know, I hope that I can create more data-driven cultures at organizations, but also build my own team. And I think experimentation is a way to do that and also to, you know, have people create lives and have very fulfilling professional lives. So that’s kind of the journey that I’m on.
Shilpa Bharti: Amazing. We wish you all the best for that and all our good wishes to you for the same. On the same lines, I think one more question that I have for you—you’ve been doing CRO for such a long time, right? Is there a moment or project in your CRO journey that made you think, yes, this is exactly why I love doing this?
Luca van den Brink: Oh, I think that happens many times, right? But maybe sometimes you lose it a little bit because you’re doing it for such a long time. So I’ve been in CRO for 10 years, and the first time was at my first job, and I actually wrote a blog about it without ever having run any A/B test.
Shilpa Bharti: Mm-hmm.
Luca van den Brink: And also, you know, looking back, so I built my first web shop when I was 11 years old. Now, at that time, there were no handy tools to do that. So I would code it all myself. I would implement PayPal somehow, and it would work. But I always was really in love with this online world and you know, the things you can create there and how you can optimize for people to go through their journeys or total worlds of whatever it is you build.
Shilpa Bharti: That’s amazing for an 11-year-old to even think that. I don’t even remember what I was thinking back then. So it’s great to hear that. Moving on to some more interesting questions that I think our viewers and listeners would really benefit from—you’ve worked as a consultant, advisor and agency leader, helping teams set up and scale experimentation programs. After seeing how experimentation plays out across so many organizations, what led you to start The Initial?
Starting The Initial: Owning vs. Renting Experimentation
Luca van den Brink: So I think part of it is my experience of being an in-house practitioner for many, many years. I think most of my career I just was in-house at really big brands and setting up the programs there, and then I transitioned to work with Spiro. And then I created my own agency and from there created The Initial.
But what I’m seeing is—whenever you start an agency, you see the dynamics of how it works. It’s great to have monthly revenues to support your team and to just have that income, but it was also kind of contrasting my love for experimentation because I saw the companies that were actually ready to do it themselves sometimes needed an extra nudge in order to really own experimentation and really bring it in-house because it can also be very convenient for big companies, of course, to rely on external resources. And I think up to a certain point that’s really good. That’s totally normal, because especially when you’re just starting out, you can really kickstart your experimentation program so much by working with someone that has experience, right? So that can help a lot, but there’s a certain limit to it, I think.
The limit is when you really wanna bring experimentation in-house, and you really wanna solve the problems you have for your product, for your business with experimentation and with being data driven, then you have to really adopt that mindset. And whenever that mindset is kind of rented or belongs to someone external, then you don’t fully own it as an organization or it’s not fully in the ways of working. So it is kind of contrasting for me to say this right, because I am now making a living and having a team built on helping companies and kind of renting experimentation.
But then because I really believe in experimentation, I really love it and really think it does good things for dynamics and for growth of companies, then I have to say at a certain point, like, Hey, I think now you can do it yourself and I would like you and the company to transition into owning experimentation and CRO much more.
And you see this at companies where they run like 50 tests per month, I think, something like that. I think this is definitely the type of programs that really need to own it or partially already are owning it, or some people, or some teams are owning it, but then need to start focusing on owning that even more.
There is a certain myth in CRO and experimentation that successful companies already experiment. That’s just not really the case, because there is also, on the other hand, if you don’t run 50 A/B tests every month—on the other hand, there’s a lot of companies that don’t A/B test at all or just need to get started. And that’s where external people can, you know, lift them up immediately and skyrocket everything they’re doing and their whole process. So that’s, you know, the side of things where people are just starting. And then the other side is where people really and organizations really need to start owning it. And sometimes, you know, you can bring organizations from having zero tests to that 50 tests a month and then having them own it.
Transitioning Teams from Guided to Independent
Shilpa Bharti: Makes sense. And taking this one step further, right? Since you’re helping these organizations in your process, you can’t just hand over a framework and walk away. How do you transition from closely guiding teams to then stepping back?
Luca van den Brink: Yeah, that’s actually a good question because on LinkedIn I’ve been a little bit stern in what I’m saying, like, oh, I’m firing clients, or I’m letting go of clients after a while. But it’s a little bit more subtle than that, of course, because in the end I want to help people in organizations do experimentation better. So it’s not like after a certain date, you’re just gonna have to figure it out yourself, because then probably they will just find someone else external.
