Episode 304 / Danilo Tauro / Aperiam / Managing Partner
Breaking Marketing Silos with AI Agents
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In a world drowning in data and technological complexity, Danilo Tauro is offering marketers a lifeline. As a seasoned professional who has worked across multiple sectors - from P&G to Amazon and Uber - he brings a unique perspective on how emerging technologies can transform marketing strategies.
Danilo is currently Managing Partner at Aperiam Ventures, as well as Senior Advisor at McKinsey & Company. Speaking about career development, he emphasises that success isn't just about knowledge, but about building a powerful network. "Knowledge is just a portion of what you need," he explains, "you also need a network... people that support you, that give you opportunity."
As for the future of marketing, the real game-changer is AI agents - intelligent systems that can activate and work across different tools. These aren't just another tech buzzword, but a potential revolution in how marketing workflows are managed. "AI agents are bringing to life a vision that existed 10 years ago, but can become reality today," he argues.
For marketers feeling overwhelmed by the technological landscape, Danilo offers pragmatic advice: start experimenting: "Roll up your sleeves. Start using tools. Start comparing tools.” This hands-on approach is crucial in understanding and leveraging new technologies.
What makes Danilo's insights particularly compelling is his nuanced understanding of both the technological potential and the human elements of innovation. He recognises that successful implementation isn't just about the technology, but about understanding workflows, reducing friction, and creating seamless experiences.
Learn more by tuning in to the full episode.
Transcript
The following gives you a good idea of what was said, but it’s not 100% accurate.
Danilo Tauro 0:00
Start using tools, start comparing tools. Getting your hands dirty is what I would recommend to learn about the space.
Speaker 0:06
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Tom Ollerton 0:45
Hello and welcome to the shiny new object podcast. My name is Tom Ollerton. I'm founder of the ad tech platform, Automated Creative the creative effectiveness platform, and this is a regular podcast about the future of data driven marketing. Every week or so, I have the pleasure and the privilege of interviewing one of our industry's leaders about the future of data driven marketing, and this week is Cannes week. So I'm lucky. I'm here in the boiling heat, not great for a ginger man. I'm in the reception of Martinez hotel, and I'm here with Danilo Tauro, who is managing partner at Aperiam, but also a senior advisor at McKinsey and Company. So Danilo, can you tell the audience a little bit about who you are and what you do?
Danilo Tauro 1:27
Of course, thank you for having me. So I like to say and think that I've seen the advertising industry from many angles, because I've been at P&G. So on the buy side for almost 10 years, I've been at Amazon ads on the tech side, on the product side, for three plus years. I've been at Uber. I was the general manager of Uber Eats advertising. So on the growth side of the industry, and right now, I'm basically on the investing side with Aperiam and with McKinsey as a senior advisor. So like to think that I've seen different angle of our pilot industry.
Tom Ollerton 2:00
Well, the downside of having an impressive pedigree is the expectation of the content on this podcast so very high. But thank you. Thank you for your time. So quick one if you're going to give a smart, driven student some advice in how to get into and succeed in this industry, if they're doing all of the all of the basic stuff, but how did you get ahead?
Danilo Tauro 2:21
Yeah, I think as I became more senior or older, depends on how you want to define it. I think one thing I realised is when I started my career. So I'm sharing this because hopefully that could be interesting for you know, young and motivated people. I was thinking, Okay, if you have knowledge that, what will get you there? But then, as I was progressing through career, I realised that knowledge is just a portion of what you need, but you also need network. You need, basically, as one of your assets, you need a network of people that support you, that give you opportunity, even that you can just pick up the phone and call whenever you need to know and understand something. So what I'm trying to say is, like the two assets I would focus on as a young student are knowledge and network. Because by building those two, I think you get to get a much steeper start with within the industry.
Tom Ollerton 3:14
So acquiring knowledge is more straightforward than it has been in the past. But how do you acquire a network? What's the practical advice for how to do this?
