
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.
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

We are excited to announce that we’ve updated our CAPE data with 2020 Census data. This release updates estimates and projections from 2010 and replaces all previous CAPE data attributes. U.S. Census data offers a great opportunity for data enrichment The U.S. Census is conducted every 10 years to determine the number of people living in the U.S. in addition to collecting data on dozens of topics across 130+ surveys and programs. U.S. Census data is already broken out into regional groups and covers 100k+ different geographies: States, counties, places, tribal areas, zip codes, and congressional districts. Block groups are the smallest geographic area for which the Bureau of the Census collects and tabulates data. They are formed by streets, roads, railroads, streams, other bodies of water, and other visible physical and cultural features. What is CAPE? Census Area Projections & Estimates data (CAPE) data from Experian utilizes a proprietary methodology to make the data easy to action on for marketing use cases. Made from U.S Census and Experian consumer data, CAPE data sets are developed at the block group and zip code level and targetable at the household level. CAPE 2020 updates CAPE 2020 uses the 2020 Census data blended with other Experian data to update CAPE’s unique attributes for data enrichment and licensing. Multiple sources are used and data is delivered at a block group level or zip code. Experian provides unique CAPE attributes not available through other sources that provide Census data. These include our Ratio and Percentages attributes, Score Factors/Segments, and Mosaic. CAPE 2020 use cases Our CAPE 2020 data sets enable strategic marketing analysis and decision-making. You can use CAPE 2020 data to understand the differences in the markets you serve as they relate to core demographics, housing attributes, education, income, employment, spending, and more. You can do this to: Find populations that are not typically captured in standard demographics. Cross-reference Census demographics data with other behavioral and shopper data. Understand supply and demand for products sold. Get started with our CAPE 2020 data today If you are using Experian’s CAPE 2010 data, please work with your Experian representative to migrate to CAPE 2020. If you are interested in learning more about our CAPE data, get in touch with us today. Contact us Latest posts

Centralized data access is emerging as a key strategy for advertisers. In our next Ask the Expert segment, we explore this topic further and discuss the importance of data ownership and the concept of audience as an asset. We're joined by industry leaders, Andy Fisher, Head of Merkury Advanced TV at Merkle, and Chris Feo, Experian’s SVP of Sales & Partnerships who spotlight Merkle's commitment to centralized data access and how advertisers can use our combined solutions to navigate industry shifts while ensuring consumer privacy. Watch our Q&A to learn more about these topics and gain insights on how to stay ahead of industry changes. The concept of audience as an asset In order to gain actionable marketing insights about your audience, you need to identify consumers who are actively engaged with your brand and compare them against non-engaged consumers, or consumers engaged with rival brands. Audience ownership Audience ownership is a fundamental marketing concept where marketers build, define, create, and own their audience. This approach allows you to use your audiences as an asset and deliver a customized journey to the most promising prospects across multiple channels. With this strategy, you enhance marketing effectiveness and ensure ownership over your audience, no matter the platform or channel used. Merkle enables marketers to own and deploy said asset (audience) so that marketers can have direct control over their audience. With audience strategy, you can tie all elements together – amplify your marketing reach, while maintaining control of your audience. Merkle connects customer experiences with business results. Data ownership Data ownership refers to the control organizations have over data they generate, including marketing, sales, product, and customer data. This data is often scattered across multiple platforms, making it difficult to evaluate their effectiveness. Alternatively, owning this data, which is typically housed in a data warehouse, allows the creation of historical overviews, forecasting of customer trends, and cross-channel comparisons. With advertisers and publishers both claiming ownership over their respective data and wanting to control its access, there has been a growing interest in data clean rooms. Data clean rooms The growing interest in data clean rooms is largely due to marketers increasing preference to maintain ownership over their audience data. They provide a secure environment for controlled collaboration between advertisers and publishers while preserving the privacy of valuable data. Data clean rooms allow all parties to define their usage terms – who can access it, how it is used, and when it is used. The rise in the use of data clean rooms strengthens data privacy and creates opportunities for deeper customer insights, which leads to enhanced customer targeting. Data clean rooms unlock new data sets, aiding brands, publishers, and data providers in adapting to rapidly changing privacy requirements. Why is centralized data access important? Centralized data access is crucial for the effective organization and optimization of your advertising campaigns. It involves consolidating your data in one place, allowing for the identification of inconsistencies. Merkle’s Merkury platform The concept of centralized data is a key component of Merkle’s Merkury platform, an enterprise identity platform that empowers brands to own and control first-party identity at an individual level. A common use case involves marketers combining their first-party data with Merkury's data assets and marketplace data assets to build prospecting audiences. These are later published to various endpoints for activation. The Merkury platform covers three classes of data: Proprietary data set – Permissioned data set covering the entire United States, compiled from about 40 different vendors Marketplace data – Includes contributions from various vendors like Experian First-party data from marketers – Allows marketers to bring in their own data Merkury's identity platform empowers brands to own and control