AI Marketing Innovation and Content Effectiveness

(0:01)

Welcome back to another edition of AI Insiders from the AI Marketers Guild. Great to see everyone here!

Today, we have a guest speaker I’m really excited about—someone I’ve always enjoyed geeking out with, especially as we’ve gone deeper into AI. We had a great conversation this morning, and I can’t wait to share it with a wider audience.

There aren’t many people with deep expertise in building technology and using it to grow agencies. Our guest has seen the evolution of agencies from the early days to now—how they’re embracing or resisting the latest developments.

He recently delivered one of the biggest keynotes at CES, hosted by Shelley Palmer, and is a highly sought-after entrepreneur and speaker. Please welcome Kevin Wassong. Kevin, I’ll let you introduce yourself, but it's great to have you here.

(01:33)

Kevin Wassong:
Thanks, David! I really appreciate it. It’s great to see how the AI Marketers Guild has evolved, and I recognize a lot of familiar faces here. Thanks to all of you for taking the time to listen.

I encourage anyone to interrupt with questions at any time—I’d love to keep this conversational.

This topic is important to me, so I’ll start with a quick background for those who may not know me.

I’ve been in the industry for a long time. Some of you may know my name, some may not. I’ve founded multiple companies, starting in digital marketing. I moved back to New York in 1995 to work for Cliff Freeman & Partners, where I pitched and won the Prodigy business.

One of my early experiences in digital was a call from Mike Ilitch, the founder of Little Caesars. He told me a franchisee had put up a “website” and insisted we shut it down immediately. Curious, I checked it out—dialed up with a Prodigy disc and saw an early animated GIF: a spear hitting two pizzas, flipping them in the air. It was a brilliant execution. Instead of taking it down, I told Ilitch that he should share it with every franchisee.

From there, I worked on digital innovation at Lowe Partners, built the first Mercedes-Benz kiosk touchscreen system, and developed SBE’s first website and online auction with Radical Media. Later, at JWT, I started their first digital division in 1998, where we built technology platforms and digital experiences.

After JWT, I co-founded one of the first consumer fintech brands. My last company before this was One Mobile, the first mobile advertising services group for the U.S. broadcast industry. That company was later sold to Nexstar Broadcasting as part of a roll-up of independent broadcasters.

That experience gave me a firsthand look at the rapid evolution of technology. I remember an early meeting with Mark Themann, then head of mobile at Google. I asked how many engineers they had—he said 12 or 15. I had 8 at the time, and I felt pretty good. A year later, I asked him the same question—he said 1,500. I still had 8. That was a wake-up call about the pace of change.

I’ve worked with CMOs, built organizations, and stayed immersed in this space. I believe we’re living through the third transformational technology movement of our careers. First, there was the internet. Second, social media. Now, we’re in the AI era.

(05:31)

My current company, mktg.ai, is based on a domain I bought over a decade ago. I originally tried to build it with IBM Watson’s team in 2016, but the technology wasn’t there yet.

A quote from MasterCard’s CMO recently stuck with me:

"The number of places where brands need to show up has exploded, but most marketing organizations are still using fragmented tools to manage them. This causes inefficiencies, inconsistencies, and ultimately lost opportunities."

This reflects the key challenge we’re addressing.

We obsessively measure media, but creative is what truly drives performance. Advertising has always been a balance of storytelling and science, yet most measurement is focused on media. Moreover, it’s analyzed in vertical silos rather than holistically.

(06:37)

With the rapid rise of AI—especially generative AI—each major platform is designing its AI to improve its own ecosystem.

• Gemini improves Google.
• Grok improves X (formerly Twitter).
• Meta AI improves Facebook and Instagram.
• Microsoft AI enhances their suite.

Brands often talk about data lakes, but these platforms are actually data oceans. OpenAI, for instance, has been reading the internet since 2015, which required massive capital investment.

Over the last 20 years, we’ve seen a 300% increase in marketing channels. That’s overwhelming for marketers. An investor once told me, "Your industry suffers from the problem of 'too many'—too many platforms, tools, data sources, reports, and dashboards."

