Gary Burtka, VP U.S. Operations at RTB House shares a few very relevant thoughts on ad buying structures and the impact of AI in ad targeting trends in this chat with MarTech Series while also diving into RTB House’s latest marketing, martech and sales learnings:

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Tell us a little about yourself Gary…we’d love to hear about your role at RTB House?

There’s no typical day at work here for me at RTB House…I oversee a number of teams ranging from account management, to technical account management (engineering), to marketing and recruiting, BI and new products. On any given day I might start the morning out on an ops call with executives in Poland, talking about new products or new client tests, then I might interview for a sales role, then have a client call or QBR – all before lunch. So, throughout the day, I’m interfacing with many different teams, helping troubleshoot, ideate on problems, provide information – it’s really exciting, dynamic work!

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What are some top trends and predictions you’d like to talk about for marketing and marketing technology in 2021 – suited to the tech and B2B marketplace? Some key trends that have changed the path since the Covid-19 situation turned into a global pandemic last year?

I see a big movement towards context in 2021 – particularly in video ad formats like CTV and OTT. With streaming so prevalent, and being done on so many devices within the house, ads on services like Hulu are more engaging and relevant than ever. These platforms are using programmatic to determine what consumers are interested in, and utilizing context AI to make the ads more efficient. As more big brands buy into this concept and begin bringing their linear TV into OTT and CTV, we’re going to see more compelling ads, and ads that are more relevant to us as consumers within this format. 

Seeing how digital journeys are now the key channel for brand marketers to capitalize on, what best practices would you share when it comes to ad buying in today’s environment? 

One thing I like to get away from is trying to target based off of demographics, sociographics, trying to see who my target audience is – it’s a lot more powerful to find someone who is the market now, looking for my product now. A perfect example of this is myself: I’m a middle aged guy, so probably not in the target demographic for a wakeboard or skateboard company. But I enjoy extreme sports – and I buy a lot of skateboards! So while a human might disregard me as I’m out of the demo, if a context AI sees that I watch a lot of Tony Hawk videos and have bought a brand’s skateboards before, they might consider me a prime target for that brand’s premium skate products. But by just using demographics, that potential revenue is lost. 

We’d love to hear about some of the most innovative ways in which you’re seeing tech marketers use their martech stack today?

QSR companies are doing some really interesting things: using programmatic to target across regions and time zones to display different ads based to different regions. Using Panera Bread as an example, they might send coffee ads to Californians in the morning, while at the same time New Yorkers are getting lunch ads for grilled cheese and soup. Then as those east coast ads are rolling into dinner, the Californians might get those lunchtime ads. A similar test that we’ve been able to replicate is to use programmatic to address geo-differences in weather – a clothing retailer might show swimsuit ads to people in Florida while showing coats to consumers in New England. 

Take us through some of your most successful marketing and sales campaigns at RTB House during this time, a few key learnings?

We recently launched a large retailer who was heavily focused on performance. We started with a head-to-head test against one of our largest competitors, and we were able to achieve mathematically significant results to give us the win. So we became the only retargeter for this client, and began working with them up the funnel. I used to be convinced that upper funnel tactics might not work for retailers that are heavily performance-focused, but in the last few months, I’ve been proven wrong by this client and others like them. By creating a very specific target group for this client, we enabled them to “fill up the cookie pool.” Essentially, by using a stack of different campaigns working together, we were able to drive new users to the site, keep them engaged, and better retain them after their initial purchase. When these campaigns all work together, upper funnel tactics that drive new customers to the site have a powerful, measurable effect on the lower funnel. The key learning here is to not just hyper-focus on performance and lower funnel advertising, as the upper funnel is important as well! 

A few takeaways for marketing leaders in 2021: top factors they should keep in mind as they plan for the rest of the year?

The first takeaway is first party data – first party data is royalty. Make sure you’ve cleaned your stack up, make sure you’ve found partners that can incorporate your data, and can be actionable with that data. Not every AI is created equally, so ensure you have partners that can harness your data to be ready for the cookieless world. Secondly, measurability is changing, and now is the time to get ready for that shift. Post-cookies, it’s going to be harder to measure some of the performance of marketing campaigns. Conversely, OTT and CTV are making linear TV budgets more trackable and measurable than ever. So while you have less accountability on performance channels, you’ll be getting more accountability than ever on TV. 2021 is going to be an interesting year for marketing leaders, so staying informed on how channels are evolving will be crucial.

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