The AI Advertising Podcast: S1

Episode 8

AI, Personalization, and Privacy: Striking the Right Balance

Cover of the AI Advertising Podcast with Ned Dimitrov

About This Episode

Jun 18, 2025

Consumers expect personalized ad experiences, but they also demand stronger privacy protections. So how can advertisers deliver relevant ads while staying compliant with evolving privacy laws?

Ned Dimitrov | VP of Data Science, StackAdapt

Yang Han | CTO, StackAdapt

Carole Lawson | Chief Data Officer, MarketStorm

00:00

Transcript

Diego Pineda (00:00:00)

Consumers want relevant ads, but they also want their privacy protected. Can AI-powered personalization find the right balance?

Personalization is a cornerstone of modern advertising. AI has made it easier than ever to deliver hyper-relevant ads based on behaviour, context, and predictive insights. But with privacy regulations tightening worldwide, advertisers face a challenge: How do you personalize without overstepping boundaries? In this episode, we dive into: how AI is enhancing personalization in a cookieless world, the privacy risks and ethical concerns in data-driven advertising, and practical strategies for balancing personalization with compliance.

Joining us today are three industry leaders:
Ned Dimitrov, VP of Data Science at StackAdapt, on AI-powered contextual personalization.
Yang Han, CTO at StackAdapt, on privacy regulations and AI-driven targeting.
And Carole Lawson, Chief Data Officer at MarketStorm, on ethical data use and privacy-friendly personalization.

AI is rewriting the rules of advertising, but where should we draw the line? Let’s find out.

Podcast Intro (00:01:15)

Welcome to the AI Advertising Podcast, brought to you by StackAdapt. I’m your host, Diego Pineda. Get ready to dive into AI, Ads, and Aha moments.

Diego Pineda (00:01:30)

Personalization has always been a key advertising goal, but the way we achieve it is changing. With the decline of third-party cookies, brands are rethinking how they deliver relevant ads without tracking users across the web. Ned Dimitrov explains how AI-powered personalization is evolving.

Ned Dimitrov (00:01:48)

When you think about today’s people’s interactions with technology, it often happens on multiple browsers and multiple devices. Like you might see an ad in an app on your phone or while you’re browsing a website on your phone, and that ad might stick with you in your mind. And then later you might go to your laptop or your desktop and go and do the purchase.

And so cookies are fundamentally not useful in a situation like this because they can’t track the user across devices and across browsers. And the industry has had a long time shift towards these multi-device tracking capabilities that allow it to be more holistic in its approach to advertising performance and attribution. So one of the innovative products that StackAdapt has created is a tool that we call PageContext AI. So that tool allows an advertiser to specify an arbitrary niche context that they want their ads to appear in. So for example, let’s say that I’m Nike, and I want my shoe ads to appear on running shoe websites. So with our tool, you can specify running shoe context and the tool will look for all of the websites online that talk about running shoes and display the display the Nike ad at the running shoe website.

So this is a very contextual way of going about delivering ads because the ad is showing up on the website, not because of information that you have about the user, but because of the website’s content. That is there because the website talks about running shoes and not because of some interest that you’ve recorded about the user in running shoes. Now, this turns out, based on our data science studies, to be highly effective in getting the brand message into the user’s mind. Because they’re reading a content about running shoes, that Nike ad really sticks with them when they see it on the website. And so PageContext AI has had a really fantastic performance when it comes to conversions because it gets the brand message into the user’s mind, and then the user goes and converts later to purchase the product.

Diego Pineda (00:03:55)

Instead of tracking individual users, AI now analyzes page content, browsing context, and behavioural trends to match ads with the right audience, without relying on personal identifiers. This approach respects privacy while still delivering relevant ads based on context. But is AI-powered personalization enough? What happens when brands need more granular insights?

Diego Pineda (00:04:25)

While AI-driven personalization improves relevance, it also raises ethical concerns. Consumers are becoming more aware of how their data is used, and regulators are responding with strict privacy laws like GDPR and CCPA.