AI is the best solution to this complexity.

(08:20)

Unlike traditional approaches, we analyze creative horizontally—across all channels, digital and non-digital—rather than in isolated silos.

Marketers typically view performance through charts and graphs (Tableau, Data Studio, Excel), yet many large brands still rely on Excel as their primary source of truth.

Even some of the biggest sports leagues still analyze team performance using Excel sheets and Power BI. That’s insane.

The problem is clear:

• We’re constrained by budgets.
• We’re constrained by resources—most companies are scaling back, not hiring more.
• We’re constrained by time—yet the volume and velocity of content keep increasing.

With AI, we can finally analyze and optimize creative at scale.

(11:00)

At mktg.ai, we built an AI-driven platform that aggregates creative assets into one searchable, horizontal view.

• It analyzes real-time performance across all channels.
• It extracts insights to improve creative execution.
• It’s non-disruptive, integrating seamlessly into existing workflows.
• We even have a provisional patent on using color to normalize performance data.

Marketers can now instantly see what’s working and what’s not.

We launched our first client in May 2024 and signed a major client just this morning. The response has been incredible.

(13:51)

To put the power of AI in perspective, we beta-tested with a retailer that has 1,100 stores. We integrated their Meta account.

Any guesses on how many creative assets they had?

The answer: 5 million.

No human team can analyze 5 million assets. Our platform does it instantly. We can isolate patterns, compare Black Friday campaigns over years, and avoid repeating past mistakes.

(26:28)

Our next step is integrating AI-powered predictive modeling. Marketers will be able to ask:

"What were the best-performing Black Friday ads over the last five years?"

The system will instantly pull the top assets across all platforms. This will transform campaign planning and creative strategy.

(26:28)

Our next step is integrating AI-powered predictive modeling.

Marketers will soon be able to ask questions like:

• “What were the best-performing Black Friday ads over the last five years?”
• “What ads resonated most with 25- to 34-year-old women in Chicago?”

The system will instantly pull every relevant asset across all touchpoints to help marketers identify patterns and make informed creative decisions.

Even further, we aim to integrate generative AI to suggest high-performing ad variations based on historical data. Imagine uploading creative concepts and having the system predict their effectiveness before they even launch. That level of insight will revolutionize how marketers brief their teams and optimize campaigns.

(28:10)

Audience Question (Max Tarter):
"Your performance metric examples focus on media metrics like engagement. Are you incorporating real business outcome data, such as brand perception or sales?"

Kevin Wassong:
Great question. We’re already integrating Google Analytics, which provides conversion data. Additionally, platforms like Meta and Google feed conversion metrics back into our system.

We’re also in the process of integrating Shopify, Salesforce, and other CRM systems to provide deeper business impact insights. The goal is to correlate creative performance with actual sales and customer behavior.

Some companies are hesitant to share proprietary data outside their firewalls, so we offer an enterprise solution that allows them to install our system within their own cloud environments, whether that’s Azure, AWS, or Google Cloud.

(29:52)

Audience Question (Aen):
"If a client has proprietary data like a brand tracking study, can that be incorporated?"

Kevin Wassong:
Absolutely. Our system allows clients to append additional metadata to creative assets. For example, if you conduct an attitude and awareness study, you can tag all related creative within our platform.

Most marketers run these studies, get results, then store them in a folder that no one revisits. We want to make that data actionable by integrating it into the creative optimization process in real time.

(31:00)

Audience Question (Jean):
"Creative is far more important than media targeting. Studies from Comscore and Nielsen show that good creative is four times more impactful than media targeting. But using AI to optimize old-school IAB-style banner ads may not be the best approach. The IAB ad standards were set in 1999 and haven’t changed. Browser screens are now four times larger, and static banners are losing effectiveness. So, how much does this solution cost?"

Kevin Wassong:
You raise a great point. Personalization is a big buzzword, but bad ads that are personalized are still bad ads.

