What makes an ad impression valuable to an advertiser? The inventory where an ad appears, the audience it reaches, or its potential to contribute to a business outcome?
The answer often involves all three. Yet curation is frequently discussed in terms of site lists, audience segments, and deal IDs. These play an important role, but they don’t tell the full story of the intelligence and decisioning required to evaluate supply and media opportunities.
Advertisers want to reach relevant audiences across quality inventory, make efficient use of their media investments, and achieve measurable business outcomes. Meeting those goals requires connecting the right identity, consumer intelligence, technology, and optimization closer to the source of each impression. Making decisions too late in the transaction can mean missing more effective, direct, or cost-efficient paths to an advertiser’s target audience.
The four pillars of effective curation
Curation works best when four capabilities come together to connect advertiser objectives with relevant media opportunities.
1. Identity makes data useful across environments
Advertisers know their customers, publishers know their audiences, supply-side platforms (SSPs) understand their inventory and traffic, and demand-side platforms (DSPs) bring knowledge of campaign goals. Data partners add behavioral insights. Each may use different identifiers, making it harder to recognize the same person or household consistently across the ecosystem.
Identity provides a shared foundation for connecting these signals. A trusted, widely adopted identity graph can link permitted identifiers to a consistent view of people and households across participating ecosystem partners. This allows advertiser, publisher, and audience data to work together under appropriate privacy controls to inform media decisions.
When that identity foundation is available through real-time integrations, audience signals can be interpreted more effectively as media opportunities arise. Decisioning can apply a consistent understanding of the audience across participating supply environments, keeping audience context connected as opportunities move through the ecosystem.
2. Consumer intelligence adds context to each opportunity
Effective consumer intelligence starts with trusted data and understanding who consumers are, what they do, and what they care about, collected and used with appropriate consent, privacy protections, and permissions.
To achieve that, it’s critical to identify which data providers, audience segments, and types of data are best suited to a specific campaign and deal. Different sources offer different insights, and selecting the right combination helps advertisers identify relevant audiences and make more informed media decisions.
The right signals depend on the campaign. Retail campaigns may draw on purchase history and other behaviors that help predict future spending. Automotive campaigns may rely more on in-market signals, given longer buying cycles, to inform audience, messaging, and channel strategies. First party audiences play a crucial role in many use cases, and the ability to apply these audiences through an independent decisioning system maximizes match rates while minimizing data sharing across platforms.
Rather than relying on a predefined mix of audience segments, an advanced decisioning system can use campaign goals, brand context, and other available signals to shape the audience for each opportunity.
It can help identify which data providers, segments, and data types are most relevant, and then adjust the audience mix as performance and outcomes provide new information. This supports more tailored media decisions throughout a campaign.
3. Technology integrations connect intelligence to supply
Real-time connections with SSPs let decisioning systems consider signals such as context, device information, and format alongside advertiser audience and campaign criteria as opportunities arise. But each SSP integration can expose different signals and data structures, making it difficult to apply a strategy consistently across supply. A neutral intelligence layer connected through the right technology framework can normalize those inputs across participating SSPs and return qualifying deal and audience signals through the SSP, helping DSPs prioritize relevant opportunities in their existing workflows.
4. Optimization turns insights into better decisions
Optimization becomes more informed as demand-side performance data, signals from real-time supply integrations, and online and offline conversion data come together. Connected through a consistent audience view, these signals can help categorize inventory and identify supply paths associated with stronger performance.
Real-time decisioning and optimization help apply those insights quickly during a campaign, while accumulated learnings can inform future campaign setup and delivery. Decisioning systems can evaluate impressions quickly. The quality, relevance, and connectivity of the information behind them determine how useful those decisions are.
Bringing intelligence closer to the impression
Advances in real-time technology are creating new opportunities to apply this intelligence earlier in the media transaction.
Traditionally, much of the intelligence informing programmatic buying has been applied through DSPs. Curation was developed and widely adopted in part because it improved decisioning and performance by layering supply side signals into the ad buying workflow. Containerization is how SSPs are extending that shift, allowing decisioning capabilities to operate within or alongside their infrastructure, closer to the source of supply.
While containers are powerful tools, containerization alone doesn’t create interoperability across supply. Each container operates within its SSP environment, therefore utilizing native features and signals available there.
Real-time integrations are needed to pass signals from participating SSP environments into a neutral decisioning layer. That layer can connect varying signals and identifiers across supply sources, helping apply decisioning more consistently across different sources and types of supply. Imagine an automotive campaign focused on test-drive bookings. Identity and audience signals help recognize likely buyers. SSP signals such as context and format describe the available placements. Campaign and conversion feedback can show which audience, context and placement combinations are performing better. Real-time integrations help apply those learnings across participating SSPs during the campaign, so the DSP can prioritize stronger opportunities while retaining control of bidding.
Advertisers, publishers, data providers, DSPs, and SSPs each contribute different signals that can inform media selection. Connecting those signals through trusted identity and interoperable technology can make decisioning more relevant to individual campaign objectives.
AI can take this a step further by analyzing connected signals and executing media decisions faster and more dynamically. As more relevant data becomes available in real time, AI-driven models could tailor how opportunities are evaluated based on an advertiser’s campaign objectives, audience priorities, and the specific requirements of a DSP. With access to appropriate performance feedback, these systems could refine their decisions over time, making curation increasingly responsive to individual campaigns.
What’s next for curation?
Curation will continue evolving into a real-time decisioning engine for the advertising ecosystem, connecting identity, consumer intelligence, technology, and optimization closer to where media opportunities become available. Neutrality and interoperability will be central to making that intelligence work across platforms and creating value for everyone involved.