But what I really want to do is—so we start usually by doing it for companies so they can really experience what it is like to set up an A/B test in a correct way. What are the steps that they need to go through? What are the frameworks they need to have? What are the systems they need to have, routines, behaviors? And once they have seen this for a while, and this already would take like a year or two, then I would really like them to transition to more kind of a “done with you” model. So we will be just watching on the sideline, or we will be there for more data-driven questions or to set up and build a culture, instead of still running the A/B test for them. Because in the end, that’s also what they need to kind of dedicate to, to bring in-house to themselves and also, of course, own that part.
Now of course, organizations are different and sometimes there’s not enough development capacity or UX capacity, and then it makes sense, definitely for a while to have some external resources. But in the end, if a company wants to really dedicate to becoming data-driven and to learning from that as an organization, then I would like them to own experimentation as much as possible.
Common Objections and Building Buy-In
Shilpa Bharti: Got it. Got it. And moving to the next question, when leaders hear the phrase “own experimentation,” it often sounds right in principle, but difficult in practice. What are the first concerns or objections clients usually raise to you?
Luca van den Brink: Yeah, that’s a great question. So we need buy-in and we need all sorts of buy-in from everyone really, from the developers that are going to build the test to the product teams, to especially leadership. So it helps a lot if leadership is on board. So that’s why in the first one, two years, we help organizations set up the systems, you know, really understand and experience how it works and change their way of thinking. So instead of like, wow, this is a great idea. Everyone loves it, we’re gonna execute it now, you know, you change to a mindset of, oh, do we actually have data to support that? Or is this really the most valuable thing for us to do right now?
So in a way, instead of running into one direction really quickly, you’re asking people to be more mindful and intentional by using data most of the time. And people need to experience that. Teams need to experience that, and they need to also see the positive effects of that. So, you know, people get really on board when they see an A/B test win. And when they see what a program can do for them over time. So of course in the end it’s also important to show a positive business case most of the time. So that’s also something we try to do to convince leadership like, Hey, you’ve invested this much money, this is what came out. Now this is not most of the time what we want to be focusing on, right? Because experimentation, A/B testing is much more than just that. But it can help to have more leadership buy-in for sure.
So coming back to your question, we need buy-in. We need everyone on board. And then once everyone is on board, you actually need the people also to take the steps needed in order to follow this process and actually be more mindful and be more intentional with the things they’re doing by using data.
Unlearning Dependency Patterns
Shilpa Bharti: Makes sense. And for many teams, outsourcing experimentation has acted as a safety net over time. Internally, what dependency patterns or habits do teams need to unlearn before they’re truly ready to build experimentation capability in-house? What are your thoughts on that?
Luca van den Brink: So maybe that’s where this piece of ownership comes in. So right now we’re working with a client that’s—I think overall they always have like 10 A/B tests live at all times from different teams. So within the organization there are different product teams and some have three A/B tests live. Some have two A/B tests live. They actually use VWO. So that’s a good credit to you guys.
So they are really owning their process. The product teams, they build experiments, they have thought of everything together with UX researcher and the design team, then actually scoped it, built it, and are then A/B testing with it sometimes in smaller steps or sometimes everything at once. But what is really essential there is the ownership. So sometimes they do still have questions about data. How long should this test run because we have a lot of variance in our data, for example, or how to handle certain conditions. And that’s where we can still guide them into the right direction.
But yeah, once you start to see such a level of ownership, I think that’s really, really good. And you see that the work of experimentation shifts from the daily, oh, I’m gonna run an experiment to empower others to use experimentation to their benefits so that the work you do kind of shifts there.
Building Collaboration and Culture
Shilpa Bharti: Got it. Makes sense. And a quick follow up on that, right. I’ve personally seen my clients also struggle with this specifically, which is experimentation as a culture within the organization, expanding that within different teams. We usually see like one person taking over the entire thing, sometimes handling 14, 15 brands on their own, right? And not having the sort of teams chime in. Do you do some sort of workshops to kind of bring that sort of collaboration? I know you speak a lot about collaboration as well. So do you do those as well?
Luca van den Brink: Definitely. So, you know, once you move away—let’s say we have a client or a company that really starts A/B testing. So first, you know, what you have to do is just all the nitty gritty, setting up the A/B testing platform, doing an AA test, and then start running tests to prove it’s actually helpful for them and to get everyone a little bit on board.
But once you have that, and once you have created a consistent experimentation program, and you run those A/B tests consistently, and you can time and time again prove like, Hey, this is the value. This is what you learned, and you get people on board, that’s also when you need to be even smarter and probably work harder to change culture.
