Expanding Addressability with Direct Access Data Match

In the era of continued third-party signal loss, first-party data has taken priority. And it makes sense: First-party data is more verifiable and thus supports improved ad reach and measurement. However, accessing quality first-party data can often be a complicated and costly process. 

That’s where our Direct Access solution comes in.

To understand how Direct Access and the recent expansion of the solution, Data Match, helps streamline publisher and advertiser relationships for more seamless data sharing, we sat down with Viant Vice President of Business Development Robby Barnett. 

Q: Robby, let’s talk a little bit about Direct Access before we get into Data Match. Can you share what our Direct Access solution is and why it’s been so important for agencies and advertisers?

Direct Access focuses on developing optimal inventory and data connections with the leading media owners in programmatic advertising. From a holistic standpoint, the integration of Direct Access within our suite of solutions — ViantAI, our Data Platform, DSP and Advanced Reporting — drives a more seamless media planning, execution and measurement process for agencies and advertisers, and also takes Viant closer to our vision of AI-powered Autonomous Advertising. 

Also, a quick note on AI and Direct Access: Effective AI relies on quality data, and Direct Access plays a crucial role in getting us there.

Q: OK, now on to Data Match — can you tell us what this expansion to our Direct Access program does?

Data Match is a new branding effort, but it’s a solution we’ve been focused on for years.

Data sharing across marketers, platforms and media owners still largely remains inefficient within an opaque process; there’s a reason supply path optimization has been such a hot industry topic. Given the significant benefits of using first-party data for personalization and measurement, with Data Match we’ve concentrated on reducing the friction so common today between advertisers and publishers, while improving data fidelity and transparency. 

In terms of how Data Match works: with each partner, we set the groundwork for a flexible data-sharing framework and co-develop a shared identifier that aligns with our approaches to privacy. The identifier is then used to inform bidding, forecasting and measurement.

I also want to note that when considering privacy —  perhaps one of the biggest challenges in digital advertising today — as a design principle, we consistently came back to flexibility as a dependency, given variable supply policies across legislation, brands and platforms. We believe our approach not only fits today’s privacy climate, but is modular enough to take us into the future.

Q: Why is it important for marketers to capture contribution versus just last-touch attribution?

Last touch and contribution don’t have to be mutually exclusive, and there’s an argument for both. However, what’s most important is that advertisers see the full picture to inform their overarching marketing perspective. We hope that advertisers can consider the interplay between formats seen within the open internet, and apply the learnings across other areas of their media investment that are limited in terms of insights, such as walled gardens.

Q. Can you provide an example of how Data Match can help agencies and advertisers?

Outside of improving all Viant services where identity is a consideration (forecasting, frequency capping, measurement, optimization etc.) being able to upload a CRM list into our platform at no cost and instantly have a scaled 1:1 match with the largest streaming partners in the US should not be understated. 

Q. Lastly, how do you foresee Direct Access and/or Data Match evolving in coming years?

While the industry is rightfully focused on improving the way adtech approaches targeting and personalization, we believe there’s an opportunity to help media owners and advertisers collaborate across their datasets more effectively to help inform planning and take measurement further.