Two or three years ago, there wasn’t really big data. Two years from now, who knows what they’ll be? Annalect’s Scott Hagedorn talks to TRUE about the need to keep up with the disruption.
Q: How would you characterize big data versus data and analytics? What really qualifies as big data?
Scott Hagedorn: Data and analytics used to be very linear—by channel or by initiative. You’d work within a specific data set and a specific analytics overlay or business intelligence overlay. You could have multiple things that you were analyzing at any given time, but they would give you essentially multiple versions of the truth. You could have a report looking at competitive, a report looking at digital performance, reports on how your search, creative or display are working, but they would be completely independent from what was happening in the marketplace at any moment.
The big data world starts to bring together these pieces of data into one common model. Then, you can run reports, but instead of looking at the competitive spaces or the marketplace, or your performance for digital, search or display, you can now start to look at the bigger picture that contains all of these. Instead of seeing things previously in isolation, you can now see them in an integrated manner, and bring onto one platform.
To earn the name big data, it requires three things: new sources of data; manipulation of that data with a cloud-based processing technology; and bringing together different sets of data that previously didn’t speak the same language.
Q: How have things changed in the past two or three years in attitudes towards big data?
Hagedorn: Two years ago, most companies weren’t really thinking about big data—it’s that recent. I think they were thinking, “Can I put my data into the cloud and make it secure? Do I need to buy all these servers or could I do something that’s more virtual?” We weren’t thinking about what happens when you have unlimited processing power when your data’s in the cloud. I’m sure people were seeing what this change could mean.
The revolution that’s happened over the last couple of years has brought what I consider to be a level of artificial intelligence into marketing where brands are no longer these zombies that are giving you the same message over and over again. The message and the marketing engine itself are becoming self-aware because consumer data and big data are being brought into the actual marketing environment, and that’s what the future looks like. This improves the fidelity pretty highly of whom we’re talking to, making sure we’re in the right conversations with the right people, and that changes the message because if you know who your consumers are, wouldn’t you talk to them like you knew them?
Q: Can you talk about how marketing campaigns are being affected by big data?
Hagedorn: If you looked at a before-and-after of how companies behave relative to marketing, you’d see that for a long time companies operated on what I consider the Y-axis of marketing: You build up your campaign insights; you build your creative, you launch your campaign; you’re in and out of market; and then you read how it performed. That’s what I consider the Y-axis of marketing. That works really well for big tent-pole events or big initiatives when you’re launching something.
But because of the Internet, consumers and customers are always there, always interacting with your brand. It’s not just the spike where they come in and out of market, and so now there is an X-axis of marketing as well. On that X-axis, you have initiatives that are always on—like paid search and like programmatic—where you’re starting to integrate together different data sets and different bidding technologies. I hate to call it a big data revolution, but it’s certainly a technology and data-driven revolution in marketing. Now the X and the Y axes both have to work together. That’s sort of the big before and after. It’s the “always on” nature of marketing, and I think a lot of the clients have embraced that.
Q: So what’s cutting edge in this ‘after’ for marketing?
Hagedorn: Cutting edge to me right now, relative to using data and technology, is the client starting to use their CRM data or their sales data and proactively act on what it tells you. It’s bringing big data sets, customer data sets, into the programmatic environment, and starting to use them to make decisions. Consider the economics of where this is going: I can buy ten video impressions, essentially ten online TV commercials, for the cost of one direct mail piece. Clients are starting to use their data to actually change the course of how they communicate, change the course of how they market. These are the ones on the bleeding edge of it all.
Q: Is there a certain type of client more likely to seek out big date solutions?
Hagedorn: From a sophistication perspective, big data and big data utilization can vary client-by-client. It gets down to how much a client is willing to embrace it. Some of them go so far as to bring on first-party data, like sales and CRM data, to merge with other data sets. But a client in the same vertical with the exact same data could behave 100 percent differently. They may choose not to integrate it, or use it to activate any touch points in the store. Oftentimes, it comes down to whether a company feels it can use technology as a weapon against its competition versus those that only want to figure out storage and make sure they’re not sending out too many emails.
Q: Is big data something that is really just for really big companies?
Hagedorn: Data-driven marketing isn’t just the purview of the Fortune 100. The thing about data and technology and the nature of where things are going, it’s a great level-playing field, and the barriers to entry and experimentation are extremely low. Data has become a bit of a commodity. Again, it’s how we make the data work together that’s actually the trick, that’s the alchemy, but getting your data into place, experimenting with cloud-based technologies, experimenting with off-the-shelf business intelligence platforms, that’s a seat-basis. It’s offered now as a software-as-a-service type offering. And so, the companies that are leaning forward can be really any company, and the barrier to getting in and trying it is super low.
Q: Are the metrics and key performance indicators the same for this new environment?
Hagedorn: The KPIs are essentially the same. Companies and clients always want to make more money. They do that through deepening their relationship with their customer base, by introducing new products, by measuring acquisition and retention. So the KPIs are generally the same. What has changed is the methodology; you’re able to paint a much more detailed picture. Your view is a lot more informed about what’s happening.
Q: At this point, are there customers that even question the need to move onto this next stage of big data even if they can’t do it immediately?
Hagedorn: Oh yes, definitely. For some clients, they don’t think that the juice is worth the squeeze. They think that this is going to be a huge investment in time. They say something like, “I’m not sure what I’m going to get out of it and I don’t really even know how to start. My business is working very well. Thank you very much.” Well, that’s a dangerous point of view to have. Look at a company like Square that virtually came out of nowhere, it has redefined credit card processing. All of a sudden small businesses that used to be cash-only can now compete with the big boys because they’re able to take credit cards on an iPad anywhere. Now we’re talking disruption. You don’t want to be seen as that brand that’s stagnant and not moving forward. Things and sentiment moves too quickly.
Illustration credits: Big Data, homepage (Tim Arbaev via Getty Images); graphs and charts (studiocasper via Getty Images)