The Hard Work of Translating Advertising Data into Client Value

Auren Hoffman (CEO of SafeGraph) and Will Lansing (CEO of FICO) are both leaders in understanding what data can tell us and how it can generate business value. They recently published an important article “Why Data Standards Matter”. The article (in no small part because its authors were not afraid to get a little technical) pulls back the curtain on data standards as a key requirement for unlocking the value of ever-growing mountains of data.

In my world, as a co-founder of MightyHive and board member of S4Capital, “data” means advertising and media data, and “value” answers the question, “did my ads work?”

Why Data Literacy Matters

In their article, Auren and Will do important work in educating brands and the market at large on how basic “data building blocks” work. Specifically, their article explains the importance of data joins and join keys—the means by which two or more data sets can be “connected” by a shared set of data values.

Educating clients is critical to helping them get more value from their data. When brands aren’t “data literate,” there is no basis for MightyHive to offer our data-driven solutions.

Data literacy must come first.

Standardizing and Joining Advertising Data

MightyHive has witnessed time and time again, the power of bringing data together. We’re proud to have helped global brands like Bayer, Electrolux, and Mondelēz expand their ability to harness and realize genuine value from advertising and marketing data.

To quote Auren and Will:

“A single dataset on its own has limited value. The real value from data comes from connecting it across multiple disparate datasets.”

This idea of connected data sets being “worth more than the sum of their parts” could not be more true in the world of digital advertising and media. There are myriad data types and sources a brand must link together in order to form a meaningful picture of advertising campaigns; from ad serving and bidstream data, to site and app analytics, to retail point-of-sale. In order to target advertising, measure performance, personalize messaging, and develop insights, brands tap the data of many types of partners including the “Walled Gardens” (e.g., Amazon, Facebook, and Google), media companies, and publishers.

In addition to sourcing data from external partners, brands must build their own first-party data sets. Brands’ first-party data can inform and enable more accurate measurement, superior customer experience, greater agility, and increased efficiency. We have all witnessed the revolution in direct-to-consumer (DTC) models powered by engines of first-party brand data and the stampede toward “digital transformation” that is largely enabled not just by data itself, but by its portability to where it will be most effective, both inside and outside a brand.

New Barriers to the Exchange of Advertising Data

Data is indeed more valuable when it’s linked to other data, but digital advertising is undergoing an upheaval in how data can be exchanged. Until recently, data could be exchanged relatively freely among parties, but data is being increasingly constrained and isolated due to regulations like the GDPR, Walled Gardens with higher walls, and technical changes like Safari ITP that block advertising cookies. This is all for the best, because it is in the public interest and protects individual privacy, but digital advertising must still find a way forward.

Data joins are basically bridges between data sets. In a privacy-first world where respective advertising and media data sets have essentially been isolated on “islands,” even simple data joins can allow multiple data sets to inform and learn from one another again in completely privacy-safe ways.

Why Data Standards Matter to MightyHive and S4Capital

The precise methods and technical considerations around data standardization and data joins can get quite complex, but this is not the point. The point is that:

• We know that data has incredible value in digital advertising and media (after all, without data, digital is nothing but another broadcast channel);
• Brands need to build bridges between data sets (both internally and externally) in order to tap that value;
• S4Capital is strategically focused on helping brands extract value from advertising data, therefore seemingly obscure topics like “data joins” get to the very heart of our approach. In fact, MightyHive recently launched a new Global Data Practice to help brands identify opportunities in and realize value from data.

With advertising data in the middle of a Cambrian Explosion and consumer habits undergoing a digital revolution, significant work and investment are required to answer the question, “Did my ads work?” using data. And before that work and investment can be realistically contemplated, a client must understand the value of data and how to work with it. Abstract data-related concepts can be difficult to articulate and explain, so it helps when S4Capital can point clients to thoughtful and relevant material. We look forward to making our own contributions to this process of education, innovation, and knowledge exchange, and unlocking new opportunities for our clients.

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Christopher Martin is a lifelong entrepreneur and currently the Co-founder and Chief Operating Officer of MightyHive, a global leader in advanced marketing and technology services that deploys and supports enterprise software for real-time, data-driven marketing. He also sits on the executive board of directors for S4 Capital, one of the largest and most successful digital advertising consultancies worldwide.