first-party identity at an individual level, unifying known and unknown customer and prospect records, site and app visits, and consumer data to a single, person ID. This makes Merkury the only enterprise identity platform that combines the accuracy and sustainability of client first-party data, quality personally identifiable information (PII) data, third-party data, cookie-less media, and technology platform connections in the market. End-to-end management of data Data ownership and management enables you to enhance the quality of your data, facilitate the exchange of information, and ensure privacy compliance. The Merkury platform provides a comprehensive, end-to-end solution for managing first-party data, all rooted in identity. Unlike data management platforms (DMPs) that are primarily built on cookies, the Merkury platform is constructed on a person ID, allowing it to operate effectively in a cookie-free environment. A broader perspective with people-based views The Merkury platform is unique because it contains data from almost every individual in the United States, providing a broader perspective compared to customer data platforms (CDPs) which only contain consumer data. The platform provides a view of the world in a people-based manner, but also offers the flexibility to toggle between person and household views. This enables you to turn data into actionable insights and makes it possible to target specific individuals within a household or consider the household as a whole. How Experian and Merkle work together Experian and Merkle have established a strong partnership that magnifies the capabilities of Merkle's Merkury platform. With Experian’s robust integration capabilities and extensive connectivity opportunities, customers can use this technology for seamless direct integrations, resulting in more effective onboarding to various channels, like digital and TV. "Experian's role in Merkury's data marketplace is essential as they are considered the gold standard for data. It significantly contributes to our connectivity through direct integrations and partnerships. Experian's presence in various platforms and technologies ensures easy connections and high match rates. Our partnership is very important to us."andy fisher, head of merkury advanced tv Through this partnership, Merkle can deliver unique, personalized digital customer experiences across multiple platforms and devices, highlighting their commitment to data-driven performance marketing. Watch the full Q&A Visit our Ask the Expert content hub to watch Andy and Chris's full conversation about data ownership, innovative strategies to empower you to overcome identity challenges, and navigating industry shifts while protecting consumer privacy. Tune into the full recording to gain insights into the captivating topics of artificial intelligence (AI), understanding how retail networks can amplify the value of media, and the growing influence of connected TV (CTV). Dive into the Q&A to gain rich insights that could greatly influence your strategies. Watch now About our experts Andy Fisher, Head of Merkury Advanced TV As the Head of Merkury Advanced TV, Andy's primary responsibility is driving person-based marketing and big data adoption in all areas of Television including Linear, Addressable, Connected, Programmatic, and X-channel planning and Measurement. Andy has held several positions at Merkle including Chief Analytics Officer and he ran the Merkle data business. Prior to joining Merkle, Andy was the EVP, Global Data & Analytics Director at Starcom MediaVest Group where he led the SMG global analytics practice. In this role, he built and managed a team of 150 analytics professionals across 17 countries servicing many of the world’s largest advertisers. Prior to that role, Andy was Vice President and National Lead, Analytics at Razorfish, where he led the digital analytics practice and managed a team of modeling, survey, media data, and business intelligence experts. He and his team were responsible for some of the first innovations in multi-touchpoint attribution and joining online/offline data for many of the Fortune 100. Andy has also held leadership positions at Personify and IRI. Andy holds a BA in mathematics from UC Berkeley and an MA in statistics from Stanford. Chris Feo, SVP, Sales & Partnerships, Experian As SVP of Sales & Partnerships, Chris has over a decade of experience across identity, data, and programmatic. Chris joined Experian during the Tapad acquisition in November 2020. He joined Tapad with less than 10 employees and has been part of the executive team through both the Telenor and Experian acquisitions. He’s an active advisor, board member, and investor within the AdTech ecosystem. Outside of work, he’s a die-hard golfer, frequent traveler, and husband to his wife, two dogs, and two goats! Latest posts

Bridging disparate data in a fragmented world In today's world, consumers engage with brands across multiple platforms, including social media, online marketplaces, in-store experiences, and customer service touchpoints. However, the main challenge for marketers and advertisers is the fragmentation of customer data across these different channels. Each platform generates its own set of data, which is stored in different databases and formats. Integrating these various data sources to create a unified view of the customer is a complex task involving technology and understanding customer behavior across different digital and physical channels. Businesses must link these data fragments to avoid creating a disconnected customer experience. For example, a person may browse products on a mobile app, ask questions through a customer service chat, and eventually purchase in an online marketplace. Traditional data analysis methods often need to recognize these activities as those of a single customer, which can result in missed opportunities to deliver personalized customer experiences across the customer journey. Identity resolution: The key to a unified customer experience Connecting online interactions across various platforms is a challenge for brands. Identity resolution enables enterprises to overcome this challenge by stitching together disparate signals and records to orchestrate experiences and analyze outcomes more effectively. By pairing Experian's identity capabilities with AWS Clean Rooms, enterprises can securely collaborate with their partners to derive deeper insights without exposing sensitive underlying data sets. This partnership between AWS and Experian enables effective matching between