Audience Data, Digital Advertising

Why Data Quality Matters - Part One

By: Eyeota

As we progress towards the end of what has been a tumultuous year for everyone, brand marketers, media owners and platform providers continue to grapple with the issue of data quality in digital advertising. While some issues in the supplier-buyer chain remain the same, new challenges are always emerging.

Eyeota recently brought together a panel of experts from across the industry to discuss how they are working together to address multiple challenges to enable brands to build trusted consumer relationships using quality data sets from multiple sources.


The panelists were:

Kristina Prokop, Co-founder and CEO, Eyeota

Timur Yarnnall, Co-founder and CEO, Neutronian

Jene Elzie, Chief Growth Officer, Athletes First Partners

Michael Gorman, SVP Product, Business Development & Marketing, Share This

In the first session, the panel discusses what we mean by “data quality”. The second session looks at the importance of data quality in a changing world. And the final session takes a glimpse into the future. 

Session one: How should we judge and grade data quality?

While there are significant challenges, the industry continues to strive for greater transparency across the supply chain to build trust between consumers, advertisers, publishers, and ad-tech vendors. Savvy marketers demand high-quality data to deliver carefully targeted digital advertising, support the construction of compelling insights and the creation of deep customer relationships that drive business success. Nevertheless, a standardized approach to measuring data quality remains some way off.

Perhaps the best analogy of the present situation is that of walking into a supermarket where none of the packaging has any food standards labelling. You must buy the food and cook it before knowing whether it’s good or bad for you!

Added to that, data quality includes numerous factors like accuracy, precision, completeness, reliability, timeliness, and consistency. And of course, data quality means different things to different marketers. But with sources becoming larger and wider than ever before, the importance of establishing some fundamental definitions is crucial to create and maintain trust across the ecosystem. Marketers must evaluate the quality of the data that is leveraged for their own decision making.

Standardization of terminology

Certainly, transparency, reliability and accuracy were already dominant factors. But as the industry moves towards ever more granular forms of targeting and measurement, while combining different data sets, the need for assurance that the information represents what it purports to represent is more critical than ever.

Before joining sports marketing agency Athletes First Partners, owned by Dentsu, Jene Elzie was global head of marketing for the NBA. She says sports marketers have a complex view of audience data because fans consume content on multiple platforms.

“We need to understand the consumer journey across TV, digital, mobile, ecommerce, social media and retail so it’s critical for a brand to know where the data is coming from,” says Elzie.

Consistency and quality are important elements to provide answers about the consumer journey, but Elzie takes it further when discussing social media marketing. “We also need to verify that brands are connecting with the right athlete or influencer they are working with using data.”

People are still wary of third-party data

The common problem with programmatic advertising is that it’s often a ‘black box’ where trust and transparency issues get in the way of data-driven decision making. A lack of consistent metrics, widespread ad fraud, and visibility into third parties are just a few of the concerns plaguing the programmatic sector.

“There are lots of ‘dark corners’ in digital”, says Share This’ Michael Gorman. “Performance is what people are looking for and this is sometimes hard to gauge from data. People need to understand the process of how the data is built and structured.”

There’s also a hotchpot of different measurement and attribution models, according to Timur Yarnall, CEO of Neutronian, and brands had to deal with the fact that the ad -tech industry was essentially marking its own homework.

The need for best practices

The goal for Neutronian and its partner Eyeota, he says, is to highlight the good things that are happening in the ecosystem and become a platform that measures data quality and builds a framework of best practices that can be shared widely with the industry.

Yarnall adds: “Another good analogy is the financial markets where you have audited accounts and stock ratings that investors can rely on for decision-making.

Eyeota’s CEO Kristina Prokop agrees. She says one of the most important roles for her business is to communicate data quality to a wide-ranging audience whose knowledge levels vary.

“No matter how educated a brand is, a standardized set of terms and definitions is needed that make it easier to understand what data quality means. That enables people to ask the right questions and a baseline conversation is covered so everyone knows what we’re talking about. Then we can hold the industry to agreed standards,” says Prokop.

To be continued...

Watch the full panel session here.