The end of third-party data has disrupted the martech and adtech industries. In 2017, Firefox and Safari depreciated third-party cookies. The next year, we saw the most significant privacy-first legislative move in history. Since these dramatic events, companies have been scrambling to find alternatives to traditional identity resolution techniques with few promising results.

However, not everyone has viewed this supernova event as a catastrophe. The teams at Echelon DS, a full-service data solutions provider, and Confection, a privacy-first data generation solution, see the pivot to privacy-first as a prime opportunity to dream bigger and build better data for the martech and adtech industries.

David Ruddel, Machine Learning Expert at Echelon DS, explains the issue they and Confection are tackling: "Traditional identity resolution techniques rely on fragile, easily-interrupted data sources like IP addresses, cookies, and cross-domain scripts. That’s the technical challenge. Socially and culturally, we also see an increased interest in data protection rights. For both of these reasons, we see traditional means of resolving identities being steadily depreciated. And the model we’re building will be far more performant (and privacy respecting) than even the best-case, front-end-dependent identity resolution techniques available today."

As front-end identity resolution solutions become increasingly inefficient, server-side products like Confection have incredible growth potential in the coming years, especially as Google begins to phase out third-party cookie support in 2023.

"Echelon DS has worked with Confection to design a server-side, AI-driven identity resolution model," David adds. "Amplifying the predictive model [Confection co-founder and CTO] Bruno already built, this model will give us the ability to attribute events to users at various levels, from specific individuals to thematic audience groupings."

This gives Confection customers access to both granular, lead-level details for B2B ABM campaigns, for example, and collective, audience-level details when serving relevant content to mass audiences (or B2B prospects higher in the funnel). The nuances of Confection's AI-driven model account for the complexities of changing consumer attitudes and interests, as well as the high standards set by the new privacy-first world.

"To adequately model the complexities of the human experience," Quimby Melton, CEO of Confection, says, "we need multi-layered ‘quantum’ identity resolution techniques. Working as partners, Echelon DS is helping us build a malleable, evolution-enabled identity model based on real-time preferences and actions, sudden changes in consumption velocity (‘I just learned something new, and now I need to binge this podcast, read all this content, &c’), and what Oren Klaff would call ‘frame-annihilating’ shifts in personal identity."

Since Confection was founded, Echelon DS has been by their side to develop these AI-driven technologies and find the ideal product-market fit in a wildly changing martech industry. Through months of R&D, they were able to develop a novel technology that is poised to solve the data crisis many marketers, advertisers, and application developers are experiencing firsthand.

Quimby noted the importance of Echelon DS as their partner in the startup phase: "They were our first investors, and that faith gave our team the foundation it needed to get started. As we keep pushing forward, the Echelon ecosystem continues fueling our success. When we decided to enhance Confection's predictive identity resolution model with AI and machine learning, Echelon DS was there as a go-to data science resource. Working with their team saved us months of research and planning, and we were able to minimize a lot of risk by working within a professional network we already trust."

By reinventing traditional identity resolution models, Confection helps customers minimize client-side disruptions and build targeted, well-rounded, privacy-respecting marketing campaigns.

As David notes, "Privacy is personally important to me, as is content relevance. The machine-learning model we’re building for Confection’s product stack solves both challenges. The technology enables more durable and more accurate identity resolution, but we can also selectively anonymize users as needed. In addition to product administrators, we can offer these kinds of controls to Confection customers and even everyday web users."

Together, Confection and Echelon DS are reinventing the standard for identity resolution in a way that’s good for marketers, brands, and people alike.

About Echelon DS
Echelon DS is a full-service data science solution provider that partners with businesses to create custom-built applications. In parallel, our advisory services team empowers client teams with a working knowledge of machine-learning solutions that allows them to develop additional tools, as well as provide valuable context when integrating developments from other data science sources. For more information, please visit echelonds.com

About Confection
Technical disruptions make it difficult for marketers to generate and leverage high-quality digital data. Confection helps customers collect, store, and distribute digital marketing data in a way that’s both compliant and unaffected by disruptions involving cookies, cross-domain scripts, and device IDs. The company serves marketing professionals and application developers at SMBs around the world. For more information, and to see Confection in action, please visit confection.io

"Traditional identity resolution techniques are far too binary to model the complexity of the human experience," says Quimby Melton, CEO of Confection. "We’re in a constant state of encountering new information, which changes the way we think about things, which affects our identities, and which ultimately manifests itself in our preferences. Sartre’s concept of ‘radical freedom’ is relevant here: Who we were yesterday is not who we are today, and who we’ll be tomorrow is not who we are today. This impacts identity resolution on both the individual level (‘I don’t like that anymore’) and the audience level (‘I’m with these people now, not those people’)."

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