disparate data sets, bolstering privacy-enhanced media planning, insights, data enrichment, media activation, and measurement use cases. Depending on their distinct needs and existing identifiers, customers can use two specific offerings of Experian's identity resolution solutions paired with AWS Clean Rooms. Experian's identity resolution products ensure a frictionless brand experience across various channels, enhancing the customer journey from start to finish. Brands can employ our adaptable identity resolution solutions to forge connections between contextual, behavioral, lifestyle, and purchase-based data sources, assembling comprehensive customer profiles. Use dependable digital data to make informed decisions and elevate consumer engagement. Advanced deterministic and probabilistic features, combined with data science and cutting-edge technology, work hand in hand to mitigate risk and uphold data privacy. Such recognition enables a more comprehensive understanding of your clientele, fostering trust and amplifying campaign effectiveness by utilizing securely managed, standardized customer data. With this strategic approach, businesses can achieve their objectives regulatory-compliant. The consumer perspective: Why consistency matters Data fragmentation can lead to inconsistent experiences for consumers, which can be frustrating and erode brand trust. For instance, imagine receiving a promotional email for a product you already purchased through an app or being targeted for a product you decided against. Consumers are increasingly tech-savvy and demand a seamless, integrated experience regardless of how they interact with a brand. They want to feel valued and recognized at every touchpoint and don't care about the complexities of data analytics. As a result, brands face significant pressure to get identity resolution right. Data security and privacy: A Fort Knox for your data AWS Clean Rooms empowers their customers to establish a secure data clean room within minutes, facilitating collaboration with any other entity within AWS. This fosters the generation of unique insights regarding advertising campaigns, investment decisions, clinical research, and more. With AWS Clean Rooms, the need to store or maintain a separate copy of data outside the AWS environment for subsequent dispatch to another party for consumer insight analysis, marketing measurement, forecasting, or risk assessment becomes obsolete. AWS Clean Rooms provides an expansive set of privacy-enhancing controls for clean rooms. This includes query controls, query output restrictions, and query logging that allows customers to tailor restrictions on the queries executed by each clean room participant. Moreover, AWS Clean Rooms include advanced cryptographic computing tools that maintain data encryption—even during query processing—to adhere to stringent data-handling policies. This process employs a client-side encryption tool—an SDK or command line interface (CLI)—that utilizes a shared secret key with other participants in an AWS Clean Rooms collaboration. With a wealth of expertise in data privacy management, Experian enhances campaign effectiveness and fosters trust by managing standardized customer data securely. By using the identity graph, you can preserve a unique identity for each customer. This strategy enables you to comprehensively understand your clientele and reach your business objectives in a regulatory-compliant manner. The future of data-driven marketing starts here AWS customers can use AWS Clean Rooms to establish their own clean rooms in mere minutes, initiating the analysis of their collective data sets without sharing their underlying data with each other. Customers can use the AWS Management Console to choose their collaboration partners, select data sets, and configure participant restrictions. With AWS Clean Rooms, customers can effortlessly collaborate with hundreds of thousands of companies already using AWS without needing to move data out of AWS or upload it to a different platform. When running queries, AWS Clean Rooms accesses data in its original location and applies built-in, adaptable analysis rules to assist customers in maintaining control over their data. Coupled with Experian's trusted data privacy management and unique Experian ID, businesses can effectively manage customer data, secure partners' communication, and achieve regulatory-compliance objectives. This combination allows companies to use data-backed insights to supercharge their marketing initiatives, resulting in more meaningful customer interactions, improved match rates, and business success. Start collaborating About the authors Kalyani Koppisetti, Principal Partner Solution Architect, AWS Kalyani Koppisetti is a technology leader with over 25 years of experience in the Financial Services Industry. In her current role at AWS, Kalyani advises financial services partners on best-practice cloud architecture. Kalyani works closely with internal and external stakeholders to identify industry technical trends, develop strategies, and execute them to help Financial Services Industry partners build innovative solutions and services on AWS. Technical and Solution interests include Cloud Computing, Software-as-a-Service, Artificial Intelligence, Big Data, Storage Virtualization and Data Protection. Matt Miller, Business Development Principal, AWS In his role as Business Development Principal at AWS, Matt drives customer and partner adoption for the AWS Clean Rooms service specializing in advertising and marketing industry use cases. Matt believes in the primacy of privacy-enhanced data collaboration and interoperability underpinning data-driven marketing imperatives from customer experience to addressable advertising. Prior to AWS, Matt led strategy and go-to-market efforts for ad technologies, large agencies, and consumer data products purpose-built to inform smarter marketing and deliver better customer experiences. Tyler Middleton, Sr. Partner Marketing Manager, Experian Marketing Services Tyler Middleton is the Partner Marketing Lead at Experian. With almost 20 years of strategic marketing experience, Tyler’s focus is on creating marketing strategies that effectively promote the unique value propositions of each of our partners’ brands. Tyler helps our strategic partners communicate their mutual value proposition and find opportunities to stand out in the AdTech industry. Tyler is an alumnus of the Seattle University MBA program and enjoys finding new marketing pathways for our growing partner portfolio. Latest posts