Danilo Tauro 3:23
I remember when I joined P&G, so I'll share a story. The very first training that I took was called the PIE framework, where PIE stands for performance, image and exposure. So that's a training that P&G gives to basically new hires. And the message was to be successful within P&G, you don't need just the first letter, which is the performance the P, but you also need image and exposure. So what does it mean? Image is you need to build a brand for yourself. So make sure that when they think of Danilo or Tom, when they think of yourself, you clearly have a brand. You stand up for something. And then, of course, it's important that the right people know about your brand. So there is the component of exposure. So don't get me wrong, you do need performance, but then image and exposure are equally important. So that was when I really joined P&G, and then as I moved to the US, so 2018 I think the concept of networking and building a network as an asset became even clearer, not just within P&G, but outside of P&G. And somebody recommended me this book, which I I recommend to a student, which is Never Eat Alone by Keith Ferrazzi. And politically, he explains the mechanics of first, why make why networking is important, but also how to do it in a smart way. So, long story short, that was a bit my journey. So from the PIE framework to Never Eat Alone, I think it was really about being intentional, building genuine relationship with people. And so I think that was at the base of how I personally built my own network.
Tom Ollerton 4:58
And if someone isn't going to read, Never Eat Alone. What are the three things to take out from that?
Danilo Tauro 5:04
So maybe I'll go to one, which for me was super interesting when I read it, which is he realised that people that are successful have relationships that support them throughout their career, their life, and so on and so forth. So then he started to realise that actually relationship is so important, as we said, it's an asset. So I started to say, Okay, if I need to get from point A to point B, what are the relationships that can help me get there? And so basically, from there, he would build a relationship Action Plan, which basically what, what he would work on. So I think it was a way to share how to be very intentional about building those relationships that can help you achieve your objectives in life.
Tom Ollerton 5:53
That's really nice. However, coming back to PIE, which is nice and easy to remember, well done P & G, it sounds like it's been written by an extrovert, right? Because someone like me, like I'll cross the room, say, Do you want to come on my podcast? I love meeting people. The more people I meet, the happier I am. I love it. But there's, you know, I've worked with some incredibly talented people who don't want any exposure, they just want to do a good job. So do you think that PIE framework is focused on the neurotypical folk, if you like, or how would that work for someone who would rather die than get exposure to the wrong people? They just want to be brilliant.
Danilo Tauro 6:27
I love this question because I think many people think that I'm an extrovert, but the reality is I'm a big introvert. So what I'm trying to say is, as an introvert, as I learned that PIE is important, then the question is, how do you get yourself to kind of get to know people? And I think there are different ways. Because, of course, you may say, you know, you can step in a room and start to talk to everyone, which is, personally not my style, but there are different ways, like, for example, engaging one to one, getting introduced to people planning in advance. And I think it's very important for introvert to understand that the end goal is building an asset, which is your network, your connections, and then from there, finding ways that feel natural, also to introvert people. So as an introvert, I would truly, you know, recommend considering this, just because it's something that, yes, it's easy to think networking equal an extrovert person, but again it's super important to do it and find ways that feel natural, also for introvert people.
Tom Ollerton 7:30
Beautiful. So gonna move on now, I'm looking for a bit of advice, single bit of advice to make someone be a better data driven marketer.
Danilo Tauro 7:38
Yeah. So I think one thought is today, data driven marketing is also based on tools that can help do data driven marketing, and there are so many tools, sometimes it's overwhelming. I was at the P&G alumni reunion two days ago. We are discussing exactly about this, which is the space is becoming so complex that people don't know where to start. So back to your question. How do you do it? My point is, just roll up your sleeves. Start practising. Start using tools. Start comparing tools. AB test so run pilots. So I think really getting your hands dirty is what I would recommend to basically learn about the space.
Tom Ollerton 8:20
That's such good advice. When you mean AB testing, you think, right, we need a email service provider, so you run trials with three or four of those providers. And what? Why would you say that over just running a pitch, for example?
Danilo Tauro 8:34
Yeah, so I think I'm sure we're all familiar with the concept of almost paralysis by analysis. So the point is, when there is so much out there, we try to build the perfect plan. We try to discuss and litigate options. And I think the point is, you never get to doing stuff. And I think this is actually slowing down the learning and the ability to become a better data driven marketer. So what I'm trying to say is like, really start with this approach of a roadmap of proof of concepts of test to get the learning and the strategy can emerge later on, after I think people really learn hands on what it means to run campaigns, email campaign, paid media campaigns and so on and so forth.
Tom Ollerton 9:24
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Tom Ollerton 10:01
So we're gonna get onto your shiny new object now, which is AI agents. So I think a lot of people listening to this will probably know what that is. But what is an AI agent to you? And why is it your shiny new object?
