Seller-Defined Audiences (SDA): An Overview
Introduction
Targeted advertising drives over 70% of ad revenue globally and expected to reach 86% by 2030. Still, the deprecation of third-party data and stringent privacy principles have interrupted traditional ad targeting processes.
With publishers adapting to the changing ad tech sphere, a more accurate and targeted approach is necessary. Seller-Defined Audience (SDA) comes into play to empower publishers to use first-party data to develop an accurate and privacy-compliant segmented audience.
In this comprehensive guide, we walk you through Seller-Defined Audiences, how they work, best practices for their implementation, and comparisons with other audience targeting methods.
What Are Seller-Defined Audiences?
Definition of SDA
Seller-Defined Audiences (SDA) is a technical addressability specification released in 2022 by the IAB Tech Lab. It permits publishers to monetize their audience responsibly without data leakage.
SDA does not require publishers to use a distinctive ID or disclose users’ identities to advertisers. Instead, they utilize the IAB Tech Audience Taxonomy metric to classify users into groupings like demographics, purchase intent, or preferences.
Ideally, publishers are responsible for audience segmentation. However, advertisers have criticized this approach, arguing that some publishers may define similar audiences differently.
How SDAs differ from traditional audience targeting methods
SDA differs from traditional audience targeting methods in various ways, including:
- Data source and ownership: SDA depends on first-party data, giving publishers exclusive control over users’ definitions and segmentation. Traditional targeting relies on third-party data, with publishers having limited control over its accuracy. Its excessive scrutiny of third-party cookies also exposes publishers to possible compliance threats.
- Segmentation and customization: SDA allows publishers to segment users at a hyper-granular proportion, where they can customize segments depending on distinct patterns and intent. Traditional targeting uses a less dynamic, broad-based approach to group users, such as location, age, or gender. So, they have thin personalization to cater to various niches.
- Real-time versatility: Publishers can leverage SDAs to promptly update user segments based on metrics like user behavior. For example, in a significant news event, publishers can segment the audience that actively consumes the segmented content and push it to advertisers. Traditional targeting has a static audience, which may not entirely mirror real-time user behavior.
- Return on Investment (ROI): Publishers can tap into SDAs and garner higher engagement and click-through rates (CTR), as the data is directly embedded in users’ timely intent and behavior. Traditional targeting uses generic data, resulting in higher bounce rates and lower conversions.
How Do Seller-Defined Audiences Work?
Overview of the processes involved in creating SDAs
SDA rests on three primary pillars, as detailed below.
- Audience Taxonomy: Groups audiences among over 1,600 defined attributes to allow publishers to establish cohorts from first-party data.
- Data Transparency Standard: Details the process of gathering quality data.
- Transparency Center: Augments the above standard, allowing publishing data labels to consolidated resources.
Use of IAB Tech Lab’s audience taxonomy for standardization
The introduction of IAB Tech Lab’s audience taxonomy allowed the industry to have a similar nomenclature for user segmentation to boost data comparability across various providers. Its data transparency standard promotes harmonious user data labeling by first-party and third-party sources.
Additionally, the taxonomy categorizes the segmentation strategy into Tier 1 labeling. This labeling determines whether the segmented attributes are classified into demographic, purchase intent, or user interest, as illustrated below.
Source: IABTechLab
Audience segmentation by publishers
Publishers segment their audience into one or more classifications as stipulated by the IAB audience taxonomy. Although they may submit a custom taxonomy, the IAB Tech Lab reserves the right to validate every request through a Github Repo pull request.
Even so, publishers must eventually map a custom segment to either of the audience classifications. They may utilize their Data Management Platforms (DMP) to categorize the audience into a standardized cohort for SDA.
Although publishers can group identifiers based on a wide variety of user data in real-time, they may face the challenge of storing new SDA mandatory fields alongside the already segmented metadata.
The process of including segment IDs in bid requests
It is standard procedure for publishers to define the segment ID, provider, and taxonomy name in any bid request. This includes running the metadata in an OpenRTB bid request utilizing the current audience, segment entities, and data from version 2.6 OpenRTB.
