Insights from Adobe: Leveraging Data and Analytics for Effective Marketing Strategies (Full Transcript)

Speaker 1: like crazy madness. And I think the other one would probably be when I worked for Adobe. So basically, I was working in Adobe heading the marketing strategy. And one, it was amazing, because it was a small team. In Mexico City, we were like 27 people, but with a good budget. So it was like working for a well-funded startup, which was amazing. We have a very competitive landscape, which was kind of hard. But I think I didn't know, I knew the part about the creative side of the business, but I didn't know how much stuff they have on the, what they call the experience cloud. So basically, they have Adobe Analytics, they have CMS, they have all these automation tools. So I think up until this point, I had actually used a lot of technology, but kind of separated or sometimes exporting things and importing here. But I've never realized how important it is to activate up on data. What does this mean? You have some, for example, we're going to touch analytics, which I think is a very important subject here. But it's amazing how many people actually have advanced analytic tools, but they don't act upon them. So they're basically creating these amazing reports, which go and get archived every month. They don't have an area, which is taking this analytics and saying, guys, we have now a lot of people coming from that. Do we actually ship to Germany? Because we like 35% of our traffic comes from Germany. Can we ship to Germany? No. Why not? Why aren't we not doing it? I mean, let's seize the market or how can they understand kind of, I think demographics are not used that much. I think now we're going more towards more like the trends and the type of interests of people, because I think it's now silly. And I would even say stupid to say like, oh, we're having this, for example, I'm going to give an example, football shirts. So you discriminate and say like girls will not be interested. What? Are you kidding me? When Beckham went to the Real Madrid, the most sold t-shirt was by women. So if someone had said, let's not do t-shirts for women in Real Madrid, it would have been a total mistake. So I think right now, I think the data and how you cross this data, how you can kind of cluster. And when you start going into more advanced things, for example, if you're using DMS or a tool that can help you with the data of the people coming in, let's say that you have bicycles, you sell bicycles, right? So you have a sale, you have some discounts, so you can cross the people who actually like bikes, cross it with people who react well to sales or to cheap prices, you cross them and you do a campaign, but then you don't have to spam all of your audience because some people don't actually like bikes. So I think Adobe, and this was a point where I kind of understood like, wow, I mean, and you realize you were doing some stuff that wasn't the best way. And you kind of were thinking like, if I actually have segmented these things in this way, and I could actually have ought upon them in a very specific way, responding these niche markets and really addressing them and talking to them differently and pretty much even showing a website differently to someone like when you, I think when you go to, for example, in some countries, I think Sprint in the U.S. does it. If you come to the website to buy a new phone, it will only show you, it will detect that you have an iPhone 11 and it will not show you anything below it. I think that is smart because you're probably not going to move to an iPhone 8 when you have an iPhone 11. So I think this moment at Adobe was one of these moments where kind of I knew a little bit of analytics. I knew about CMS. I knew about marketing automation. I knew about data management platforms. I knew about a lot of stuff, but I had never seen the importance of really having like an asynchronous system that works and can flow throughout all the thing. Because sometimes you build, you see this, like this kind of like Frankensteins that are built. They have this analytics and then they export them and they have like a flat file and then they push it to somewhere else. But at the end, nothing gets activated upon this analytics. So I think that was the other point. I think working for them really made me understand the importance of choosing the right tools that can help you really automate and act upon the information that you're getting.