Danilo Tauro 10:15
Yeah, yeah. I know it's very plain to talk about AI agents today, because everybody is talking about them. But I think the thing that is very relevant for me is like, how do we move from intelligence to activation? So to your question, what is an AI agent? It's an intelligent system that can activate and work across different tools. So if you think chatgpt, so that's intelligence. You ask a question, you get an answer. So that's intelligence, if then you have somebody that is intelligent and can activate tools, for example, through APIs or UIs, and take the output from one tool plugging into another tool, and basically manage a full workflow with different type of operations, in parallel, in series, and so on and so forth. I think that's basically an AI agent team that can basically get can accomplish many different things, and why it's my shiny new object. Because I think we talked about the power of big data, advanced analytics for the last maybe 15 years or 10 years, and I think AI agents are bringing all of this to life, because now finally, you can break the silos across the different systems. You can make sure that things get done at scale fast. You can iterate. So AI agents are basically bringing to life a vision that existed 10 years ago, but can become reality today.
Tom Ollerton 11:39
So give me an example of that working. So conceptually, I get that :disparate data sets, big data, large volumes, and that means teams talking to each other, but you stick an AI agent over the top, and you can say, x, y, z, help me with that, and it pulls together the disparate data sources. So in in your worldview, now, how should data driven marketers be using that?
Danilo Tauro 12:05
Yeah, so let's take, I love the question, because we can take a very specific use case. So if we take, for example, the media supply chain. I call it supply chain because there are specific steps. So you have strategic planning, you have tactical planning, you have buying, you have optimization, you have reporting, you have measurement, you have financial reconciliation. So these are kind of high level the steps of a media supply chain. So then the question is, how can different steps rely on different data sets and different tools? So now the question is, if you need to manage all of this, you can either do it manually, with an agency, you can in house. But these are different people that work on different teams that need to pass data in different ways, ideally in a more digitised way. But sometimes it's like emails and Excel spreadsheet. So what I'm trying to say is like, if you have AI agents that are able to connect the different systems, understand the KPIs, understand the relationship about all of them, and understanding how to optimise the system end to end. The end, they can basically work through APIs or through UIs. My point is you can tell the AI agent what is the expected outcome, and then the AI agent will take care of the full workflow end to end. And this is what Mark Zuckerberg, in one of the latest earning calls, said, Oh, as Facebook meta, you will tell us exactly what you're trying to achieve. We'll take care about the rest. So this is basically what he has in mind.
Tom Ollerton 13:32
So it's an interesting one. So let's go deeper on the Facebook pitch there. I mean, that's that's Facebook saying how great their their black box is, right So, but isn't the advantage really, with agents to pull across different black boxes and different data sets, whereas, if... I didn't see that, but if Mark Zuckerberg said, don't worry about it, we'll take care of it. That should ring alarm bells to most brands.
Danilo Tauro 13:55
Yeah. So I think clarification. So that's the vision. I think, if you ask me from a marketer standpoint. So my recommendation would be to be very clear about who owns inventory and who manages your workflows. So what I'm trying to say is like, if some companies own media inventory and manage the process of allocation of budgets across different channels, there may be basically a conflict of interest, but if you have media owners and separately you have basically people that can manage your planning, your buying, I think you reduce the conflict of interest. So again, the Zuckerberg was an example, but the recommendation would be to have a clear separation between the technology for the planning, the buy and so on and so forth, and the media inventory.
Tom Ollerton 14:43
And so who, for you, is creating the best agents at this point in time, like you described, a very specific use case and a philosophy which I'm on board with. But who's doing that? Are you building those yourselves, or is Have you seen them provided by certain suppliers?
Danilo Tauro 14:59
Some. We at Aperiam, we are not building agents, but we are investing in companies that are actually building AI agents. And I think the secret is invest in companies that build AI agents for or that start at least from very specific use cases, because I think the competitive advantage is not in the underlying technology, which, to be honest, is almost getting commoditized. It's the ability to really understand what's the use case, how to prioritise, how to make sure that the outcomes are good, how to make sure that, basically, the different KPIs you may want to optimise for, like latency, outcome and so on and so forth. You can really optimise for that. So, long story short, we're not building AI agents, but we're investing in companies that are building agents that solve specific marketer problems.