If publishers opt for the Prebid solution, they must utilize the Prebid.js function to synchronize the appropriate ORTB feature in Prebid.
As reiterated by Anthony Katsur, the IABTechLab CEO, Prebid.js allows the SSP to fix and transmit the SDA data to the DSP.
Source: X
However, the publisher should determine how to transmit the attributes to Prebid. Although the IAB hints at using data assemblers, it does not explicitly divulge the specifics. Ideally, the interpretation could be that a publisher may need to submit a code to cluster SDA data.
Below are sample bid requests for the cookiless and cookied environments.
Source: IABTechLab
Data Utilization in Seller-Defined Audiences
SDAs utilize various data sources to generate a segmented audience, enabling publishers to monetize ads effectively. Below is how SDA utilizes data with:
Browsing behavior
SDA leverages three key metrics with pages visited, search queries, and time a user spends on a site. Based on these, the publisher can segment the audience based on user interests and develop a granular classification for niche advertising.
Demographic information
SDA utilizes demographic data, including age, gender, income, and location. It permits data segmentation across various aspects, such as generational, gender-specific, purchasing power, and geo-targeting.
Purchase history
Purchase history is a rich data source for items purchased, order value, and purchase prevalence. It enables publishers to build user profiles and classify them as prime or otherwise for segregated offerings.
Device data
SDA utilizes devices for type, operating system, and browser source data. This allows publishers to optimize device functionalities for targeted campaigns, aligning with device-specific user behavior.
Advantages of Seller-Defined Audiences
Improved Ad Targeting: How SDAs enhance targeting accuracy
SDAs leverage first-party data to analyze how users interact with products and web content, broadening user insights. Such data capability equips publishers to develop audience cohorts that closely mirror advertising needs. The result is effective ad campaigns and fewer wasted impressions.
Cost Savings: Reduction in advertising costs through more efficient targeting
Since publishers capitalize on their segmented data, they eliminate the burden of relying on costly external data sources. Alongside a premium and well-targeted audience, publishers can optimize ad revenues and maximize profits.
Increased Conversions: Potential for higher engagement and conversion rates
Definitive SDAs ensure ads get better outcomes in terms of CTR and conversion rates, building social proof for publishers’ inventory. With repeated successful campaigns, publishers can build advertising partnerships over the long run, creating a steady income.
Customization: Ability for publishers to tailor audience segments
For every data source, publishers get unique user insights, helping them segment the audience based on value and niche topics. Such customizations form a basis for publishers to have price differentiation, charging premium rates for well-targeted audiences.
Challenges and Disadvantages
Limited Reach: Potential constraints on audience size compared to broader targeting methods
Reliance on first-party data narrows the audience size, particularly for publishers with relatively low traffic or those focused on a single niche. So, they may be less attractive for wide-reach ads, negatively affecting the publishers’ revenue.
Data Privacy Concerns: Issues related to data collection and user consent
When collecting first-party data, publishers must comply with the relevant privacy laws, such as the GDPR or CCPA, and other global regulations. Any misstep in data privacy may jeopardize user loyalty and overall site engagement.
Cost of Data Management: Financial implications for publishers managing first-party data
Publishers must invest in talented manpower, security, tools, and technology to develop and maintain a data management system capable of handling robust first-party data, which can be costly. However, they can exploit data alliances to cut data management costs.
Limited Scalability: Challenges in scaling SDA across different platforms
SDAs compatibility with other DSPs or ad technologies may be resource intensive, limiting scalability. Also, other platforms may not align with SDAs, restricting the efficient utilization of multi-platform campaigns.
