Expert Mode: The New Playbook for Performance Marketing in a Privacy-First World with Phoena Pang from Mintegral

The Mindset Shift: From Absolute Numbers to Confident Incrementality

The first and most significant hurdle for many marketing leaders is not technological but psychological. We have been conditioned to rely on absolute numbers and react to daily performance dashboards. In today’s landscape, that approach is a recipe for frustration and flawed decision-making. The new starting point, according to Phoena Pang of Mintegral, is a frank acceptance of our new reality.

“A lot of marketing leaders, they need to get comfortable with the confidence intervals rather than the absolute numbers they’re getting from their ad. Because evaluating the ROAS today, you need to require looking at aggregated trends… instead of reacting to the daily fluctuation in very subtle data.”

This is a profound shift. Moving from precision to probability requires leaders to manage expectations both within their teams and with the C-suite. The conversation must evolve from “this specific ad drove X conversions yesterday” to “this channel is demonstrating a positive lift of Y percent over our baseline this quarter.” This is where long-term incrementality testing becomes a core competency. By strategically turning channels on and off and measuring the resulting impact on overall revenue, sophisticated marketing teams are gaining a truer understanding of each channel’s contribution. It’s a less immediately gratifying process than checking a real-time dashboard, but it provides a far more durable and strategic view of what is actually moving the needle.

Creative Ascends: From Asset to Primary Targeting Lever

With less user-level data available for granular targeting, the role of creative has been dramatically elevated. It is no longer simply an asset to be tested and iterated upon within a campaign; it is now a primary driver of the targeting itself. The ad creative must do the heavy lifting of filtering a broad audience and attracting the right users—a task previously handled by algorithms fed a rich diet of personal data.

“Creative has a more important role… they should be the primary targeting. A lot of sophisticated ad marketers… are using the creative in three different specific ways. The first one… is the creative line signal generation, because when you cannot target by specific interests, so your creatives then will do the filtering.”

Pang outlines a three-pronged approach that advanced marketers are using. First is this idea of creative as a signal generator. By running broad campaigns where the visual and messaging hooks are designed to appeal to a specific sub-segment, the creative itself finds the audience. An ad featuring hardcore game strategy will naturally attract and engage users interested in that genre, providing the algorithm with valuable contextual signals about who is responding.

The second approach is a move toward macro-concept testing over micro-optimizations. Instead of A/B testing button colors, savvy teams are testing foundational emotional hooks. Does our audience respond more to a feeling of competition, stress relief, or achievement? Testing these core concepts provides much more valuable and scalable insights. Finally, diversifying ad formats is critical. Interactive formats like playable ads, which offer a mini-game experience, provide incredibly high-intent signals. A user who replays a playable ad multiple times is sending a much stronger signal of potential long-term value than someone who simply watches a video.

The Global Value Exchange: Not All Users Are Created Equal

The shift toward ROI-centric advertising and the growth of the open internet has fueled a rise in ad formats built on a clear value exchange, such as rewarded video and playable ads. These formats succeed because they create a win-win-win scenario: users receive an in-app reward (like an extra life or currency), publishers see higher user retention, and advertisers get to engage a highly receptive, high-intent audience. However, a one-size-fits-all global strategy for these formats is doomed to fail. User expectations and behaviors vary dramatically across regions.

“In Europe, we see… the users are more selective. So, they have a very strong preference for quality over the quantity… we want to make sure they’re very high production quality. Otherwise, it will cause a higher turn rate… European user, they’re more willing to pay for premium ad-free experience once they’re hooked.”

Pang’s global perspective reveals critical nuances. In many APAC markets, which are digital-first, users have a high tolerance and engagement rate for rewarded ad formats, as the “rewards economy” is deeply integrated into their daily app usage. In North America, users value brand familiarity and convenience; they will complete rewarded ads but have low patience for long load times and respond well to free trial offers. In Europe, the emphasis is on quality over quantity. Users are more selective, expect high-production ad creative, and are uniquely willing to pay a small fee, such as $0.99, to remove ads entirely once they are invested in an app. For enterprise leaders, this underscores the necessity of empowering regional teams to tailor both creative and monetization strategies to local cultural norms and user expectations.

Demystifying AI: From Black Box to Strategic Accelerator

AI in user acquisition can often feel like an impenetrable black box. It works, but we don’t always know why. Pang suggests that demystifying AI is less about guessing and more about understanding that its primary function is pattern recognition. For user acquisition, AI is most impactful in two key areas: value-based bidding and LTV prediction. Value-based bidding uses post-install signals—a user making a purchase, completing a tutorial, or engaging with an ad—to identify what she calls “whale behavior.” The algorithm then learns these patterns and predicts which new users are most likely to exhibit similar high-value actions, bidding on them accordingly. This is a far cry from a simple cost-per-install (CPI) model.

The balance between human strategy and machine execution is particularly crucial when it comes to creative automation. The fear that AI will replace creative teams is misplaced. The ideal model is a symbiotic one where humans and machines each focus on what they do best.

“Human should define the soul, which is the emotional hook and also, how you gonna set your brand strategy. Like, what’s your brand? What’s the story? All of those things, it should be defined by human. But then the AI should be handling the skill. So you can generate thousands of the variations and also all the adoration, all the AB testing.”

In this framework, the marketing and creative teams are responsible for the core strategy—the “soul” of the campaign. They define the emotional hooks, the brand narrative, and the core concepts to be tested. The AI then takes these strategic inputs and handles the “skill”—the massive-scale generation of variations, the automated A/B testing, and the continuous optimization based on performance data. For leaders, this means the critical investment isn’t just in AI tools, but in the talent and processes that can effectively bridge the gap between creative strategy and data-driven execution.

Navigating the new terrain of performance marketing requires a fundamental evolution in leadership. The era of absolute certainty is over, replaced by an era that values strategic direction, creative intelligence, and a deep understanding of probabilistic impact. Success is no longer found in simply out-bidding a competitor on a specific keyword or audience segment. It is found in building a resilient system that embraces aggregated trends, empowers creative to be a targeting engine, and respects the nuanced expectations of a global user base.

The most critical investment a marketing leader can make today is in what Pang calls “open internet diversification.” This means developing the capabilities—smart bidding strategies, sophisticated creative testing frameworks, and robust data analysis—to effectively engage users beyond the walled gardens of traditional social platforms. The user’s attention is more fragmented than ever, scattered across countless apps and digital experiences. The brands that will win are not those still mourning the loss of old signals, but those actively building the strategies and skills to capture attention and drive growth in this complex, dynamic, and ultimately more interesting new world.