Tom Ollerton 15:50
So an interesting situation I'm seeing at the minute. So I use otter.ai transcribe all my meetings, everything, everything, everything. I love it. I love not having to take notes and have all in one place. But then otter has a chat function in it, right where you say, oh, what you know? What were the main points? What did Danilo have to say? But I didn't write thoseprompts. I didn't write how it responds, whereas what I can do is take that out of otter and put it into chat GPT, where I can build a project and build my own agent, really a meeting, a meeting agent, if you like, but I design that to a degree on top of what chat GPT has built. So how do brands and data driven marketers fight against the situation where there'll be like an agent, an agentic layer over the top that they didn't write. So I'm, I know someone at P&G, and I'm, yeah, I'm using this agent, but I didn't design what's inside that agent. How can I be sure that it's not hallucinating? Like, what's your view on that? Because it is, it's, it's kind of putting a black box on top of a black box.
Danilo Tauro 16:58
Yeah. And I think this is a fantastic point, because the point is, it's important to understand the space to be able to lead, versus being led by technology. I think this is a very important point, because by not understanding the space, things turn into a black box, and then there is no control, there is no governance. There are risks with privacy, with ethics, and so on and so forth. I think understanding the space gives you a chance to turn that black box in something that is much better controlled, where governance is in place. So long story short is knowledge gives you the power to control and avoid the black box effect that you just mentioned.
Tom Ollerton 17:47
So one of the frustrations I have with the industry at the minute is everyone's getting very excited about using AI to do what they were doing before, but faster and cheaper. And there's a lot, there's a lot of people patting themselves on the back, thinking, Oh, I used AI to save myself 20% production efficiency and so on and so forth. But I argue that everyone could do that, everyone can get a licence to and off they go. Whereas I think with AI, the opportunity is to do something you couldn't do before. And what you're talking about here is something we couldn't do before. So I I'm on board with what you're saying. So if someone's listening to this podcast and they're thinking, Danilo is right, how do I get started? What's the what's the entry level move here?
Danilo Tauro 18:30
So one, so two thoughts that I shared before, which is, one, get started. You know, talk to AI agents, company, understand what they're doing, compare them. Try to do some pilots. So really roll up your sleeves and do something. Because I think again, if we start with the strategy, we may lose a lot of time and waste time with this paralysis by analysis. So really get started to understand better. And then the second thought is, before I mentioned the media supply chain, so I called it supply chain. And I think it's very important to understand how things are done today, and categorise all the different steps, the sequencing and so on and so forth, because that supply chain mindset is, I think, a great fit for AI agents, because it's very important to understand not just the technology, but also how to structure, connect, integrate and synchronise the different agents. Now, people talk about synthetic teams, so humans and agents. So having an understanding which is supply chain oriented, I think it's very important. So that will be the combination I'd recommend to get started.
Tom Ollerton 19:36
And then, what is your advice to suppliers that are feeding into those agent systems. So say, for example, in that media supply chain, you've got a you know, you talk about measurement, so optimization, you talked about deployment and so on and so forth. They all speak different languages, and they all output their data via an API in or not even in an API, might be decks or spreadsheets or whatever it is, they're they're all going to talk their language, right? You know, because as a supplier, we have our language that distinguishes ourselves from other ad tech providers, right? But that's kind of a blessing and a curse, in a sense, because our output, our language, our words, our our acronyms, are different to everyone else's. So what's your advice to people in that supply chain to make sure that what's coming out of their system is congruent with everything else that's needed?
Danilo Tauro 20:28
Yeah, so I think this is an important point, and it goes back for me to the concept of orchestration. So I think right now that systems are more complex and more interconnected, I think it's going to be very important for every single player within those supply chains, which could be a media supply chain, a creative supply chain, would be very important to understand how to interact with all the other systems, how to make sure that the data have the right taxonomy, the right schema, they're readable, they're understandable, because if not, they're going to be left behind just because the different systems that we need to get input, we prefer to work with other systems. So. Long story short, if before as an entrepreneur, there was a focus almost single minded on your technology and the problem you're solving, I think now it's also important to understand how you fit the broader ecosystem to create an experience which is frictionless for the end customer, which is the buyer, which is the brand.
Tom Ollerton 21:27
So we're coming to the end of the podcast now, unfortunately, but if someone wants to get in touch with you to discuss agents or anything else we've talked about today, where's a good place to do that and what makes a message that you'll respond to?
Danilo Tauro 21:40
I'm very active on LinkedIn, so I love to get to know new people through LinkedIn. So please feel free to reach out and yeah, super passionate about anything advertising technology, marketing technology, AI is a big investment thesis for us at vaperium. So anything that is ad tech, martech with AI in it, I think I would love to learn more.
Tom Ollerton 22:02
Brilliant. Thanks so much for your time.
Danilo Tauro 22:04
Thank you,Tom.
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