Comparison with Other Audience Targeting Methods
Contrast between SDAs, Universal IDs, and Google’s Topics API
As tabulated below, SDAs differ from Universal IDs and Google’s Topics API regarding features.
| Feature | Seller-Defined Audience (SDA) | Universal IDs | Google Topics API |
| Definition | Seller defines audience segments for targeted ads. | Distinctive identifiers that monitor users across various platforms or devices. | Google’s API groups web content into various topics for targeted ads. |
| Purpose | Allows publishers to use first-party user data to customize the advertising experience. | Enables publishers to leverage consistent identifiers for more accurate targeting across devices and platforms | Uses categorized content for personalized recommendations. |
| User Privacy Concerns | Relies on first-party data, requiring extra privacy compliance- depending on publisher data collection approaches. | Raise privacy concerns due to cross-platform tracking. | Focus on content categorization instead of monitoring minimizes privacy concerns. |
| Audience Creation | Use first-party data to define and segment the audience. | Uses DMPs to collect third-party data. | Google owns topics and keyword databases. |
| Audience Targeting | Targets users based on certain demographics or behavior. | Tracks users across platforms for ad personalization. | Categorized content for content discovery, recommendations, and ad targeting. |
| Integration | Integrated into Customer Relationship Management (CRM) systems and ad platforms to develop custom audiences. | Integrated across platforms to track and personalize ads. | Integrated into Google’s advertising and content recommendation systems. |
Implementation Best Practices
Steps for publishers to effectively implement SDAs
Publishers should strategically approach SDA implementation, focusing on data management, regulatory compliance, and technical alignment. Below are the steps to optimize the process.
1. Developing a first-party data strategy
To develop a first-data strategy, publishers should capitalize on primary data gathered directly from users, such as user interactions, browsing metrics, and content use. They should:
- Collect qualitative and quantitative user data by identifying main sources–websites, sign-up forms, apps, and more.
- Organize the data in a structured manner to facilitate segmentation.
- Augment data by integrating third-party behavioral data.
- Enhance user trust through data transparency and voluntary opt-in and opt-out forms.
2. Ensuring compliance with IAB standards
Publishers should ensure compliance with IAB standards in data collection, sharing, and use. They should:
- Follow the transparency and consent framework (TCF) to easily manage user consent and ensure compliance with data privacy frameworks.
- Enforce a consent management platform (CMP) to manage users’ consent to data collection while allowing them to manage cookies and data sharing preferences.
- Periodically audit data practices and amend data consent policies.
- Clearly inform users how personal data is being utilized and how they benefit.
3. Leveraging DMPs for audience segmentation
DMPs enable publishers to leverage SDAs and segment complex audiences by:
- Consolidating data from various sources, ensuring publishers have a wide audience outlook.
- Segmenting the consolidated data based on user interests, demographics, and browsing habits.
- Activating data in real-time based on audience behavior for relevance and actionability.
- Integrating with DSPs and ad grid, enabling publishers to monetize the segmented audience through personalized ads.
- Providing resource-based tools for publishers to monitor the efficacy of their audience segmentation and for strategic optimization.
Future of Seller-Defined Audiences
SDAs are shaping the digital space, with 72% of brands preparing to shift from third-party to first-party cookies. Google has also been at the forefront of winding up third-party cookies in Chrome.
Since first-party data has become the most popular solution, accounting for 25%, the trend is expected to continue in compliance with Google’s directive.
Source: HubSpot
Also, Artificial Intelligence (AI) in audience personalization comes into play, with 46% of companies using AI to hyper-personalize user experiences. This aligns with the SDA strategy to utilize user data to drive improved recommendations.
Source: Ascend2
Besides, ad revenue driven by personalized customer experience is projected to surpass the current $9.5 billion, and publishers are strategizing to tap into this revenue. This trend indicates SDA will transform the digital advertising space in the future.
Conclusion
Digital advertising continuously embraces efficiency and prioritizes privacy. SDAs help publishers drive this narrative and deliver targeted and personalized ads while complying with global privacy regulations.
This is a no-brainer, as 73% of users are more concerned about data privacy. So, SDA is a forward path to balance privacy and ad demand. It is not just to stay relevant but to grasp data control, monetize opportunities, and promote the future of targeted ads.