Regarding cost, we use a flat licensing model, with no seat-based pricing. We want everyone in a marketing organization to have the same view, avoiding inefficiencies caused by siloed teams.

By the way, I actually helped create one of the IAB standards in 2012—the responsive square. Back when I was running One Mobile, we asked, “Why can’t an ad dynamically resize to any screen?” It’s surprising how little has changed.

(33:19)

Audience Question (Jean):
"I work at Responsive Ads, where we focus on aspect-ratio-based designs instead of fixed-pixel ads. That allows creative to dynamically fill different slots. I see potential synergy here—our clients would likely pay extra for insights from your system. Would you be open to a partnership?"

Kevin Wassong:
Absolutely. Let’s connect offline and discuss.

One of the most significant studies on this was from Nielsen last year. They found that real-time creative optimization can increase ROI by 20-30%. That’s a massive lift—far beyond what you’d get from better media targeting alone.

The fundamental truth is: there are only two ways to improve marketing performance:

1. Be more efficient (reduce costs, improve workflows).
2. Be more effective (make better ads that resonate).

Our platform helps with both.

(35:57)

We’ve intentionally gone direct-to-client out of the gate. Agencies have high turnover—marketers switch agencies, CMOs change every two years, and media strategies constantly shift. But creative intelligence should stay with the brand as part of its long-term DNA.

One of our clients, a financial services company, has over a decade’s worth of creative data in our platform. That means they can go back and analyze what worked, avoid repeating past mistakes, and build smarter campaigns.

For retailers, it’s a game-changer. Imagine pulling up five years of Black Friday ads, across every channel, to see what performed best. No more guesswork—just data-driven decisions.

(38:41)

Audience Question (Karen):
"Can you track competitor ads?"

Kevin Wassong:
Not directly. We don’t scrape the internet like OpenAI or Grok. However, as we onboard more brands, we’re gaining a broader category-level view. Over time, this will allow us to provide competitive insights, even if we’re not directly pulling competitor data.

Our goal is to brief marketers on what types of creative work best within a given industry, rather than generating creative itself.

(40:58)

Audience Question (Max):
"Have you considered an API partnership with Nielsen?"

Kevin Wassong:
Great suggestion. Right now, we’ve been entirely self-funded and haven’t raised capital yet. That means we’ve had to prioritize our API integrations carefully.

We’re currently integrating into the Google AI Startup Program and entering the Google Cloud Marketplace. But as we scale, a Nielsen partnership is something we’d be very interested in exploring.

(41:33)

Audience Question (Todd):
"How do you account for targeting variables? If an ad performs poorly, it might not be the creative—it could be bad placement or audience mismatch. How does your platform account for that?"

Kevin Wassong:
Great point. Right now, we don’t attempt to out-optimize individual platforms. Meta, Google, and others have powerful data tools for targeting.

However, we do capture gender, geo, and age data to provide directional insights. Over time, as we gather more data, we’ll be able to analyze how targeting variables impact creative performance.

(43:09)

Audience Question (Jean):
"I like that you’re going direct-to-client. Agencies often lack transparency. Will you maintain that direct-to-client approach?"

Kevin Wassong:
Yes, our contracts are always with the brand, not the agency. If an agency manages a client’s platform, they can still use it, but the client owns the data.

We’ve also launched a Pioneers Program specifically for SMBs. Most small businesses don’t want to stay small—they want to grow into major category players. This program helps them build a scalable, data-driven marketing foundation from the start.

(47:06)

Kevin Wassong:
That’s everything I wanted to cover today. If you’re interested in learning more, you can reach me at kevin@marketing.ai.

David, I really appreciate the opportunity to speak here. What you’ve built with the AI Marketers Guild is incredible—it reminds me of the early days of the IAB.

(47:42)

David:
Thanks, Kevin! This was fantastic. We’d love to have you back to share more insights as your platform evolves.

Also, if you come across cross-brand findings that can help educate marketers, let’s share those with the Guild.