The AdTech industry is buzzing with discussions about cookie deprecation and effective strategies to tackle it. One of the commonly suggested solutions is the utilization of clean rooms alongside responsibly sourced first-party data.
Above all else, the industry recognizes the importance of respecting consumer data and complying with all privacy laws. Additionally, the industry acknowledges the need for a change in our historical practices. This shift benefits everyone involved, as consumer data is more secure than ever. Tremendous investments have been made to ensure the utmost security of consumer information.
Clean rooms are one of the tools that enable companies to use data securely, ensuring the content that you see is as relevant as possible.
Two ways the AdTech industry is addressing cookie deprecation
The days of sending data directly to partners for usage or for using only third-party data for marketing efforts are gone. Now, the emphasis is on responsibly collecting first-party data and using clean rooms to enrich first-party data to enhance marketing efforts.
First-party data
The industry is starting to lean into first-party data gained through transparent means. This valuable information provides organizations with deeper insights into their customers, allowing for more personalized and effective interactions. By embracing the power of first-party data, either on its own or enriched via partner collaboration, you can cultivate stronger relationships, build trust, and deliver tailored experiences that resonate with your customers on a deeper level.
Clean rooms
Many data lakes and warehouses offer this service, ensuring their clients can not only store their data with them but can connect it with other partners in a secure environment and extract more information through the combined data sets versus their data on its own.
Brands and their partners recognize that they need to work together, and a clean room provides a secure environment to share their first-party data without exposing their sensitive data to their partner.
So, while we’re losing third-party cookies, brands and partners can still get value from first-party data by using a clean room to generate audience insights, segmentation strategies, personalized experiences and offers, media plans, and measurement and attribution.
Three ways data clean rooms can improve
Data clean rooms are a great way to facilitate data collaboration while ensuring sensitive data is not exposed.
Data clean rooms are not yet easy to use nor are they inexpensive. They require investment, both financially and resource allocation-wise, and you are not guaranteed to yield great match results. Let’s dive into three areas for data clean room improvement.
High cost
According to the IAB’s State of Data 2023, nearly two-thirds of data clean room users spent at least $200K on the technology in 2022. In addition, one-third of data clean room users expect the price of data clean rooms to rise in 2023. The high cost of this solution can make it inaccessible to smaller companies in the advertising space.
Resource intensive
Nearly half of the companies using data clean rooms have a team of six or more dedicated to the technology, according to the IAB’s State of Data 2023, while nearly a third of companies using data clean rooms have 11 or more employees focused on the technology. Data clean rooms are not turnkey solutions.
Inefficient matching
Even if companies are using clean rooms does not mean that they are automatically going to achieve great success. Identity fragmentation, data hygiene, and differing identifiers can suppress client match rates in clean rooms, leading to significant investment and a lackluster output.
How to get the most return on your clean room investment
The finish line for data collaboration in clean rooms is not just having a relationship with a clean room. Instead, you should incorporate an identity resolution solution in your clean room. By adding an identity solution to your clean room, you can:
- Resolve and match all your identity data, regardless of the identity data that you or your partner have, giving you a larger data foundation to analyze.
- Generate more valuable insights and information, leading to a better experience for your customers.
- Join data sets to create smarter activation and targeting strategies and produce more holistic measurement.
Experian can help you get started with identity resolution and data clean rooms
If you are investing in data clean rooms, that means you are committed to the best in data practices. Experian recommends going the extra step and that you also invest in finding an identity resolution solution. By doing this, you can see better match rates.
Experian offers this capability and has existing relationships with three clean room partners, Amazon Web Services, InfoSum, and Snowflake. In addition to collaborating in clean rooms, we offer collaboration in two other secure environments.
Contact us today to discuss how we enable identity resolution in clean rooms or to chat about our other collaboration capabilities.
