▶️ Listen now on Apple, Spotify, and YouTube
This week Juan and Scott take a philosophical discussion on the role of data in business. Data-driven obsession is influencing spending on cloud platforms that are forecasted to reach more than $1 trillion in spending by 2026, but privacy and security problems are changing perspectives on the value and liabilities of data collection. Juan and Scott also touch on metaverse spending and VR hardware, Martech stack reviews, generative AI, and cloud innovation. Let's dive in.
In another BIG week in Martech:
🗞️ The Headlines
- Metaverse movements: Bytedance announces a new VR headset competitor to Oculus, and more than $70 billion in spending from Meta on the metaverse.
- Martech stack reviews: A new study from Gartner suggests that Martech platform reviews are happening more frequently than we thought.
💁♂️ The Big Chat
What is data: Most people use the analogy of oil or sand for data in their business - a resource that should be extracted, refined, and used to create value. But the problem with data is that when it is used to invade our privacy, or when bad actors breach and steal it, then the concept of "data as oil" doesn't really work. What are some better ways to think about data in business? Read the full transcript below.
⚡The Shoutouts
- Scott's exploration into generative AI: DALL E 2 is now open to the public, what does this mean for the creative industry?
- The cloud is eating up Martech: An essay from Miles Younger on the ongoing trend of cloud data warehouse platforms adding features, products, and services in the Adtech and Martech industry.
▶️ Listen now on Apple, Spotify, and YouTube
📚 Talked About On The Show
Rita Liao
Martin Peers
Juan Mendoza
Kyle Wiggers
Myles Younger
📖 Read The Show: What is data?
Scott: What's our big chat topic for this week?
Juan: I have got an interesting concept. For The MarTech Weekly, I did this essay on the whole idea of how marketing technologists understand data - the role it plays in their business the role it plays in society, the role it plays to them personally, and even how they plan their careers around data.
And, you know, the whole concept and idea of data, I think is one thing that defines our entire industry. I mean you've been working quite a bit, Scott, over the years on the concept of Big Data, and you talk about Big Data needs big Ops, and you've probably seen this whole world change in terms of how brands understand the role of data in their own businesses.
On being data driven
But I wanted to take a step back and think, what are the ways in which you can think about data that are obvious, what are the ways that are not so obvious?
There's a chart in that newsletter that talks about Google trends and the searches for the concept of being data-driven. As you can see, the idea has had major traction in the industry. Everyone uses it.
Now, if I said to you, Scott, what is being data-driven? What would you say to that? How would you answer that question?
Scott: Well, my joke is data-driven means you drive around until you find the data that proves the point you wanted to make in the first place. That's the wrong use of the word, data-driven.
No, I mean, everyone's looking for objective evidence of what should we do and is what we're doing actually working? And that's kind of what people think of when they think data-driven.
Juan: And I would agree with that. I mean, there's the funny aspect of driving around to find the right data point that proves your point, But the idea of being data-driven is really interesting in that if you look at companies like Amazon I mean, that is a company that you would probably say they're very data-driven.
If you talk to people working, say in marketing or tech and product at Amazon, Everything needs a data point. Everything needs rational, objective evidence for whatever decision they're making. And so, data-driven is this whole concept of, well, what does the data say about this situation that we are in?
Or what does the data say about this decision that we need to make? What is a key insight to guide our decisions? Now, I actually asked a question in the essay, 0 we've been thinking about being data-driven for a long time, but where is it actually driving us? And I think one of those aspects in which being data-driven is driving us is that it's actually leading us to hoard and collect more data than ever.
The age of data hoarding
So there's some great research from a number of different resources around this topic, but the amount of spending that is going into just cloud platforms and cold data storage in particular is absolutely exploding. The IDC did a great piece on this to say, well, in 2022 there's about 706 billion being spent on cloud and cloud storage, and they forecast that by 2025 it's going to be a 1.3 trillion industry.
So that's going to double almost in terms of the amount of spending that's going into just the cloud, and a lot of platforms are saying things like "you should be collecting as much data as possible." I mean, we see data collection as almost like an insurance policy in a way. Collect as much data as possible because you never know when you're gonna need it.
You never know when you may have a use case for it or analytics you may need to pull up. So just collect it all right now and then figure that out later. But I think that's led to data obsession. I think we've kind of created this culture where we've become so obsessed with data.
Data is not oil
The main sort of meme or the idea for data that most people have in their minds is data is oil or data is sand like it's a resource. You extract it from the earth, you refine it, you manipulate it, and then it turns into something valuable like gas or a sheet of glass. So the thinking behind this is that data is a raw resource that we extract for value.
