There is an extremely important element, essential to healthy analytics, that most brands are not doing. The implementation of this strategy leads to efficiencies in budget and spend, delivers a granularity that makes insights worthwhile, saves time, allows for smart optimizations, and works as a gateway to more sophisticated modeling exercises. It’s not sexy, but it is foundational. In many cases, companies are quick to layer on complex technology first. Yet in this blog post, I’ll introduce the solution that I implement for clients, an imperative-yet-basic program that unlocks clarity, cost savings, and revenue.
WHAT IS DATA GOVERNANCE?
Consider a typical brand, engaging in a multi-channel, digital promotion. There are likely multiple ads, all with different copy and creative, running through separate channels (Facebook, Google Adwords, etc.). Data governance comes into play with how the ads themselves are named in the backend. Data governance is the implementation of a proper and consistent nomenclature across all your data elements and marketing platforms; it’s a data dictionary (rules) and a centralized data repository.
Ad attributes such as video length, color, offer message, and more need to be consistently captured across all channels, when applicable. For example, a data rule should be set up that states that an offer message needs to always be in the campaign name, in the second position after an “_” across all media platforms. The data dictionary—the set of rules—creates consistency of attributes in positioning and use which allows teams to deep dive into cross-channel performance.
Then there is the issue of saying the same thing in many ways. By creating a common centralized data repository, duplicative instances of the same thing can be avoided. Consider, too, that in most cases, many people—or vendors—are implementing the ads. For example, there may be cases where the words “national,” “domestic,” and “U.S.” are all used when building the ad. While these terms are all essentially the same in description, they will appear in separate line items of reporting, leading to a considerable volume of post data clean up and a failure for clean performance analysis
WHY DATA GOVERNANCE
Once the clear path for naming and organizing data is implemented, you can have a true cross-channel view of all of the performance related to different channels. For the first time, how an ad performed across all metrics can be assessed, and reports can be created that allow for fresh insights. Because ads are named consistently across channels and platforms, cross-channel attribution becomes much easier. Using this strategy of proper organization removes duplication, cleans up data, creates efficiencies, and reduces time for getting reports. With clean data, campaigns can be better optimized, saving budget and unlocking revenue.
AUTOMATE THE STRUCTURE
When setting out to properly organize the data, all key attributes that will require reporting on need to be defined in a centralized data repository. Then, I recommend creating an automated way of generating ad names that include those key attributes, so that user error is eliminated.
Data governance eradicates the need for translation and report cleanup, while offering an understanding of performance at highly granular levels such as message, offer, creative, geo, demographics, strategy, goal, video length and targeting type. Though seemingly tedious and hardly exciting, data governance proves that strong foundations build great brands.
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