And changing culture is really, really hard because you have to deal with this organism that is an organization. So there are no quick, easy fixes for that. It always depends, whatever you do on the organization, what their problems are. Sometimes it’s about something like having leadership set OKRs or goals for a quarter that involve data driven working or experimentation. That can be one thing. Or sometimes it’s like you say, to involve more people in a workshop and to get everyone on board and to have everyone’s ideas listened to.
So in some organizations you also see that maybe the other end of it—that ideas only come from leadership. So they come from the top and then they go down. But that doesn’t actually give the people working in the teams enough space to solve problems and to solve problems with the knowledge they know. So changing those dynamics can be very hard.
And I think at the very bottom of it all is psychological safety. So that’s probably like a requirement needed actually for A/B testing for people to be able to verify what they’re doing, is it good or bad? And if it’s bad, how do we deal with that? And that kind of needs to be accepted. If we have a failing test, we embrace that and we learn from it, and we are not immediately gonna, you know, speak bad about someone or never listen to that person again or fire that person, you know? So there needs to be—maybe at the base of running A/B tests there needs to be psychological safety as well.
So, you know, there’s many things and there can be many things wrong in an organization and they can be small things to tackle, but they can also be really big things that need a lot of time and effort to address.
Shilpa Bharti: Makes sense. And that’s such an interesting point that you bring up about the psychological safety bit. Because I think that is something we all tend to miss, especially when we are trying to build that sort of culture.
Community Response and Conversations
Shilpa Bharti: Alright. Within the experimentation community, what kinds of conversations has this approach sparked? Have any peer reactions or feedback helped you clarify or refine the model?
Luca van den Brink: Yeah. So I was actually a little bit scared to start saying things like this, like, Hey, you have to stop working with clients, or sometimes I’m also saying CRO agencies can be dangerous. But in the end the response was very positive and especially from, you know, really good CRO experimentation agencies. There was a response that they said like, yeah, of course we try to make ourselves redundant. That’s actually our goal, but at the same time, it always contradicts with, you know, the business side of things and needing to make money.
So I have also seen agencies sticking with clients way too long and just, you know, keeping on supplying them very top level ideas and experiments, which can be great quick wins, but not really integrating with what is this organization actually trying to fix and how can we help them.
So ideally I would want all agencies to say like, Hey, we work with you until this point in time and then we’re gonna help you do it and we’re gonna empower you to own this thing. But of course, I cannot say how other people have to run their business, but it’s definitely something I’m trying, but it’s scary because it means I will also let go of clients or not let go, but you know, you move away from doing everything—design, development—to like a more supporting role, which is very different.
But it’s really something I believe in and, you know, you have to do the things you believe in. So let’s see how this works out. If next year I’m gonna be totally bankrupt, find me again and I’ll come back on all of this. But I think it’s going to be fine because I think companies will also resonate with that. Organizations will resonate with this, and the right organizations will want to bring experimentation in-house.
Impact on Metrics and Accountability
Shilpa Bharti: Absolutely. And when experimentation is owned in-house rather than outsourced, does it change how teams think about metrics—and not just what they track, but how accountable they feel for outcomes?
Luca van den Brink: I mean, in a way, of course if you work at an agency, you’re always trying to make yourself look good. In a way you’re always trying to sell yourself. So maybe that comes into play when you talk about metrics as well. But I would say the biggest change when experimentation is owned versus experimentation is outsourced, is that it empowers teams much more to do their best work. So it empowers designers, developers, product teams to go ahead and verify the ideas they have. And I think that’s the biggest shift for me. Democratizing this whole process of what it is we’re going to do next and having some influence in that process.
But definitely it probably also influences metrics and how accountable they feel, because of course if experimentation is really part of the organization, then I can imagine people feeling much more accountable for that. But on the other hand, having experimentation sit at an agency, that also means they’re investing money, which also creates an interesting dynamic of, okay, we’re investing this money so it’s important. And sometimes that is missing when it’s an internal experimentation program. Then you see that sometimes the dedication to it can be less because there is not that decision made to spend money, for example. So, yeah. Those are the dynamics that I see.
Building Systems vs. Running Isolated Tests
Shilpa Bharti: Got it. Got it. And since The Initial focuses on building systems rather than running isolated tests, where do advanced experiments fit in? What needs to be in place before teams attempt them? And what common pitfalls have you seen when teams jump in too early?
