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Why Data Quality Matters - Part One

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.


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

· Clients,Tech

West Pier Ventures recently broughttogether a panel of experts from across the industry to discuss how they areworking 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, BusinessDevelopment & Marketing, Share This 

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

While there are significant challenges, theindustry continues to strive for greater transparency across the supply chainto 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, astandardized approach to measuring data quality remains some way off. 

Perhaps the best analogy of the presentsituation 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 knowingwhether it’s good or bad for you! 

Added to that, data quality includesnumerous 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 thequality of the data that is leveraged for their own decision making. 

Standardization of terminology 

Certainly, transparency, reliability andaccuracy were already dominant factors. But as the industry moves towards evermore 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 ofmarketing 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 journeyacross TV, digital, mobile, ecommerce, social media and retail so it’s criticalfor a brand to know where the data is coming from,” says Elzie. 

Consistency and quality are importantelements to provide answers about the consumer journey, but Elzie takes itfurther 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 programmaticadvertising 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’ indigital”, says Share This’ Michael Gorman. “Performance is what people arelooking 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 differentmeasurement and attribution models, according to Timur Yarnall, CEO ofNeutronian, 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 theecosystem 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 thefinancial markets where you have audited accounts and stock ratings thatinvestors 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 dataquality to a wide-ranging audience whose knowledge levels vary. 

“No matter how educated a brand is, astandardized set of terms and definitions is needed that make it easier tounderstand 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...