DaaS Defined

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Demystifying the fundamentals that marketers need to know about data as a service.

With all the customer data marketers have on hand, do they really need data as a service? Quite possibly, because DaaS isn't about getting more data; it's about having the right data when marketers need it. Still, many marketers are unsure of what DaaS actually is, unapprised of the benefits and drawbacks of using it, and uncertain of how they can find the right vendor to meet their needs. Here's a primer:

What it is

DaaS is a repository of data sources aggregated by a vendor that marketers can shop on-demand through service connections, like the cloud, and pump into their systems to fuel their marketing efforts. Cory Treffiletti, VP of marketing for DaaS platform Oracle Data Cloud, likens a marketer's software-as-a-service (SaaS) platform to a luxury vehicle and DaaS to the gas that powers it.

“In that example, you want to buy the highest octane, most efficient gas so you can maximize the engine in that car—that's the role DaaS plays,” he says.

Why you want it

This model offers marketers numerous benefits. According to Anders Ekman, president of DaaS provider DataMentors, one benefit is that DaaS “makes big data small” by allowing marketers to cut through the clutter and find the data they need. Doing so delivers another benefit: allowing them to go to market faster. Ekman adds that DaaS can lower costs and drive efficiency by helping marketers craft more targeted messages. “You're able to market to fewer and do better,” he says.

Kitty Kolding, CEO of data acquisition agency Infocore, adds that acquiring data from a central repository, such as the cloud, allows marketers to avoid the time and monetary costs associated with implementing, storing, and maintaining their own databases. Plus, she says, it enables marketers to pass on these technological and data processing responsibilities to vendors—freeing up their time to focus on their strategies and messaging.

“The idea is compelling because those costs are real,” she says.

Why you don't

Marketers drawn to those benefits need to tread carefully. Kolding points out that the lure of DaaS is based more on the fantasy of what could be than on reality, and that marketers still have a long way to go before these benefits can come to fruition. “There are a lot of really cool things happening, but the reality of merging all of these data inputs [and] figuring out exactly who you're dealing with…is very, very hard to do,” she says. “I don't yet believe that the technology is up to the task, and I don't believe that the sources of data are in a condition yet that allow a marketer to really synthesize everything that's out there.”

Indeed, there are quite a few DaaS-related challenges that marketers have yet to overcome. One area, perhaps surprisingly, is the limitations of the data on offer. Although DaaS provides marketers with a variety of data, they're limited to the data sources their vendor offers, Kolding says. What's more, she says, marketers aren't buying data as much as they're renting it. After all, once they stop paying for a particular data source, their pipeline is cutoff. “You don't have that data anymore,” she says. “That's the promise and peril.”

Another issue is that DaaS does not guarantee data quality or security, points out George Corugedo, CTO of data management solutions provider RedPoint Global; so, marketers need processes in place to manage these aspects.

“Data as a service isn't going to solve your data quality problem, which is an enormous problem across the board with marketers,” he says. “They often live in a world with very fragmented data. Just because you put it in a data-as-a-service environment, doesn't mean it's integrated.”

What to look for

So, how can marketers determine whether DaaS is right for their organization? And, if so, how can they select the right vendor? Kolding advises marketers to start by identifying what they hope to accomplish through DaaS. Oracle Data Cloud's Treffiletti suggests that marketers follow a three-step construct to better determine their needs and how a vendor's services will meet them: data in, adding value, and data out.

Data in is all about ingesting, organizing, and accessing data, Treffiletti says. To do this, he notes, marketers have to identify which data sets they have and which ones they need, as well as where the incoming data is going to come from, how they're going to store it, and how they're going to use it.

Adding value, he continues, involves connecting the data points, using analytics to derive insight, and establish success metrics. “Many companies offer elements of value, but few are capable of doing all of these,” he notes, “and even fewer can do this accurately and at scale.”

Finally, data out relates to the distribution of data and the ability to transfer it to partners, activate it, and manage the licensing of it, Treffiletti explains.

After marketers complete this three-step vendor review process, he notes, they need to do an internal examination to see if they have the right people and processes in place.

“You need people with analytical skills, but also with a commercial mind-set,” he says. “You need people who can either do or manage the analytics, but are experienced in understanding consumers and revenue-driving requirements. This is a unique combination of skills and ones that are becoming more and more valuable to the marketing organization.”

In fact, Brian Hopkins, VP and principal analyst for Forrester Research, asserts that DaaS isn't enough. It provides the “raw materials,” he says, adding that many providers don't offer the analytics capabilities needed to derive the insight marketers need. “There's this enormous gap between data and action, and just providing data as a service doesn't create the action. It's just data.”

To drive this action, Hopkins recommends that marketers aspire to create a “System of Insights”: a trifecta of people, processes, and technology that work together to access data, leverage analytics and data science to derive insights, test those insights against business outcomes, measure customers' response to those insights, and refine.

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