And what I argue in the essay is not necessarily that it's wrong. I think it's very true that data is everywhere and getting value out of it is important. That makes sense. But there are other elements to it as well. One aspect is security and privacy. So here in Australia, we've had a bunch of news come that Optus, one of our biggest telecommunications providers actually suffered a data breach. Almost 10 million customer records have been breached, and that has caused a lot of noise and discussion in the industry about, well, why was Optus collecting all this personal data, like passport numbers and credit card numbers in the first place?
Privacy is changing our concepts for data
Do they need to store all of that really? Do they need all that data? And I think that's one of the main points here is that privacy and security are changing how we think about the role of data in our businesses, it's not just oil. It's not just value, It's also a danger as well. It's risky. I'd say that there's a bunch of stuff to unpack there, but, looking broadly across the industry, there's not just the example there with Australia with Optus, but there's also Sephora.
And we mentioned before about Sephora being fined more than a million dollars for sending customer data to ad platforms. You have the ICCL, which is taking Oracle to court for the BlueKai data network for advertising saying that Oracle has so much data, it's a violation of privacy.
And then you have TikTok where you had Scott Galloway come up to say that TikTok should be banned full stop because of their data practices and where that data is being stored.
And so, Privacy's changing how we think about data because it's not just oil in that example. When a database is breached and data is stolen that impacts real people.
And so my thesis in this article is all about, well, we, maybe data is more about us. Data is about people. It's about what we learn and know about people. And we should treat data just as carefully as we would treat people like your employees or your staff or your customers. With that much care and that much sensitivity Because data is us in a lot of ways.
I mean, my passport number, my bank account details, all those, that information, all of that leads to, well, who I am as a person, where I shop, where I go. So that's a big takeaway here is that data is us, and I think we need a better mental model.
A better model for the concept of data
So the four areas I would say around data that are often neglected are knowledge - analytics, insight, Growth, which is focused on revenue or driving use cases, advertising, and marketing. Safety includes security, crime prevention, and then also service, looking at how, okay, how do we actually serve customers through data?
But I think the safety one has been the one that's been the most neglected because if you think about it, data makes customers safe. If I sign up for something and I give my bank account details or my credit card number to a company, They collect data on that, but also they need to keep is secure.
What are your thoughts? How do you approach this whole concept of data in business, Scott?
Scott: Yeah, I thought that was a brilliant essay. I really enjoyed it. You know, it struck me when I read it that data's one of the few things that is both an asset and a liability, right? It's an asset for what we potentially can get out of it and it is a liability for the risk it poses from a security perspective.
The data superposition
Frankly, it's also a liability from the volume side. In theory, the data we want is more likely to be in there, but the more data we have, the ability to actually find the data we want becomes harder.
And you know, since we're on the philosophical topic it's like like the quantum mechanics question of Schrodinger's cat - is the cat alive or dead? You don't know until you open the box. It's in that state of quantum superposition. It's kind of like, well, data's like that too.
Is this data an asset or a liability? Well, you won't really know until you either get some specific value out of it or something bad happens with it. So I don't know if there's an answer to this somewhere, but I agree it is probably at the center of, this modern business challenge.
And I think this is the reason why we've talked about this before. I'm sure we're gonna talk about it more. Yeah. This is probably the biggest innovation that's happening in MarTech right now. This is happening at the data layer and the data ops layer because this thing is just getting larger and we do not have it under control at this point.
Juan: Yeah, it's, I think Schrodinger's cat is good example here because data is very ephemeral. I mean, like data, you can't hold data in your hands in the way that we are talking about it Here, it's a, it's a row in a spreadsheet. You see it on a screen, but it's not like oil. Oil is a physical reality. You can get petro and put in your car, but data, I think, is epistemologically challenging, like to even just think about it - we've been collecting all this data and sure we know what it is, but what does it actually do in the business? A lot of marketing teams are even just trying to grapple with what data they even have in their companies.
I mean, that's one of the biggest challenges is just figuring out what we've got. And I think there's the Optus breach of their data systems is a real wake-up call. I call it Chernobyl moment. Where, with Chernobyl, the power plant had exploded and it caused nuclear fallout across Europe and that changed the entire nuclear industry.
All of a sudden, no countries wanted nuclear power plants because of this major thing that happened. And I look at the Optus data breach, and there are many, many others and at a way larger scale. But you think about it, you're like, well, Is there a Chernobyl moment here to say, well, yeah, well, is data something that is, should be protected?
You know, should it be something that needs licensing to actually access and use? I mean, we are still in the very early stage in terms of how we think about data, but I wanted to throw some thoughts out there and see what people think. I think there's, a lot there that we still need to explore around what we actually think about data and its role in our business.