AMENIA, NY — First-party data has earned its valorization the last few years, particularly among the brands that tend to own it. But that doesn’t mean third-party data, which has had its ups and downs and ups again lately, is inherently less useful.
“When people even outside of advanced TV hear about third-party data, they have a gut reaction that it’s icky or it’s low quality,” Suvadip Choudhury, head of TV partnerships at media analytics provider Alliant, told Beet.TV contributor David Kaplan at the Beet Retreat Berkshires 2025. “I think that is a huge misconception just because data is not originating from the direct source, doesn’t invalidate it.”
This perception problem comes as video streaming fragmentation and shifting consumer viewing habits create complex targeting challenges that first-party data alone cannot solve.
Consumer behavior’s influence
The television advertising landscape has been experiencing a new revolution every few months as this age of practically infinite access content creates new consumer behaviors.
“You have every organization with content coming out with their own streaming service, you have the rights to stream different pieces of content moving around, and it creates a really complex environment for consumers and their behaviors change as the options change,” Choudhury said.
This fragmentation forces advertisers to navigate multiple platforms and data sources while maintaining campaign effectiveness and audience reach across an increasingly dispersed viewing environment.
Data partner selection criteria
Choudhury highlighted three critical questions advertisers should look at when questioning potential data providers.
First, compliance and data provenance matter more than convenience, requiring understanding of original data sources and user consent processes.
Second, third-party validation provides essential quality assurance. “A great question to ask is if the data has been validated by a third party, this could be a measurement provider or some sort of case study or even an independent body that will rank or tell you how accurate your data is,” he said.
Third, model transparency separates sophisticated providers from black box solutions. “Savvy data providers will be able to tell you exactly how that model is built, the details of which are so paramount to understanding what drives performance and who your consumers are,” Choudhury said.
Bridging first and third-party data gaps
At Alliant, data flows through what Choudhury describes as a cooperative model where first-party data becomes second-party during processing and third-party upon activation. This structure addresses data quality concerns while expanding audience reach beyond known customer bases.
The model proves particularly valuable for retail media networks expanding into non-endemic advertising categories. “There is a place where third party data can fill gaps for retail media networks. This is mainly in their non-endemic businesses where you have to think through what can a data provider tell me that I don’t already know?” he said.
This fills the reach limitations that pure first-party strategies create. “It behooves a company buying media to only focus on it and miss reaching all of the people outside of their known walls,” Choudhury said.
Data freshness critical for TV targeting
Television advertising faces unique data freshness challenges due to unstable identifiers like IP addresses that cycle regularly. Unlike other digital channels with persistent identifiers, TV targeting relies on IP mapping that can become stale within 30 to 90 days.
“The data freshness piece is even more important in TV than it is with other channels just because so much of it is happening on unstable identifiers like IP address, which cycles out,” Choudhury said.
Without regular refresh cycles, advertisers risk targeting outdated IP addresses that no longer represent intended audiences. “You run the risk of having stale data where that IP is suddenly now out of market or representing someone else,” he said.
Choudhury recommended quarterly refreshes as a minimum cadence. But that refresh methodology matters more than frequency. Complete model reruns with new ID populations outperform simple additions of net new identifiers to existing audience pools.
Platform ubiquity strategy
Alliant’s competitive strategy involves data integration across the entire TV ecosystem rather than focusing on major platforms exclusively. This includes cable providers, programmers, broadcasters, and underlying ad serving technologies.
“Alliant takes a strategy of having data everywhere where we really want to make sure that if it’s a TV platform that buyers are transacting on or media is moving through some sort of technology and data is being matched into it, we want to be there,” Choudhury said.
The company optimizes audience models for specific channel characteristics, delivering top-performing IP addresses for IP-targeting platforms and top-performing email addresses for email channels. This channel-specific optimization improves performance compared to generic audience rankings.
“You’re not necessarily targeting someone because they ranked well overall,” Choudhury said. “You’re targeting someone because of how they ranked relatively within the channel.”
