"Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by John Lee, executive vice president at Merkle.
For many marketers, it makes perfect sense: the idea of using data to craft a personalized experience that’s suited to a consumer’s motivations and context and delivered seamlessly across channels and devices. The secret sauce that everyone is discussing is data, particularly advertisers’ own data sitting in their CRM databases.
The idea is simple. If Geico has a predictive model that scores the US population to identify the 5 million people most likely to switch auto carriers, it should be able to pull a file with personally identifiable information, onboard it into a data-management platform or Facebook and engage those people with great results. Sounds simple enough, right?
The potential upside is huge: In the telecommunications industry, for example, the use of CRM data resulted in online campaigns that were 39 times more effective, according to Neustar.
In reality, we are seeing very little use of first-party, known consumer data in today’s performance media programs. As it turns out, leveraging this data is harder to pull off in a meaningful way at scale than most people think.
Intuitively, you would think it involves little more than having your IT department or database provider pull a file of recent converters, push it into a custom audience platform application programming interface, such as Facebook, and allow the platform’s lookalike algorithm to do the rest.
In truth, this can be done as a one-off test, and it happens often. But beyond an interesting test, it rarely scales into a first-party data asset that impacts significant marketing spending. And rarely does it become something the CMO and CFO really focus on. There are three primary reasons for this that marketers must address.
The first reason is that using first-party data at scale requires a completely new planning and execution approach that is people-based, rather than placement-based. The term “people” is used here because I am talking specifically about building the media plan around utilization of individual, known consumer data flowing out of the CRM database, not buying third-party audiences and not retargeting consumers who were cookied on the site.
This people-based planning and execution approach looks way more like the database marketing process that features predictive modeling, segmentation and campaign management than it does the typical digital media plan. One major implication of this is that we are accounting for a testing approach to engaging consumers over time and across platforms. In this mode, that one-off Facebook test would be just one cell in a massive people-based marketing test matrix that spans the whole year.
The second reason is highly related to the first, which is that the skills needed to actually pull this off are fractured between the traditional database marketing/ analytics and digital marketing functions. It is extremely rare to find these two functions in one place, integrated into a people-based planning and execution operating model as described above.
The database-marketing people with the skills to manage the CRM data and build the campaigns don’t know anything about digital media, while the digital media folks who understand programmatic buying and optimization don’t know anything about CRM. But without the integration of these functions and the training of leaders who truly understand both worlds, using first-party data as an asset is nearly impossible.
The third reason is the technology. Again, in a one-off test, we can manually get a CRM file pulled, hashed and uploaded into an addressable platform. It’s messy but can be done. Now try to take that single test cell and explode it out into a thousand cells. Good luck.
When the marketer turns to the existing technology stack for answers on how to automate all of this, the story gets very complex. The platform required to deal with this is an integrated marketing technology stack that allows a known consumer record to flow from the database through analytics, anonymized and orchestrated, out to multiple platforms and back to the database to close the loop.
The problem is that the capabilities needed to do this are siloed in the CRM, site and ad tech stacks. Without integration of the data and workflows inherent in the various tools, there simply is no way to scale the use of first-party data.
The good news in all of this is that the data, skills, tools and audience platforms required for this to work all exist today. But to get beyond the rhetoric, advertisers need to stop minimizing the challenge associated with truly monetizing their first-party data.