Luca van den Brink: Right. So when you talk about running isolated tests versus building systems, I think what often happens is at the beginning when a company starts experimenting, so, you know, running their first 10 experiments, there is often something very funny happening and most companies think they need to start experimenting with something really big.
So they have this big idea and they wanna experiment with it. So recently I spoke to Alyssa and she was a product owner for Experimentation at Preply, which is like a big language learning platform. I spoke to her for my own podcast, which I’ll be hopefully launching soon. So keep following me on LinkedIn to see more of that. But what I learned from that was that their first test was, for example, a fraud detection system, their first A/B test. That’s a huge thing. That’s not the easiest one.
And then I see that a lot. A client of ours selling photo products, they started with an experiment on a full redesign of their new page. Another client of ours also redid like a full journey and then wanted to experiment to see if it was not harming their brand in any way. So it’s often at the start somehow, it’s the big projects that get leadership buy-in, that gets development capacity and get prioritized on the backlog, and that gets attention in general. Because somehow there is a myth that if it’s big, it must work.
But then, what we also see with experimentation is sometimes the small things can really help. So on the other hand, we have the quick wins, right? The low hanging fruits, things you can experiment with that can have a big impact. And I think in the end, an experimentation program is all of that, but in a balanced way. So all of those really big things, all the small things, and just trying to learn as much as possible in the smartest way.
And to do so, what you need to do is build systems, build habits, build routines in people so it’s not just like, oh, we’ll run an A/B test this year and maybe this month we run another one. But it’s really also in the beginning—it’s like having a new habit, right? So like if you wanna start a diet or start working out, it’s like you need to reinforce that habit and tell yourself, or tell the team, okay, we’re going to run five A/B tests this month and next month again, and we’re going to do that for at least six months to see what the impact of that is.
So you’re not just building one redesign. But what you wanna be building is a good habit and a good habit that creates a data-driven culture and that creates happy people, I think, doing their jobs in a more empowered way.
Tools and Team Readiness
Shilpa Bharti: Makes sense. Alright, and in your view, what should teams expect tools to handle and what kind of tools should they begin with? Where does organizational capability need to take over?
Luca van den Brink: Okay. So yeah, tools are always very interesting and I often make the case if you are just starting out with experimentation and A/B testing, don’t focus too much on the tools, because sometimes it can be a huge distraction for companies. So I actually built like a little A/B test tool advisor where people can go, they can fill in what they need, and then they get sent an email of three testing tools, for example, that would fit their situation. And what I hope is that, you know, companies use the momentum and the motivation they have within their organization to immediately start, you know, demoing tools and get a right tool for them and just implementing that as fast as possible within what is reasonable, of course.
Because the danger is that companies keep on demoing tools. They don’t make a decision and then they end up not A/B testing at all. And then I would rather say just pick any tool, because the most important thing is that you A/B test and later on you can move on to another tool. That’s kind of my standpoint, because it’s just a tool. And of course it’s important to have a tool, but in the end, you know, it’s the people, it’s the dynamics, it’s the system behind it, and that’s gonna make it work, yes or no?
So I would say also the simplest setup for an experimentation program is, you know, having a testing tool, so people can use my tool advisor or, and having a process management tool because it is important to keep track of the process. For example, you have 10 A/B test ideas. Some are in the backlog, some are in the design phase, some might be in development. And you just wanna have like a Kanban board to see where everything’s at, because if you don’t have this overview, it will be just hard for you to manage it. And of course you need to plan whenever your test goes live, and eventually you wanna work towards reaching the maximum velocity of your brand and of your data and running as much experiments as possible.
But yeah, I always say with tools, watch out to not get stuck on it. It’s like you want to go running and first you spend a lot of time and money on buying shoes without ever going running. And then I think it’s probably better to do it the other way around because then once you invest in expensive shoes or an expensive tool, you already have all those great habits that you’ll need to rely on to make it successful.
Shilpa Bharti: Yeah. You’ve put it so rightly with the example that you’ve shared. I’m sure it would make a lot of sense for everybody.
AI’s Role in Experimentation
Shilpa Bharti: When we talk about in-house experimentation model, right? Where does AI add value in helping teams make their own decisions rather than just automating testing and analysis?
Luca van den Brink: I think in part we’re still figuring that out. So like you say, it’s great to save time on analysis and just automate things in general. We’ve been using it as an extra perspective as well. So just to get feedback on your first ideas or on your data or sometimes even how to phrase it in a way that it gets received well, because that’s also a big part of our job, how to translate data and make it stick with someone.