Site lists and deal IDs remain useful components of programmatic activation. Relying on site lists and contextual signals alone, though, means overlooking much of what curation can offer. The broader value comes from connecting identity, consumer intelligence, technology, and optimization through real-time supply integrations to inform media decisions. As these capabilities become more connected, curation can play a greater role in how the industry evaluates and acts on media opportunities, helping advertisers and their partners make faster, more customized decisions across the open web.
That’s where the value of modern curation comes into focus, and where its future in media lies.
About the author
Budi Tanzi
SVP, Product, Experian
Budi Tanzi is the Senior Vice President of Product at Experian Marketing Services, overseeing all identity products. Prior to joining Experian, Budi worked at various stakeholders of the ad-tech ecosystem, such as Tapad, Sizmek, and StrikeAd. During his career, he held leadership roles in both Product Management and Solution Engineering. Budi has been living in New York for almost 11 years and enjoys being outdoors as well as sailing around NYC whenever possible.
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In our Ask the Expert Series, we interview leaders from our partner organizations who are helping to lead their brands to new heights in ad tech. Today’s interview is with Jordan Feivelson, VP, Digital Audiences at Webbula. Jordan is a 22-year advertising industry veteran who has worked for media properties such as WebMD and Disney. Over the past ten years, he has transitioned to the data and programmatic space, including growing the data business for Kantar Shopcom and Adstra. What types of advertisers might benefit from utilizing Webbula audiences across various verticals? Can you provide examples of how different industries successfully leverage your data to achieve specific campaign goals? Most advertisers can leverage Webbula’s award-winning attributes for their activation initiatives. Webbula offers approximately 3,000 syndicated segments covering categories such as Demographics, Automotive, Political, Mortgage, B2B, Hobby/Interest/Lifestyle, and Interests & Brand Preferences (brand name targeting). Audience insights and marketing strategies What specific types of audience segments does Webbula provide? How can advertisers leverage these segments to craft more effective, personalized marketing strategies? Webbula has incredible depth and breadth within its verticals, giving marketers the tools to deliver targeted messaging effectively. Our Demographic, B2B, Mortgage, Automotive, and Interest and Brand Preferences segments each contain 500-1,000 segments, all built on deterministic, self-reported, and individually linked data. We ensure the best accuracy with multiple deterministic data points tied to the real world (ex., first name, last name, postal address, and email address). Some examples of our unique syndicated audience types: B2B: A view of the latest industry trends with detailed cuts of the professional world, such as companies with and not within the Fortune 500 companies and job positions that are directors and below. This also includes custom capabilities, including ABM (list of target companies in an activation campaign or by industry code (ex. NAICS, SIC). Interest and Brand Preferences: Consumers who have shown interest and affinity to hundreds of brands (ex., Nike), genres (ex., comedy, hip hop), sports teams, and more. Mortgage: A detailed view of homebuyers’ purchase range, loan type (ex. jumbo loan, standard loan), mortgage amount, interest rate, and more. With Webbula’s audience data, brands can create a comprehensive picture of their audiences down to the individual level and reach them accurately. Data quality, sourcing, and differentiation How is consumer data sourced and curated at Webbula? Are there data quality standards that Webbula establishes for consumer data, and how do you ensure your sources and methods meet these standards consistently? Webbula’s data is aggregated from over 110 trusted and authenticated sources, including publishers, data partners, social media, and more. The data collected comes directly from consumers who self-report information through surveys and other methods. We apply our hygiene filters to mitigate fraud and accurately score the data. Data Collection: The data collected comes directly from consumers who self-report information through surveys, questionnaires, transactions, and sign-ups. This ensures that brands display ads to audiences based on self-identified, cross-channel behaviors, not modeled assumptions. Hygiene Solutions: Webbula applies multi-method hygiene solutions to mitigate fraud and accurately score the data before onboarding, ensuring that all data meets the highest quality standards. Examples of Data Sources: Questionnaires: Self-reported data through surveys, offer submissions, and telemarketing. Transactions: Deterministic data from aftermarket parts, online purchases or services, and more. Sign-ups: Individually linked data from information entered through sweepstakes, infomercials, newsletters, and forms. What differentiates Webbula’s data from other data providers in the market? Can you explain the unique value proposition that Webbula offers in terms of data depth and breadth? Due to our extensive experience in data cleansing, we provide the most accurate data within the programmatic ecosystem. TruthSet, the leading programmatic accuracy measurement company, has ranked Webbula as having the highest number of top attributes compared to other data providers with 150M+ HEMs. Additionally, Publicis Groupe and Neutronian further validate Webbula’s data quality, underscoring its position as a leader in the industry. Webbula’s data stands out in the market due to its unmatched accuracy and quality, achieved through years of expertise in data cleansing. Unlike other providers, Webbula’s foundation lies in its robust email hygiene process, ensuring that all data entering the programmatic ecosystem is thoroughly cleansed. Privacy, compliance, and future-proofing What measures does Webbula take to maintain data privacy and compliance? How do these efforts benefit advertisers in an evolving regulatory landscape and ensure ethical standards? Webbula was created over a decade ago with a future-proof, privacy-compliant foundation. We understand the industry’s rapid changes, including government and state legislation and cookie depreciation. Our goal has always been to build long-term partnerships and ensure we are prepared for industry changes. We rely on validated offline data sources, making us resilient to external influences. Success stories Can you share success stories where advertisers saw significant campaign improvements using Webbula’s data? What were the key factors that contributed to these successes? Our success is measured by client feedback and increased client spend. Webbula has helped several key advertisers achieve six-figure monthly thresholds by providing the most accurate data to meet campaign KPIs. Clients consistently return to use our data, validating our belief that “the proof is in the pudding.” Thanks for the interview. Any recommendations for our readers if they want to learn more? For those interested in learning more about Webbula, reach out for a personalized consultation. Contact us Latest posts
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