Data Quality Management Emerges as New Priority for Thriving in Today’s Digital Advertising Environment
By Lane Cooper, Editorial Director, BizTechReports
Leaders across the ecosystems are coming to grips with the fact that capturing, rationalizing and analyzing data to rapidly execute effective advertising campaigns across an increasingly complex digital landscape is a competency that will have to be mastered to enjoy sustained success.
Defining “quality” in the context of digital advertising can be confusing because the players across the industry have presented so many interpretations. Increasingly, however, the industry is coalescing around one core concept: identity resolution.
As consumers move from CTV to mobile phones to laptops, AI/ML technologies and big data analytics can be effectively used to identify individual “personas” within a household.
Spending on digital advertisements is poised to cross the $300 billion mark as we approach the middle of the decade. As a result, key players in the industry are in a race to secure strong market positions in this constantly evolving environment. After years of focusing on quantity — in which the industry has captured as much data as possible from as many sources as possible — a new key to prosperity is emerging, says Fariba Zamaniyan, vice president of data and advertising at TiVo.
Fariba Zamaniyan, TiVo
In a recent podcast interview, she described how leaders across the ecosystems are coming to grips with the fact that capturing, rationalizing and analyzing data to rapidly execute effective advertising campaigns across an increasingly complex digital landscape is a competency that will have to be mastered to enjoy sustained success. In other words, quality is trumping quantity when it comes to securing competitive advantage in advertising.
Quality Over Quantity
Defining “quality” in the context of digital advertising can be confusing because the players across the industry have presented so many interpretations. Increasingly, however, the industry is coalescing around one core concept: identity resolution.
“Quality in digital advertising boils down to how data can be leveraged to isolate and identify specific audiences in an accurate and accountable manner,” says Zamaniyan. “Once audiences have been identified in a way that meets this standard, advertising campaigns can be activated so that the right messages and products are presented to the people who are most likely to align with the offerings.”
This is not an easy feat to accomplish. The process of accessing large amounts of data to then leverage insights requires a comprehensive effort.
“Information must be collected from a vast array of sources in many different formats and then be aggregated for correlation analysis. Furthermore, not all data is equal. There is often bias in the data modeling and collection process which is problematic. This is why limiting bias is key for effective data analysis and decision-making,” explains Zamaniyan.
While the situation is maturing with the development of more sophisticated methods of data mining the discipline is still evolving. In many ways, however, the issue of quality is running into a cultural barrier because a preoccupation with data quantity remains. Old habits, it turns out, are difficult to kick.
“In the early days of digital advertising, the sector got caught up in the ability to collect vast amounts of data. It quickly became an article of faith that more data is better than less data,” explains Zamaniyan. “It flowed from the notion that information is power and more information makes you more powerful. What ensued was a wild west scenario where advertisers were in a race to grab all of the data they could possibly capture.”
This “land grab” approach opened the door for bad actors to “game” the new system. Click farms — and eventually bots — were introduced into the equation, creating false data while corrupting good information. As a result, a significant amount of data today is not truly representative of anything or anyone. This, says Zamaniyan, raises questions about how and when to trust data for planning, decision-making and campaign execution. It is the reason advertisers today are focusing increasingly on the quality of data to elevate the effectiveness of advertising.
“When we talk about ‘quality data’ we should be focused on referring to data sets that are an accurate representation and reflection of the audience we want to reach,” says Zamaniyan. “Armed with this information, advertisers can then create messaging that aligns with their target audience.”
The Transition to Digital Data-driven Advertising
While the transition to a new, digital, data-driven advertising ecosystem is gaining traction, we are still in the early stages. For instance, the infrastructure required to execute data-driven advertising decisions is incredibly complex. It involves machine learning (ML) and artificial intelligence (AI) systems that process and categorize vast amounts of data to identify and dismiss poor-quality data.
“That is why TiVo is working with a variety of technology and data analytics partners in the ecosystem to manage these complexities. It allows us to mine big data sets to get valuable insights into viewer preferences so that we can assist advertisers and streaming companies that are interested in personalizing ads and content,” says Zamaniyan.
“We are doing this while maintaining data integrity and protecting the personal data of consumers. When this is done properly — and with a strategic vision — we not only get advertising messages out effectively but also enhance the viewer experience,” she adds.
TiVo’s process of isolating and identifying data points across digital devices — including the “big screen” in the living room with connected televisions (CTVs) — is becoming increasingly sophisticated.
Best Practices for the Next Era of Digital Advertising
Integrating these different consumption platforms is the key to digital advertising.
“We live in a digital world where we consistently access content across several different platforms — desktop, laptop, tablet, smart TV, mobile phones and now connected cars. One of the biggest challenges facing the advertising industry today revolves around integrating consumers' connected lives and capturing the right information in a proper manner to establish effective identity resolution,” says Zamaniyan.
This is how the industry can ensure that the right messages are getting to the right people (real people) at the right time on the right device. As consumers move from CTV to mobile phones to laptops, AI/ML technologies and big data analytics can be effectively used to identify individual “personas” within a household.
“This is a gold mine for advertisers. This wealth of information enables advertisers to connect the dots and truly build an integrated digital ad campaign. It allows advertisers to manage the volume of impressions that need to be delivered, the frequency of delivery and the specific targeted messaging that should be displayed across multiple touchpoints and devices.”
To learn more, please visit: https://bit.ly/FaribaZamaniyan.