How Buyers Actually Find Brands Now
Telling teams to "use AI" doesn't produce results. Damien Voita is Principal Campaign Manager at AdRoll, with nine years of agency and in-house experience in paid media and integrated campaign strategy. He explains why leaders must define what an effective AI outcome looks like before asking teams to experiment, and why a clear target, such as producing more output or working faster, is the first step. He also makes the case for framing AI as automation of a specific process, so the work makes the business more efficient.
- Part 1Why Q4 Discovery Now Starts In September
- Part 2 How Buyers Actually Find Brands Now
Episode Chapters
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01:25: Step Two Between AI and Profit
Telling a team to "use AI" without a defined vision or outcome leads to head nods in the meeting and no real action. Leaders need to get specific, such as asking for more output or faster turnaround, to make AI adoption worthwhile.
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02:26: Replacing "AI" With "Automate"
Reframing AI as a way to automate processes ties its use to making the business more efficient rather than using it for its own sake. The hype that once lifted stock prices has passed, and a clear reason for using it is now needed.
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02:59: Vague AI Mandates Shorten Workdays
Without specific goals, knowledge workers may use AI to finish in one hour what used to take three, simply shortening the day. The productivity gain is hard to prove or capture when expectations stay undefined.
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Episode Summary
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How Buyers Actually Find Brands Now: Why "Use AI" Is Not a Strategy
Introduction
Damien Voita is Principal Campaign Manager at AdRoll, a multicha el advertising platform that helps mid-sized brands run full-fu el campaigns across the open web. He brings nine years of agency and in-house experience across B2B and B2C, which gives him a practitioner's view of what actually changes outcomes versus what just sounds good in a pla ing meeting. His conversation with Benjamin Shapiro closed with a lightning round that cut straight to a problem most marketing leaders are living with right now: leadership says "use AI," the team nods, and nothing happens. -
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The Missing Step Between the Mandate and the Margin
Voita's framing comes from a LinkedIn post he wrote referencing the South Park underpants gnomes, whose business plan famously skipped step two. He sees the same gap in AI adoption. Executives a ounce that the organization needs to be using AI, but they rarely define what a successful outcome looks like or which work should change as a result. As Voita put it, "If you don't have a vision of what that should look like or what an effective outcome would be, how do you expect all the people who work for you to take time from what they're already doing and go experiment and figure this out?" -
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Be Specific About the Output You Want
The fix is not more enthusiasm. It is a clearer ask. Voita's recommendation is to pair any AI directive with a concrete target, such as producing a specific number of additional campaign variants or compressing a pla ing cycle by a defined amount. That turns a vague cultural mandate into a measurable operational goal. Without it, he warned, "that's going to get head nods in the meeting, everyone says yeah okay cool, and then nothing's going to happen." -
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Replace "AI" With "Automate"
Shapiro's reaction was a useful reframe for anyone writing a MarTech roadmap. He suggested marketers swap the word AI for automate whenever they talk about adoption. The question stops being "are we using AI" and becomes "which process are we automating, and what does that do for the business." That shift also filters out AI theater. A year ago, mentioning AI in a quarterly filing moved a stock price. Now, the only reason to deploy it is that it makes a specific part of the business faster, cheaper, or better. -
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Tie Every Tool to a Workflow
For marketing operations teams, this means evaluating AI features the same way they would evaluate any other piece of the stack. Identify the workflow, name the bottleneck, define the metric that should move, and then decide whether the tool earns its place. That discipline matters more than ever as nearly every vendor has bolted an AI label onto their product. The problem is the same one that drives stack sprawl: collecting tools instead of solving problems. -
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The Productivity Leak Nobody Is Measuring
Voita raised a second consequence of vague AI mandates that most leaders have not considered. If a knowledge worker uses AI to finish in one hour what used to take three, and there is no stated expectation for what happens with the reclaimed time, the most likely result is a shorter workday rather than more output. He acknowledged he has no way to prove how widespread this is, but the logic is hard to argue with. -
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Decide Where the Saved Hours Go
This is a resourcing decision, not a surveillance problem. If a campaign team automates reporting or creative versioning, leadership should know in advance whether that capacity goes toward more testing, more cha els, deeper audience work, or something else. Pairing the mandate with a destination for the saved time is what converts efficiency into growth. Otherwise the gain quietly evaporates. -
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Conclusion
The takeaways are straightforward. First, never issue an AI directive without defining the outcome you expect. Second, talk about automation, not AI, so every initiative is anchored to a real process. Third, evaluate AI features with the same rigor you apply to any MarTech purchase. Fourth, decide upfront where reclaimed time should be reinvested. Voita's point is that AI only produces profit when leadership supplies step two. For marketing executives heading into a busy season, that clarity is the difference between a tool that sits in the stack and a capability that compounds. -
- Part 1Why Q4 Discovery Now Starts In September
- Part 2 How Buyers Actually Find Brands Now
Up Next:
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Part 1Why Q4 Discovery Now Starts In September
Holiday demand compresses into a few weeks, which makes late-season ad spend inefficient. Damien Voita is Principal Campaign Manager at AdRoll, with nine years of agency and in-house experience in paid media and integrated campaign strategy. He covers a three-phase measurement model that moves from platform metrics like CTR and CPM to branded search impressions to year-over-year CPA comparisons. He also explains how to shift budget into open web channels like CTV, native display, and audio, and how to build third-party validation that LLMs recognize. Finally, he outlines how to pitch brand investment to a CFO as a way to lower CPA and then shift to retargeting before shipping cutoffs.
Play Podcast -
Part 2How Buyers Actually Find Brands Now
Telling teams to "use AI" doesn't produce results. Damien Voita is Principal Campaign Manager at AdRoll, with nine years of agency and in-house experience in paid media and integrated campaign strategy. He explains why leaders must define what an effective AI outcome looks like before asking teams to experiment, and why a clear target, such as producing more output or working faster, is the first step. He also makes the case for framing AI as automation of a specific process, so the work makes the business more efficient.