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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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In our Ask the Expert Series, we interview leaders from our partner organizations who are helping lead their brands to new heights in adtech. Today’s interview is with Georgia Campbell, Head of Strategic Partnerships at Kontext. What types of audiences does Kontext provide, and what are some top use cases for these insights in marketing strategies? Kontext leverages its 1st-party, deterministic shopping data to generate real-time online audiences. What sets Kontext apart is our ability to see the entire consumer journey, from shopping interest to intent and purchases, at a SKU-level. This comprehensive visibility allows us to create purchase-based audiences across various consumer verticals, such as frequent online shoppers, consumers shopping for beauty, segments using Mastercard, or Black Friday enthusiasts. Our data engine, built on a foundation of approximately 100 million consumer profiles and over 10 billion full-funnel, real-time shopping events, enables the creation of precise audience segments. This real-time 1st-party shopper data is invaluable for partners aiming to understand and engage with consumers more effectively. Whether a brand wants to activate past shoppers in a specific category or reach new audiences with a propensity to buy, Kontext provides the insights needed to make informed decisions. Some examples of audience types include these (and hundreds more): In-Market Shoppers: Consumers showing high intent to purchase specific categories, like skincare or electronics, based on recent online behavior. Past Purchasers: Shoppers who have made verified purchases within specific time frames, such as beauty products in the last 18 months. Frequent Shoppers: High-frequency buyers identified through repeated purchasing behaviors. Seasonal Shoppers: Consumers active during key shopping seasons, like Black Friday, Mother’s Day, Valentine's Day, etc Premium Buyers: Shoppers who used a premium CC (eg. Amex) and a higher AOV (average order value) Beauty Buyers: an audience that has indicated intent to purchase beauty products (deterministic past purchasers also avail) By using Kontext data, brands can identify the right audiences across multiple verticals, such as retail, CPG, health & wellness, auto, business, energy & utility, financial, and travel. Additionally, our collaboration with Experian allows further refinement of these audiences through layered data from specialty categories like demographics, lifestyle & interests, mobile location, and TV viewing habits. How is Kontext’s data sourced, and what differentiates it from other data providers? Kontext’s data is unique because it is deterministic, 1st-party, and collected as transactions occur. We capture the entire path-to-purchase, down to the SKU-level product detail, across 100 million consumer profiles and more than 10 billion real-time shopping events. Our proprietary technology, embedded in widgets across our 5 million premium online destinations, tracks the full consumer journey—from reading an article of interest to clicking on our dynamic commerce modules, adding items to cart, and completing purchases. This real-time data collection ensures there is no lag between digital events and their connection to consumer profiles. Unlike other providers, we do not aggregate data from multiple platforms; instead, we focus on building our models and insights based on authentic online consumer behavior. Our data stands out due to its: Deterministic Nature: We capture 1st-party data as transactions occur (all in real time) Full-Funnel Coverage: We capture consumer journeys from awareness to purchase, providing a complete view of consumer behavior. Real-Time Insights: Our data engine processes events in real-time, enabling timely and relevant marketing actions. How does Kontext ensure the accuracy and reliability of its audience data? Kontext ensures accuracy and reliability through our unique technology and direct data sourcing. By not aggregating data from other platforms, we maintain control over the quality and integrity of our insights. Our continuous investment in refining our models around online consumer behavior further enhances the precision of our audience data. What types of brands or verticals might resonate the most with Kontext audiences for activation? Any brand looking to understand and activate online shopping behavior – informed by 1st-party transaction data – will resonate with Kontext audiences. Essentially, any vertical that benefits from understanding real-time shopping behaviors, such as retail, health & wellness, auto, and financial services, will find our data invaluable. We have particularly strong insights in beauty, hair care, health & wellness, and values-based online shopping habits, as well as the food & beverage space. Retail & Consumer Goods: Leveraging shopping behavior data for targeted campaigns. Health & Wellness: Identifying consumers with specific health and wellness interests. Automotive: Targeting potential buyers of electric vehicles or eco-friendly products. Financial Services: Engaging high-value shoppers with premium credit card usage. And many more How does Kontext’s data help advertisers navigate the challenges posed by the deprecation of third-party cookies? As third-party cookies become less reliable, Kontext’s 1st-party data becomes invaluable. Our deterministic data engine, which does not rely on cookies, offers: Direct Consumer Insights: Accurate and consented data directly from consumer interactions. Privacy Compliance: Our data collection methods are fully compliant with privacy regulations, ensuring secure usage. Cross-Device Coverage: We use verified digital identifiers, allowing seamless unification and targeting across multiple devices. What measures does Kontext take to maintain data privacy and compliance, and how does this benefit advertisers? Data privacy and compliance are fundamental to Kontext. We meet or exceed all privacy compliance and security standards, ensuring that our data sourcing and usage are transparent and comply with regulations (CCPA, CPRA, VCDPA, etc). Kontext prioritizes data privacy and compliance through: Consented Data Collection: All data is collected with explicit consumer consent. Robust Security Protocols: Data is encrypted and secured with industry-leading practices. Compliance with Regulations: We adhere to global privacy laws, including GDPR and CCPA. User Control: Consumers have the ability to opt-out and manage their data preferences. Can you share success stories / use-cases where advertisers significantly improved their campaigns using Kontext’s data? To give you a sense of how Kontext data can be applied, here are two use-cases: Beauty Brand Campaign: An agency hoping to activate an audience of beauty purchasers for a Major Beauty Brand could utilize Kontext's custom audience of high-value beauty product purchasers. By targeting those consumers who had bought similar products in the last 12 months and had an average cart size of over $50, the campaign would significantly increase performance and ROAS. Electric Vehicle Launch: For a major auto manufacturer’s EV launch, Kontext could be used to identify eco-friendly consumers who had not yet purchased an EV but had shown interest in sustainable products. This precise targeting could lead to higher engagement and conversion rates for the campaign. Thanks for the interview. Any recommendations for our readers if they want to learn more? For those interested in learning more about Kontext, reach out for a personalized consultation. Contact us About our expert Georgia Campbell, Head of Strategic Partnerships, Kontext In her current role as Head of Strategic Partnerships at Kontext, Georgia plays a pivotal role in shaping the company's strategic direction within the data space. With a deep-seated expertise in leveraging data to drive impact for companies, Georgia has been forging key partnerships that enhance the effectiveness and reach of Kontext's offerings. Georgia comes from a background in emerging technology, where she has been focused on cultivating partnerships and employing data-driven approaches to spearhead market expansion efforts. She started her career in finance, managing investments across equity, debt, and alternative assets at Brown Advisory. In this Q&A, Georgia shares her insights on Kontext's Onboarding partnership with Experian, offering perspective on how Kontext's unique insights can unlock new opportunities for advertisers and brands alike. Latest posts