Hi, I'm Alban Gérôme, I'm French, and I work for Legal & General, which is the largest insurance company in the UK. And I'm based in Wales, which is west of Great Britain. I've been working in analytics for 13 -14 years now. I was originally a linguist, I studied languages at university. Became a web developer. From web development I went data base plumming, then after that I became a web analyst working with IT implementation. I use tag management and automated testing tools. So the reason why I come to MeasureCamp generally is mostly for the people. So, I use a very special stack for which may not be a session for me at MeasureCamp Copenhagen or anywhere. So for me just to meet new people and catch up with people I know. I've known Steen for example for many years, but a lot of people here at MeasureCamp, as well. So, it's mostly for that for me: the people and building relationships, expanding my network as well potentially. And we might have a conversation with another and then you might give me an idea and I give you an idea about something else I haven't thought of. you just try to increase the serendipity of things and be happy with lucky random concessions that you might have won over that help both sides of discussion. At Legal & General right now we're about to start implementing a CDP, a customer data we're about to start implementing a CDP, a customer data platform. So try to bring all the data we have in house to build that single customer view and try to personalize the experience. I hope we can have bigger profits from that, but also help the customers and find what's the best products for them as well. So that's one of them. And then the second one is more like focusing on technological debts. So we have a lot of code. We have managed a tag management system, which was written years ago. Coming from a web analytics background. I look at the code and I just go like... who wrote this. There's no indication on the code and maybe it is very verbal. It could be more compact and faster and easier to maintain going forward. So for me, personally, my second thing I would look at. And the third thing is that we use Adobe Analytics as our main product we're looking into soon we have to migrate to server-side tagging to build a proof of concept based on that, leveraging the API's as well for the different tools we use. We use Adobe Launch as our tag management system for example, we try to leverage a lot of that kind of stuff. So API's and server-side tagging would be the third thing I look at. Yeah. That's something I've been talking about at MeasureCamp Amsterdam and also at MeasureCamp London this year. It seems that in our field we believe that data-driven is the solution to every problem we have, but actually I think it can be super dangerous as well. And that's what I'm going to talk about this afternoon, as well. Giving examples from history where some policies were, in my mind, very data-driven but that backfired horribly and that led to a worse outcome but what people were started with. So just a quick teaser for my session maybe. It's how towards the end of the 18th century in India and the start of the 19th-20th century in Hanoi. So, we had both problems where the government tried to tackle rats and snakes but given monetary incentives to capture those. And that led people to cheat, the entire program backfired. So when Peter Drucker said that øyou can't improve what you can't measure'. It's not by him, but it's claimed to be by him. There are a lot of things that are important, but we can't track. There are things that we can't track, but are not as important. So there's a tendency where we see that just because you can measure and we can improve it and it's important, but not necessarily the case. And if you try to have the wrong incentives it can backfire a lot. And kind of tied to that as well as a rule of emotions and decision-making, as well. We seem to think that, you know, emotions are bad, they model the field model of the data that we work with. But actually neurosciences say something different. They said that actually without emotions you can't make a decision, all options look equal without emotions. That's what makes the balance tilt in favor of one option or another. So I think we should reconsider all emotions and realize that is not the best thing in the world. We need to have a better balance of emotions and hard data, but also add judgment. Judgment and good feelings drive decisions, as well. So I think that all that is something that we're talking about this afternoon. So where the market is going. It's kind of the media, so, well what we've seen in the last couple of years with ITP tracking prevention. So there's a stronger... people are beginning to become more conscious about their online presence and the kind of data that is behind and what companies do with our data. So it's, I think we're going to see that more and more going forward. Although the last couple of years we haven't seen a big push from Apple in particular. We reached a plateau in a way, but let's hope it stays like that because it's creating a lot of headaches for people like me working with tagging, for example, where we have to reengineer our solutions trying to find other ways of getting consent or trying to make a big case why we need the consent that we give in return to customers without consent, but we see Brave browser, for example, that's increasing in market share all the time. And that's what I use on my personal phone and at home as well. So I don't get tracked at all. I can watch YouTube without any ads any more. Without having to pay a penny for it just because they use Brave and blocks all the ads. So it's hard to make a case for why we need it from customers. But again, I think it should be a give and take where I see what's the need for them. I want to give you data. It's not just a matter of giving them a very personalized experience, but we feel like some insurance to try to understand what are the best products for them. How can we really understand what we need put the right products in front of it, I guess.