But the thing with AI is that it’s great in suggesting best practices or it’s great in suggesting things that already exist. But if I think about the biggest tests and the biggest impacts in my career that I’ve seen, it would always be a solution that would be very close to the product that usually didn’t exist yet, but also would tie in very neatly with the customer somehow. But those were always solutions that you would never get from best practices. For example, it would be like very custom to the customers, the products, and then sometimes also what we saw in data, et cetera. But that’s something that AI cannot do yet.
So what currently what we’re using it for is to, you know, the busy work to automate that and to just have more time for us to do the actual thinking and to come up with new solutions to problems that maybe don’t exist yet, but will be right for, you know, a brand, a website, an app.
Sustaining Long-Term Ownership
Shilpa Bharti: Makes sense. Awesome. And to wrap up now, what’s one piece of advice you’d give teams to sustain ownership of experimentation over the long term?
Luca van den Brink: Oh, that’s a great question. And you see over time that even if companies years back already run experimentation programs, sometimes something happens like COVID or maybe the leadership team completely changes. And sometimes they start from zero again, and the teams need to have leadership buy-in again, and they need to build their first experimentation program all over again.
And I think in every organization, you’ll see those cycles of this happening. And I’m not sure that you can do anything about that specifically, but I’m always an advocate for starting small. So, you know, even though leadership might have changed or COVID, or something external has changed the way you work or the way the business works, it’s a new chance to start again, to start small. Get evidence for the case of experimentation, why it’s good. An A/B test that works, an A/B test where you learn from, and then slowly get more people on board, do more tests, get more evidence for the case of working data driven.
And then of course also follow a system for that again, so build a system, habits, a process that people can follow, that shifts the mindset and lets people be more intentional by making decisions for their website, their features, whatever they launch. But also know that whenever we talk about systems and processes, that’s great. It’s a great template and we can, you know, hold ourselves accountable to that. But the meaning of those systems is for me to really empower teams and organizations and individuals with experimentation.
So, you know, we do the systems, we build the behaviors, we build a process, we focus on that, but it’s always to empower the individuals who, in the end—the individuals, the teams, organizations. And I believe that that in the end is what makes organizations grow. So not experimentation to get to a hundred A/B tests a year, which is great and which is a great goal, but I believe there should always be something underneath there. Like, we’re going to a hundred A/B tests a year because we really wanna be data driven, or we wanna build this mindset and empower people, et cetera.
So I would say over time, if you work somewhere, I don’t know, more than five years, you will see cycles of whenever experimentation and data driven is kind of more popular or easier, and then it changes again, and you kind of have to ride that wave and see what you can do. It’s always different. I would take it as a challenge and try to solve that as best as possible.
Shilpa Bharti: Makes sense and I think that’s a great advice for life also, especially when you talk about evidence, because I read a slide recently, that whenever you’re in doubt, start building those libraries, those documents of evidences so that you can then look back at it and then be like, okay, you know, I’ve done this before. I can do it at a later stage. I think that same thing applies for anybody who’s starting anything from scratch also, for that matter. So I think that’s a great piece of advice for our listeners.
Final Thoughts
Shilpa Bharti: Just any final thoughts or messages that you’d like to share with our audience before we conclude?
Luca van den Brink: So I think the main message I’m trying to get across is, yes, it’s great if you have someone external or if you have an agency help you bring you to a certain level, because those people, those agencies, people like me, they have a lot of experience and they will get you from A to, well, to experience much faster than when you do it yourself.
But eventually, you know, the aim is probably for you to bring experimentation in-house. So I would say to organizations, always keep in mind that in the end, this is a mindset. This is working data driven, and you’re making a choice as an organization if you want to do this, yes or no. And if you fully commit to this choice, that also means that eventually you wanna bring experimentation or at least, you know, the biggest part of it—you can always have support, you can always have extra development capacity or a consultant giving some advice here and there—but most of it, eventually you will want to bring in-house. And also the most successful experimentation programs I see at companies like, let’s say HelloFresh, Booking.com, Airbnb, they fully own their process.
Rapid Fire Round
Shilpa Bharti: Makes sense. Awesome. We’ve had a fantastic discussion so far, Lucia. It’s time to switch gears and enter our rapid fire round. This is where I put some quick questions your way and I’d love to hear your spontaneous responses. Are you ready?
Luca van den Brink: Yep.
Shilpa Bharti: Awesome. If you were starting a career in CRO today, what is the one thing that you would do differently?
