Mobile DMPs nudge their way onto the ad-tech scene
Four new mDMPs hit the market this year as tech companies look to meet the demands of marketers looking to activate their mobile data.
The No. 1 criticism leveled at mobile data-management platforms (mDMPs): Who needs another silo?
But that’s not stopping a growing number of ad tech companies from unveiling mDMPs as they move to meet the demands of marketers looking to activate their mobile data. Although several players have been on the scene for a while now – both Lotame and AdChina added mobile DMPs to their platforms in 2014 – at least four mDMPs hit the market this year. More are surely on the way.
The debate over their usefulness, however, continues.
“The bottom line is that you need to have all of your data assets and all of the various aspects of your digital tech stack centralized to get the best return on your investment,” said Keith Petri, VP of strategic partnerships at IgnitionOne. “And you can’t do that with siloed mobile data.”
David McIninch, VP of marketing at Acquisio, had a somewhat more cynical view of the motivation behind developing an mDMP: “The need for an mDMP is situational. … It’s driven by a need to show immediate ROI on mobile advertising initiatives, and so publishers can build out a revenue model that looks like desktop’s.”
Traditional DMPs typically store, process and analyze cookie-based data from myriad sources – everything from demographics to intent and past purchase history.
But mobile data – app data, in particular – is unique in the ecosystem, said Michael Katz, CEO and co-founder of mParticle, a company that describes itself as a “mobile data automation platform.”
“Apps operate in a browserless environment and browser-based things like pixels and cookies, which are used to capture and distribute data on the web, just don’t work,” Katz said. “There are a number of complexities that are core to native apps.”
And then there’s mobile data’s scale to contend with. Mobile content consumption is increasing every quarter.
Smartphones and tablets combined accounted for 60% of digital media time spent in Q4 2014, according to comScore. As a result, the amount of mobile data is growing exponentially, said Michael Oiknine, CEO of mobile attribution firm Apsalar, which launched its own mDMP product in June.
“Look at all the attribution data you generate just around user acquisition – when you acquired the user, what ads they viewed, where they clicked, which campaign they came from – and then there’s in-app activity, the products a user bought, the products they considered, the SKU, the device type, their physical location,” Oiknine said. “All of that information is key if you’re going to generate intelligence from audience.”
But why couldn’t legacy desktop-focused DMPs add functionality to their existing platform to handle the influx of mobile data? Katz agreed that there’s nothing stopping them – other than time, cash and resources.
“Could traditional DMPs handle data capture through an SDK or an API?” Katz said. “Sure. It’s tough to argue against that one. But have most of them built out all of the tools and controls they need so they can handle all the various mobile-specific use cases? Speaking from our own experience, the answer is no. Can they throw a bunch of resources at it? Of course. But it’s taken us doing nothing other than this for two years to get where we are today.”
And contrary to a common misconception, mobile DMPs are not necessarily mobile-only platforms, Oiknine said.
Apsalar, for example, targets two types of clients with its mDMP: brands that already have a desktop DMP partner and brands that haven’t yet implemented any DMP solution at all.
To handle the first scenario, Apsalar integrated with a variety of different marketing automation companies, including Adobe, Google, Kahuna, Swrve, Appboy, MailChimp and Marketo, among others, so that brands could share data and audiences across platforms.
If a brand doesn’t have a DMP already in place, Apsalar onboards the company’s desktop data, using third-party partnerships with cross-device companies to convert the cookies into device IDs, thereby creating a cross-platform view of the user.
Device IDs in particular are critical for an mDMP to function. But considering Facebook’s guardedness around cross-device data – Facebook recently alerted several mobile measurement partners, including Apsalar, Appsflyer and Kochava, that on Aug. 20 it would cut access to device-level data collection for app install ads – one could argue that mDMPs are at the mercy of the bigger players. If Facebook, Google or Twitter cut access to device IDs, mobile DMPs can’t do much in the mobile targeting department.
But that’s not a particular concern, Oiknine said.
“[They] are more than happy to have their data come back to them as long as the marketer doesn’t see this data in a raw device ID format – we confirmed this with both Facebook and Twitter,” Oiknine said. “For instance, if a marketer acquired an audience via Facebook, Facebook is more than happy to have the marketer retarget part of that audience on Facebook.”
Rather than becoming too focused on the channel, Alistair Goodman, CEO of enterprise location data company Placecast, takes a longer view. In late May, Placecast, which works with large mobile carriers like Telefonica, Three in Europe and Rogers in Canada, made its mobile DMP available as a standalone solution separate from its mobile DSP offering.
In the next 24 to 36 months, an ubiquitous view of consumers across devices will be possible, Goodman said, noting that having the right data management tools will be de rigeur.
And while “mobile and mobile data will play a major role in that, it’s by no means an exclusive role,” he said, pointing to the importance of television, offline and household-level third-party data.
“But I guarantee you that all DMPs are either thinking about creating a mobile DMP or are actually working on something,” Goodman said. “You can’t ignore the shift in media consumption patterns and budget dollars toward mobile.”
Advertisers that neglect mobile as part of their DMP strategy will be burned in the near future, said Neil Sweeney, CEO of JUICE Mobile. Separating online and mobile is “a non-starter” because it prevents brands from successful cross-device targeting and accurate attribution.
While most traditional DMPs do address the mobile web, apps are often left out of the mix. That’s a problem because apps are “a big part of the puzzle here,” said Sweeney, who acknowledged that there are some companies doing a good job of handling app-related data, including Krux and Adobe.
For his part, Krux CEO Tom Chavez has no time for the concept of mDMPs, full stop. They’re simply “dead at design time,” he wrote in an AdExchanger column.
“As your customers move across devices, your platform should let you tailor your interactions with them across any device,” Chavez wrote, somewhat sharply. “Mobile anything is ill posed.”
But there’s no one who disagrees on the significance of mobile data in a cross-platform mix. Perhaps it’s simply the term “mDMP” that grates.
“People are quick to label things in this industry, and if you’re dealing with data, everyone will say that you’re a DMP or a tag management solution or you’re X or you’re Y – but it’s not always that simple,” said mParticle’s Katz. “I don’t know if using the term DMP in the mobile context does these solutions justice. But maybe that’s just what they think investors want to hear.”
Latest from mParticle
Get your flywheel in motion with Data Master
Learn how mParticle's Data Master enables you to increase data quality throughout the customer data pipeline, allowing insights to compound, and making every campaign and product launch better than the last.
GOAT: Lifecycle marketing for scalable growth
Learn how GOAT uses mParticle to streamline their data pipeline and increase Customer Lifetime Value.
mParticle launches new features to help brands create ‘data flywheel’
New features for seamless data quality management, and transformation to serve as a foundation for improved customer experience and better insights.
Better data, better insights, better results: Helping brands create a data flywheel
Introduce total quality management and enforcement into your customer data pipeline with new Data Master features and Calculated Attributes. With Data Master and Calculated Attributes, establishing a source of reliable customer data that will create a customer data flywheel, where the data quality and data’s impact on the product cycle will continuously improve over time.