Mint Perspective E2 — Data Unification & Advanced Attribution Modeling

MediaMint and Snowflake share actionable strategies to help streaming leaders unify fragmented data systems, enhance audience targeting, and unlock superior ad performance.

Streaming platforms are entering a high-stakes era where data quality, speed of insight, and deep audience understanding directly determine growth. Yet, fragmented data ecosystems and attribution complexities are significant operational hurdles.

This blog synthesizes key insights from MediaMint’s conversation with Drew Holland (RVP, Solution Engineering, Snowflake) and Michael Kohn (VP of Growth, MediaMint) in the latest episode of Mint Perspectives, “Data Unification & Advanced Attribution Modeling: Strategies for Streaming Success”.

Watch the full episode:

Part 1: Building a Unified Data Foundation

Problem: Streaming platforms face significant challenges due to fragmented data. 

Michael Kohn detailed this complexity: “You might be working across 20-plus platforms, each with different definitions and regulations.” 

This results in inconsistent audience insights, fragmented privacy compliance, and limited cross-platform performance understanding. The inability to consolidate data across multiple platforms creates blind spots in audience behavior analysis.

Solution: Drew Holland highlighted the strategic approach of using Snowflake’s Data Cloud to address fragmentation:

“All your data—subscribers, ads, engagement—must live together. When it does, those blind spots disappear.” 

Drew further explained the ‘how’: Snowflake facilitates seamless data consolidation and integration of first-party and third-party signals within secure environments, enabling platforms to derive richer, actionable insights and ensuring compliance across diverse privacy regulations.

AI plays a crucial role here, Drew Holland explained, “Large-language models can spot hidden patterns in user behavior and spin up fresh traits, such as ‘likely to purchase’ scores, without manual feature wrangling.” 

 

Michael Kohn substantiated this with a practical impact: “What previously took weeks of data wrangling now happens in minutes,” dramatically improving campaign efficiency and effectiveness.

 

Part 2: Navigating Attribution Challenges in Streaming

Problem: Traditional digital attribution techniques fail in streaming due to the absence of direct call-to-actions (CTAs) and multi-device user journeys.

Michael Kohn emphasized this uniquely streaming challenge: “There’s rarely a direct call-to-action in streaming. People intend to act but don’t always follow through immediately.” This fragmentation in user behavior tracking often obscures the real impact of advertising campaigns.

 

Solution: Addressing this attribution complexity requires nuanced and layered attribution frameworks. 

Drew Holland outlined an effective strategy: “It’s not about a silver bullet. It’s about connecting dots between immediate signals and longer-term outcomes.” 

 

In practice, this involves combining immediate, real-time data signals for quick adjustments with broader attribution methods like multi-touch attribution and media mix modeling.

AI further advances these attribution frameworks. Michael Kohn explained precisely how AI addresses attribution gaps: “AI helps recognize patterns, linking streaming impressions to eventual user actions—insights impossible to surface manually.” 

 

Leveraging AI ensures attribution methods remain accurate, adaptable, and closely tied to meaningful business outcomes.

Part 3: Transforming Ad Experiences with Data and AI

Problem: Streaming platforms must continually balance viewer satisfaction with advertiser ROI. Poorly targeted, intrusive, or irrelevant ads negatively impact user experience and platform loyalty.

Solution: The panelists underscored the value of treating data as strategic intellectual property. 

Michael Kohn stated clearly, “Advertisers benefit significantly from deeper audience intelligence, enabling them to deliver smarter, more targeted ads.” 

 

He elaborated how platforms can proactively leverage data-driven strategies to predict and mitigate churn: “Staggering content drops or sequencing campaigns is no longer guesswork—it’s data-informed.”

Drew Holland projected a future with fewer but highly impactful ads, explaining: “Every extra ad is a risk. But the right ad at the right time boosts viewer experience and brand results.” 

 

Emerging AI innovations, such as generative AI used to test and optimize ad variations dynamically, ensure ads are context-aware and tailored to viewer preferences, significantly enhancing both viewer experience and advertiser outcomes.

Conclusion: Future-Proofing Your Streaming Data and AI Strategy

Toward the webinar’s close, Michael Kohn offered pivotal advice for streaming platforms looking to future-proof their strategies over the next 2-3 years: 

“Invest in your data foundation and embrace AI now—the sooner you break down those silos and start learning from your data, the better positioned you’ll be in the future.”

 

Echoing Michael’s insights, streaming leaders who prioritize unified data ecosystems and leverage AI-driven attribution and personalization today will dominate tomorrow’s landscape. Future-proofing isn’t optional; it’s strategic, achievable, and essential.

Missed the webinar? Watch the full conversation here or contact MediaMint and Snowflake to accelerate your journey toward streaming success.