“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 Elmar Mamedov, vice president of engineering and analytics at Thinknear.
With the walled gardens of Google and Facebook attracting up to 85% of the new advertising dollars entering the digital space, the rest of the ad industry has been building competitive advantage on the cornerstones of data-sharing co-ops, partnerships and collectives.
The strategy is formidable in theory, allowing ad platforms to offer better audience insights, more cost-effective media buys and scalable, cohesive attribution through pooled customer data. But in practice, the industry has struggled to generate tangible results beyond a handful of one-off partnerships that fail to make a dent in the long-term market share enjoyed by the industry’s two digital giants.
The gap between Google and Facebook and the rest of the ad industry has nothing to do with inferior technology; it is thanks to the lack of data at scale for those not connected to the Google and Facebook ecosystem. What’s holding many companies back is a fear of taking the steps required to strategize collectively on combating this disadvantage. From executive leaders on down, these organizations are wary of embracing the data alliances needed to combine their resources and create a stronger data offering on par with the big players.
These alliances may go against the grain of the competitive mindset that many executive leaders prefer, but in an industry dominated by two tech giants, a radical approach is needed. In this battle for advertising dollars, it’s possible to fight data with data. The key is building a strategy that can help companies execute this plan.
Opening Up Data Without Giving Up A Competitive Edge
Brands may be doing this under the assumption that they’re protecting sensitive data, but in reality, they’re hurting their own ability to analyze ad performance and understand the ROI of their campaigns.
Meanwhile, brands are also operating advertising campaigns across multiple platforms at the same time. While this serves the critical purpose of testing campaigns to measure performance and ROI, it also creates dissonance within a brand’s entire marketing ecosystem, since different campaigns may be isolated. Too often, they aren’t talking to one another through the company’s data-sharing setup, which leaves brands unable to follow their own data through different channels. The end result is an overall marketing picture that is stitched together from many disconnected sources.
The impulse to protect proprietary data isn’t always bad: There are instances where first-party data is better kept secret than shared with others. But by sharing some proprietary data with other data partners, smaller retailers, for example, can finally operate at industry-level scale and close the gap that’s separating those walled gardens from the rest of the retail field.
In their efforts to compete with retail giants like Amazon, for instance, many companies hoard their proprietary data to maintain what they see as a key competitive advantage. In reality, this is a losing strategy that inadvertently plays into Amazon’s hands. By isolating data and avoiding data-sharing opportunities, retailers can’t leverage data at scale. This smaller pool of information is far less valuable than the data larger competitors can access, and it puts data-limited retailers at a stark disadvantage.
Imagine major retail brands such as Macy’s, Nieman Marcus and Kohl’s coming together to share their own data. While these major retailers compete with one another for business, none have the volume of customers to operate at scale with their data. But by coming together to share some proprietary data, they can paint a better and more meaningful picture of the customer journey and leverage this data to improve their own respective strategies.
Leveraging Media Partners to Develop A Unified Data Strategy
Attribution models can’t be created in isolation. Even a single-source attribution model requires data to be shared between multiple organizations. Effective advertising depends on high-quality data to serve the right ad in the right context, but this isn’t the extent of data’s value: It can also help build a cohesive, scalable attribution product or a better probabilistic product when the scale of the campaign is large enough.
Strategic media partnerships play a central role in this process. Companies can partner with MasterCard, for example, to gain access to purchase data, which can be used to create new products to improve marketing and advertising strategies. These data alliances are ultimately leveraged to create new data-driven opportunities.
But these relationships aren’t enough to compete with the walled gardens. To clear that hurdle, organizations must come together and pool their data to create something more valuable than the sum of its parts. These partnerships can be hard for some to embrace, especially when potential partners are the competition, but there are ways to ensure each brand is protected.
This data-sharing can be managed through a third party that functions as an independent party, guaranteeing that the data is being shared as intended.
Executive leaders have long been trained to believe that their first-party data must be protected at all costs. But to beat the giants at their own advertising game, brands have no choice but to embrace a new data-sharing economy. Without a more cooperative approach that crosses company lines, data owners will never be able to drive the kind of ROI they deserve.
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