Audience Curation: When advertising learns from the food industry

In recent years, the advertising industry has made significant strides toward building a more transparent ecosystem in data collection—one that prioritizes consumer privacy and choice.

Advertisers are looking to harness this data in meaningful ways to deliver more relevant experiences. However, despite the industry becoming increasingly data-driven, the vast amount of data and the fragmented landscape present a major challenge for advertisers trying to navigate and leverage this data effectively.

Not all data is created equal

There are countless data brokers providing hundreds of thousands of audience segments, yet marketers have traditionally lacked the necessary insights to make informed decisions. Available information has been limited to basic details like data ownership, user count, and pricing—emphasizing volume over quality.

For example, a travel advertiser searching for relevant audiences may use a keyword like “frequent travelers” only to be overwhelmed by an extensive list of options with no clear ranking system or quality indicators to guide their choice. This is where audience curation comes in—empowering buyers with the necessary insights to make informed decisions that enhance campaign performance.

Audience curation simplifies the selection process for advertisers by providing additional information about these audiences. This allows marketers to make smarter choices and improve their campaign efficiency.

Standardizing Data Transparency with IAB Tech Lab Data Labels

IAB Tech Lab has developed standardized Data Transparency Labels to bring greater clarity to the data marketplace and Yahoo is the first DSP to adopt them. These labels provide advertisers with valuable insights into how audience segments are built and what data they contain, helping them make more informed decisions for their campaigns. To communicate this information in a clear and engaging way, IAB Tech Lab took inspiration from food nutrition labels—creating a simple yet effective format that lists the "ingredients" of each data segment. Below is some information advertisers can access similar to what you find on food labels:

• Fresh or frozen: When was it packaged? The lookback window is an important attribute for advertisers as it varies significantly across industries. For example, an auto-intender audience typically requires a longer lookback window—spanning several months—since consumers take time to research and deliberate before purchasing a new car. In contrast, industries with shorter decision cycles, such as travel or consumer goods, benefit from targeting audiences with shorter lookback windows to capture intent more effectively and drive timely engagement.
• Family-style or a la carte: How many servings per container? Knowing whether an audience is built at the household level versus the user level is crucial. For example, CPG brands benefit from household-level data as products are often shared in the family, while beauty and retail advertisers require user-level data to ensure they are reaching the right individual in the household.
• Farm-to-table: Are the ingredient sources clear? Understanding where the data originates is key to assessing its quality and compliance with privacy laws. Are the data sources public records, surveys, or commerce transactions? Knowing how the data was collected and processed helps advertisers gauge its accuracy and suitability for their campaigns.
• Organic or processed: The methodology behind audience data is key to evaluating its accuracy and reliability. Is the data declared—such as demographic information provided directly by users—or collected from a small panel and then modeled to represent the entire population? Declared data is typically more precise, whereas lookalike audiences offer greater scalability but may sacrifice accuracy. Each method provides unique advantages, and pricing should reflect these differences accordingly.
• Expiration dates: How often is the data updated? Some audience segments, like declared demographic data, require less frequent updates since this information remains relatively stable over time. However, intent- and interest-based audiences must be refreshed regularly to ensure accuracy and maintain relevance as consumer behaviors and preferences can evolve rapidly.

Yahoo DSP: Leading the Charge on Data Transparency

Being the first DSP to adopt the IAB Tech Lab Data Transparency label signifies our commitment to transparency. Our integration with IAB Tech Lab’s Data Labels ensures consistent and reliable data transparency for Yahoo DSP advertisers, empowering better decision-making, increased campaign performance and greater accountability across the data supply chain. Our ownership of extensive first-party data from direct consumer relationships across Yahoo media properties allows us to offer transparent insights into key information of Yahoo audiences in our DSP. 

The Industry Must Move Forward Together

At this critical moment for the industry, broad ecosystem participation is essential. Data owners and brokers must adopt and pass data labels—because only through collective adoption can we truly demystify audience composition and sourcing.