Yang Han (00:04:43)

Privacy regulations do vary depending on vertical or certain verticals like healthcare that are a lot more strict. And so brands have to navigate that a lot more carefully. It also depends on the geo and the jurisdiction in which these brands are advertising as well. um As a company at StackAdapt, we try to make this as easy as possible, so advertisers have to worry about it less because at the end of the day, our platform is responsible for doing the targeting in different jurisdictions. And so, for example, we try to understand when a brand runs a campaign, you know, what vertical are they running in? And then we see what geo they’re running in and we may provide different guidance essentially, or we may automatically do different things internally to make sure that we’re following all the guidelines when it comes to their verticals. So it’s very important for the brand to also understand what they can and can’t do and various limitations when it comes to their strategies. Ultimately, it’s also up to us to try to guide and educate our brands as much as possible as well.

Diego Pineda (00:05:42)

StackAdapt and other adtech platforms are implementing built-in privacy protections, such as: Geo-based compliance settings that adjust targeting based on jurisdiction; first-party data strategies that prioritize user consent; and automated safeguards that prevent data misuse. But privacy challenges don’t stop at regulation. Ethical concerns also come into play. Here’s Carole Lawson.

Carole Lawson (00:06:07)

As a matter of fact, we don’t use Google Analytics for that reason. So we use a platform called Netrix. It’s based in Matomo. And so people you know who are familiar with the different analytics platforms will understand that. But it’s total data ownership. We can do things with data. We can see data with more granularity because the data is owned.

When you’re thinking about privacy, you have to think about, what is going to happen to the data when this privacy plugin, for example, is implemented? And then are you going to say, well, why can’t I see people? Why can’t I see the cities people are from? That’s because the tool you’re using has blocked that. And so if that’s something that you need, you either need to find another tool within the law that still gives consumer choice, or you need to find a platform that can collect that information within the law. And so it’s a constant dance and it makes the data that we work with very difficult because you can’t report on what you can’t collect.

Diego Pineda (00:07:01)

This is a critical decision for brands. Some tools prioritize ease of use but come with privacy trade-offs. Others require more work but provide greater control over data. This raises an important question: Are there limits to how much personalization should be allowed?

Diego Pineda (00:07:22)

So where does AI-powered personalization go from here? Advertisers need new ways to tailor ads while staying compliant.

Ned Dimitrov (00:07:30)

So we’ve seen advertisers really care about the privacy concerns. There’s multiple ways to address this. So one way is through the contextual advertising that we talked about before, which basically doesn’t use any user data in the targeting. It just uses the website content. But the second way to do it is to make sure that the clients that you’re personalizing and collecting information for have opted into that information collection. So for example, laws like GDPR in Europe have various consent mechanisms where the user can say, yeah, it’s OK to personalize my ads. I prefer to get a personalized experience. And it’s important for advertisers and advertising companies like StackAdapt to follow those rules and those opt-in criteria to personalize the ads for the users that want that personalization.

Diego Pineda (00:08:22)

Opt-in strategies ensure consumers actively agree to personalized ads, creating a win-win for both brands and users.

Ned Dimitrov (00:08:29)

I think it’s very important to be compliant. Customers really care about their privacy, and that’s why we have these various privacy laws coming up in various geographic regions. But in addition, it’s just general bad business to invade the privacy of your future clients. It can make them unhappy and view your business in a negative way as opposed to a positive way.

Diego Pineda (00:08:54)

In the coming years, AI-driven personalization will focus on three key areas:
AI-powered contextual ads, targeting based on content, not personal data. Predictive modeling; forecasting behaviour without tracking individuals. And transparent opt-in personalization, giving users control over their ad experience.

Personalization and privacy don’t have to be in conflict. With AI, advertisers can deliver relevant ads while ensuring consumer trust and regulatory compliance.

Diego Pineda (00:09:27)

Three key takeaways from today’s episode:
One, AI-driven contextual targeting is a privacy-friendly alternative to third-party cookies.
Two, advertisers must balance personalization with ethical data use.
And three, transparency and consent are key to building consumer trust.

AI is redefining personalization, but it’s up to advertisers to use it responsibly.

Podcast Outro (00:09:52)

Thanks for listening to this episode of The AI Advertising Podcast. This podcast is produced by StackAdapt. Visit us at stackadpat.com for more information about using AI in your advertising campaigns. If you liked what you heard, remember to subscribe, and we’ll see you next time.