Luca van den Brink: So I would probably try to learn as much as fast as possible. Try to find out better what kind of resources are out there. So I think, you know, there are some courses out there that are so helpful. For example, you have on CXL, Lukas Vermeer’s A/B testing Mastery course. That’s like everything you need to know, it’s more advanced. But if you’re starting, you also have Ruben de Boer’s course on Udemy. And it’s basically everything you need to know, all the basics. So I think that’s a great place to start and then go to trying to bring that to life and trying to experiment really somewhere.
I always thought at first I needed to experiment on a website of the brand I would work for, but I would now recommend like, Hey, just build a WordPress and run an experiment there, even if, you know, you don’t have enough data just to understand the process of how to set it up, how it works, et cetera. So that’s what I would recommend.
Shilpa Bharti: Awesome. One thing your non-industry friends still don’t understand about your job.
Luca van den Brink: They, most people don’t realize they are in the biggest psychological experiments of ever when they go online. And every time I tell them, they’re like, what? And they’re like, mind blown. But then they forget again. So that’s something I always kind of lead with. Like, hey, if you go online to a big website, you’re basically always in an experiment, and that’s something people don’t really understand yet. But I love that it’s part of what I do.
Shilpa Bharti: A person that every CRO professional or product leader must follow?
Luca van den Brink: Ooh, there are so many good people out there. It’s hard to just name one. It’s still very difficult. So I’m thinking, who is posting the most interesting stuff right now? I am really bad at this. Like I want to go to LinkedIn, get some inspiration.
Shilpa Bharti: I think I will say firstly, to all my listeners, we should follow Lucia. She posts great stuff. So that’s something.
Luca van den Brink: Yeah, and I think someone who recently started posting a lot of good stuff is Neil Stoots. He works at Zalando as Product Lead. So that’s a great one. Then we have Maria Louisa, who’s also been in the space for years, and sometimes she posts really, really interesting things. And also I would say I still like Ben Labay’s posts as well, so he posts really oriented to product leads and he comes from a very science backed background.
Shilpa Bharti: Awesome. What’s your go-to travel destination?
Luca van den Brink: Oh, my go-to travel destination. So actually I’m married to a Brazilian, so I often go to Brazil, which is a great place and otherwise I probably would not have that as a main travel destination, but that’s where I go.
Shilpa Bharti: Awesome. One thing that AI will probably take over in the next three years.
Luca van den Brink: I think a lot of busy work, so post test analysis for sure, and also maybe running CRO audits. For some people that has been a big part of their job, but I think if you base yourself out of best practices and data that’s easy to read or easy to understand, I think AI will take that over pretty soon.
Shilpa Bharti: I agree. If not CRO or product growth, what other profession would you have chosen?
Luca van den Brink: Oh, so I’m actually also a writer. I’ve written two literary novels and so that’s also something I really love, but it’s very different.
Shilpa Bharti: Awesome. Do you wanna share that with our viewers and listeners? Where can they find that?
Luca van den Brink: Oh yeah, it’s in Dutch, so that limits the potential readers a little bit. But if they would search for my name on, you know, the biggest book platforms, I even have like audio books and stuff. So that’s all there. But yeah, it’s very separate from the experimentation space.
Shilpa Bharti: Awesome, awesome. One CRO metric that you wish people would stop obsessing over?
Luca van den Brink: Not necessarily one CRO metric, but just using one CRO metric. I think that’s very dangerous. So if you would run an A/B test and only look at conversion rates, it doesn’t tell you the whole story most of the time. Whereas if you also look at add to cart or maybe churn or cancellations afterwards, that gives you much more holistic picture. So I’m very cautious of using one metric only because one metric tells one story, and we actually most of the time need a bigger picture to really understand what’s going on.
Closing
Shilpa Bharti: Yep. Amazing. Awesome. And with that, we will bring today’s episode to a close. Lucia, thank you for joining us and for sharing such thoughtful, real world insights on what it truly takes to build and own experimentation inside teams. It was great having you on the VWO podcast and to everyone listening or watching, thank you for spending time with us. If this episode added value, make sure to subscribe to the VWO podcast and stay tuned for more conversations like this. Thank you so much, Lucia. It is great having you again. I am hoping that we can have you back again whenever possible. I love these conversations. I remember the previous one that I had with you. It’s almost as fresh as it was just yesterday, so it was amazing. Thank you so much.
Luca van den Brink: Okay. Yeah. No worries. Thank you too.
