Not too long ago, ad tech was the darling of the digerati. But while programmatic trends like header bidding continue to gain footing, it’s marketing technology—or mar tech—that’s become the hottest buzzword for brands and agencies alike. Capital investment in mar tech was predicted to total a whopping $2 billion in 2016, according to PitchBook, a firm specializing in venture capital and private equity data. As mar tech takes over, it might seem like a no-brainer for industry types to be fluent in the basics. However, a lot of “mar tech 101”-style questions continue to pop up when potential clients talk with firms big and small.
“The questions we get from clients tend to still be pretty basic,” said Ric Elert, president of personalized digital marketing agency Conversant. “I get the sense that some brands feel that what we do is smoke and mirrors because it’s technology. It’s artificial, unlike a billboard or TV ad.”
Likewise, many clients are still skeptical of the increasingly prominent role mar tech plays. “A lot of the ‘marketing cloud’ solutions have been touting that they can connect with consumers across the entire customer journey and can help brands deliver on the promise of personalization,” said Seth Garske, executive director of marketing science, analytics and targeting at HackerAgency. “But I still haven’t seen many marketers pull this off.”
When it comes to knowing what works and what doesn’t, understanding how all the pieces of the mar-tech puzzle fit together is key.
“[Mar-tech companies] all try to sell you their gear, like selling you a kitchen,” explained Steven Moy, evp, chief technology officer at R/GA. “[But] the only way you can make good food is by buying the right ingredients.”
To help mar-tech newbies figure out just what those right ingredients are, Adweek asked agencies and major mar-tech companies to share the questions they get most often from current and potential clients.
What’s the difference between mar tech and ad tech?
While they can overlap, marketing and advertising technologies chiefly serve two separate purposes. Ad tech focuses on the delivery of creative and communication of actual ads (programmatic or otherwise), while mar tech is more holistically about loyalty and one-to-one customer relationships. Think about it as short tail versus long tail, Moy said. “[Mar tech] is not one size fits all, it’s not a silver bullet, but a lot of marketing technology can be a vehicle for you to test and learn,” he said.
What’s a marketing cloud?
While being “in the cloud” is becoming about as common as spring rain, it has a different meaning in the marketing industry than just digital storage. A marketing cloud—such as those used by Salesforce, Adobe, Oracle and others—is a suite of software that helps with email marketing, advertising and other services. Ideally, a marketing cloud helps connect data and services across platforms to focus on various types of business objectives rather than one that’s too focused on one channel or device. For example, Adobe recently began using its Analytics Cloud to offer voice analytics, while Zeta super-charged its own cloud with machine learning through an acquisition of Boomtrain.
What’s a DMP?
There are a lot of acronyms that get thrown around in ad tech and mar tech, but one of the most common is DMP, which stands for data management platform. A DMP is a type of software that performs three main tasks. First, it captures data from sources such as web traffic, online ads, points of sale, beacons and apps. Then, it takes the data back to a centralized place where it is attached to users’ anonymous online identities. Finally, the DMP makes that information available for marketers to use. (For example, brands can track the DMP-enhanced user profiles to see when a person who views an ad browses a website or performs some other activity.) Companies running DMPs include The Trade Desk, Neustar and Rocket Fuel.
Is AI actually important for marketing?
Artificial intelligence might seem like it’s still a budding trend—because it (mostly) is. However, it’s also already transforming the way marketers use data through analysis, media buying and other tasks. Along with helping humans more efficiently perform tasks, AI is connecting the dots within vast realms of data larger than the human mind can comprehend. “Think of natural language processing powering things like Alexa or Siri, machine learning powering Google or Amazon recommendations, and Facebook and some ad tech leveraging deep learning to power face recognition in imagery,” explained Chris Jacob, director of product marketing for Salesforce’s Marketing Cloud.
What goes into a user profile for personalization?
While there are hundreds (or even thousands) of data signals that can go into a single user profile, creating one involves painting a pixelated picture of a consumer in a way that protects their identity to maintain anonymity while also being detailed enough to ensure the profile is relevant. That means adding context through data related to purchase history, loyalty and other past references and interactions. “Context is as nuanced in digital environments as it is in physical interactions,” said Steve Hammond, a senior director of customer success and product strategy for Adobe’s Experience Cloud. “It requires historical data, as well as current, last millisecond data that describes the situation. Additionally, profiles must be globally accessible and contextual. And they need to be fresh and scalable for real-time decision making.”
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