AdTech has never had more data, yet it has rarely been harder for brands and agencies to answer a simple question: what actually drove the result?
Clicks, conversions, and platform-reported performance have long served as proxies for success, shaping how campaigns are evaluated, budgets are allocated, and results are communicated. But they were never designed to measure business impact directly. They offer a directional view of activity rather than a definitive answer.
Clicks indicate interest, conversions indicate action, and platform-reported metrics reflect performance within a given environment. Each of these signals plays a role, but none of them, on their own, can confirm whether marketing led to a business outcome.
That limitation isn’t new, but it’s becoming more visible as signals shift and measurement becomes more fragmented. Measurement systems are under increasing strain, shaped by signal fragmentation, privacy constraints, and data environments that make it harder to connect media exposure to outcomes. In fact, 75% of marketers say their current approaches are falling short.
Performance can appear strong in one platform and materially different in another, making it harder to reconcile results across partners. Connecting campaign performance to actual business outcomes remains difficult.
As identity, data collaboration, and measurement become more strategic to marketing performance, organizations are looking for infrastructure that can connect data across partners while preserving neutrality, flexibility, and interoperability.
Why performance doesn’t always reflect impact
Even when data is available, it doesn’t always tell a complete or accurate story.
A conversion after an ad exposure may suggest a relationship, but it doesn’t establish causation. Attribution models favor what’s easiest to measure, and platform-reported metrics often reflect biases toward their own ecosystems. Over time, this creates a version of performance that can appear accurate while overstating actual impact.
Measurement should move from signals to conversions, then to verified outcomes, and ultimately to incrementality. Each step brings measurement closer to understanding true business impact. In practice, most strategies stall in the middle, treating conversions as the endpoint even though they don’t show whether marketing drove the result.
This creates a gap between what’s measured and what matters. Incrementality is gaining focus because it isolates what changed due to marketing, separating true impact from what would have happened anyway. Industry guidance increasingly reflects this shift, recognizing incrementality as a reliable way to measure causal impact in a fragmented, privacy-first ecosystem.
As AI and agentic technologies become more involved in planning, optimization, and decision-making, the quality of the underlying identity and data foundation becomes increasingly important. Reliable outcomes require trusted identity and interoperable data.
The infrastructure shift: Why CAPI matters now
Measurement is evolving at both a conceptual and technical level.
As browser-based tracking becomes less reliable, the industry is shifting toward server-side approaches, including conversion APIs (CAPI). These approaches create a more direct, durable connection between advertiser data and platform systems, reducing reliance on signals limited by browsers and privacy controls.
Platforms are reinforcing this shift. Meta positions CAPI as a way to improve data quality, measurement accuracy, and optimization by enabling more complete event capture. Google similarly emphasizes server-side tagging to improve data control, resilience, and performance in modern measurement environments.
On their own, these approaches don’t solve the measurement challenge. Combined with identity, they create a stronger foundation for connecting marketing activity to real outcomes.
Stronger data collection infrastructure is most effective when paired with interoperable identity and privacy-first governance, giving marketers greater confidence in how data is connected, activated, and measured across environments.
Identity as the connective layer
Identity resolution is a key enabler of that foundation. By connecting identifiers across platforms, devices, and environments, it helps marketers tie exposure to consumers and, ultimately, to real-world outcomes. Without it, measurement stays siloed across platforms and channels. With it, marketers can see how activity across environments contributes to a single outcome.
Interoperable identity is becoming more than a marketing capability. It increasingly serves as a foundational layer that helps brands, agencies, publishers, platforms, and partners collaborate across a growing number of data and media environments.
Industry efforts around data clean rooms, interoperability, and privacy-safe collaboration all address the same challenge: how to connect data across environments without relying on outdated or fragile signals. Solutions that strengthen identity resolution within these environments improve match rates between partners, making collaboration more effective and measurement more complete.
As collaboration expands across clean rooms, platforms, and activation channels, marketers benefit from identity frameworks that support interoperability rather than limiting how data can move across the broader ecosystem.
What brands and agencies should expect next
For brands and agencies, the focus is shifting from what appears to perform within a platform and toward what drives results. That requires looking beyond platform-reported metrics, asking more of measurement partners, and incorporating incrementality into how success is defined.
It also requires investment in identity and measurement that enable outcome-based measurement. Without that foundation, even advanced reporting will struggle to provide a clear view of performance.
That foundation should include trusted consumer data, transparent governance practices, and identity capabilities that can adapt as technology, privacy expectations, and AI-driven workflows continue to change.
Many organizations are also evaluating how measurement, identity, and activation strategies can maintain long-term flexibility across agencies, platforms, publishers, commerce media networks, and emerging channels.
What this shift means for AdTech
Reporting within platforms or optimizing intermediary metrics is no longer enough. Success increasingly depends on demonstrating how marketing activity translates into business results across channels and environments.
As marketing systems become more automated, brands need visibility into the data and identity layers informing those decisions, along with confidence that those systems are operating on accurate, privacy-safe consumer information.
That shift requires interoperable identity, cross-platform measurement, and infrastructure that supports more complete and reliable data collection. It also requires validating whether marketing drove incremental business impact, rather than simply reporting observed conversions.
Independent identity and neutral data infrastructure can help support that effort by giving organizations the flexibility to work across partners, platforms, and channels while maintaining consistency in measurement and audience understanding.
This means building systems that connect exposure to outcomes, measure incremental impact, and link media investment and business results. Clicks and conversions remain useful, but their limitations are becoming more visible as reliability declines.
Trusted identity, privacy-safe data collaboration, and transparent measurement are becoming central to how marketers build durable strategies that can adapt as the ecosystem continues to change.
Measurement will be defined by the ability to connect marketing activity to verifiable outcomes, with incrementality at the center of understanding true impact.
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About the author
Ali Mack
VP, AdTech Sales
Ali Mack leads Experian’s AdTech business, overseeing global revenue across the company’s expansive tech and media portfolio. With over a decade of experience in digital and TV advertising, Ali drives strategic growth by aligning sales, customer success, and solutions teams to deliver impactful outcomes for clients and partners.
She has successfully guided teams through two major acquisitions, integrating sales organizations and product portfolios into unified go-to-market strategies. Under her leadership, Experian has consistently exceeded revenue targets while fostering collaborative, results-driven teams and mentoring emerging leaders. Working closely with finance, product, and marketing, Ali develops strategies that support a diverse ecosystem of publishers, brands, and technology partners, positioning Experian at the forefront of data-driven advertising and identity resolution.
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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
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