Public AI vs. Purpose-Built AI: Which One Delivers for Commerce Media?

The retail media boom shows no signs of slowing down. As larger investments pour into the channel, competition is heating up, pushing marketers to adopt more advanced strategies to stay ahead. Enter commerce media: a new approach that addresses the entire customer journey, from discovery to sale, using every available marketing tactic in the commerce funnel. Commerce media extends beyond retail media by blurring channel lines and integrating additional advertising touchpoints such as paid search and social advertising to amplify impact.

While commerce media builds on retail media’s foundation by incorporating broader marketing strategies, it also introduces new complexities. Marketers need support to navigate these challenges, and generative AI can help. Vendors across the digital advertising industry are increasingly introducing “AI solutions” to simplify commerce media and unlock its full potential.

You might already be in the evaluation process of finding AI to help you with your commerce media program. But — warning — not all AI is created equal. Choosing the wrong solution can lead to wasted resources, missed opportunities, and subpar campaign performance, leaving you behind the competition. Worse, the wrong AI may suggest optimizations that steer you away from strong performance by misinterpreting data or failing to account for key cross-channel dynamics. 

When evaluating AI solutions for commerce media, here are the five critical capabilities you should look for and some questions you can ask vendors to ensure you’re picking the right tool for your business.

Purpose-built for commerce media: AI designed for the job

Commerce media demands AI explicitly designed to handle its unique goals, challenges, and workflows. A purpose-built solution ensures that every insight, recommendation, and interaction is relevant to commerce media rather than being adapted from generic applications.

Commerce media combines the infinite intricacies of retail and advertising, meaning off-the-shelf AI tools won’t cut it. Purpose-built AI focuses exclusively on commerce-specific goals like iROAS, share of shelf, and sales velocity. By understanding commerce media’s hybrid nature — balancing retailer relationships, inventory management, and promotional strategies — this AI ensures no insights are lost in translation.

Also, unlike public AI, which may struggle to grasp commerce media’s nuances, purpose-built AI avoids distractions caused by metrics or terminology that aren’t relevant to this space. It’s also optimized for commerce-specific use cases, such as identifying high-performing SKUs, improving product discoverability, and addressing advertising constraints in real time.

A purpose-built commerce media AI also bridges the gap between the marketing funnel and operational realities. It ensures that recommendations are tailored to commerce media’s unique dynamics, helping marketers focus on what truly drives results. As Guy Cohen, Chief Product Officer at Skai, explains: “A purpose-built AI doesn’t just understand commerce media; it thrives on it, tailoring insights to the complexities of this evolving space.”

Questions to ask a vendor:

• How does your AI address commerce media-specific KPIs and challenges?
• Is your AI designed specifically for commerce media or adapted from a broader application?
• What commerce-specific use cases does your AI support?

Understanding commerce media data and metrics: uncovering meaningful insights

Commerce media requires an AI that goes beyond crunching numbers. It must understand the nuances of commerce-specific metrics—how they’re generated, what they represent, and how marketers interpret them.

Commerce media is data-rich, but raw numbers aren’t enough. AI must deeply understand metrics like ROAS, sales velocity, and share of shelf—not just their definitions but their implications. For instance, AI needs to account for the unique ways these metrics interact across channels, ensuring recommendations are grounded in a comprehensive understanding of performance.

Marketers rely on metrics to inform strategic decisions, but data sources can vary widely in quality and consistency. Purpose-built commerce media AI should flag inconsistencies, identify trends, and clarify complex data relationships. By leveraging historical data and understanding account nuances—such as seasonal trends and retailer dynamics—AI can uncover patterns that align with both immediate and long-term goals.

Incrementality remains a significant challenge, with only 23% of marketers rating their measurement proficiency as strong—underscoring the need for advanced AI solutions that contextualize data effectively.

Questions to ask a vendor:

• How does your AI handle nuanced commerce media metrics and their interdependencies?
• Does your AI flag anomalies or inconsistencies in retailer-provided data?
• How does your AI contextualize performance data to inform strategic decisions?

Integrated for speed and accuracy: seamless workflows

Integration is critical to streamline workflows, reduce errors, and improve time-to-insight and time-to-action. AI embedded in the platform ensures marketers can access insights where they’re most needed without juggling multiple tools.

Commerce media is fast-paced, and delays in insights or actions can be costly. An AI integrated directly into the campaign management platform eliminates inefficiencies caused by external systems or manual data transfers. This seamless integration ensures insights are not only generated faster but can also be acted upon immediately.

Moreover, integration fosters collaboration across teams. A unified platform enables campaign and analytics teams to work together without friction, reducing the need for back-and-forth. Familiarity with a single tool also minimizes the learning curve, empowering marketers to focus on strategy rather than platform navigation.

By streamlining workflows and reducing the risk of errors, integrated AI enhances both the speed and accuracy of decision-making, allowing marketers to stay ahead in a competitive landscape. As organizations engage with an average of 7 networks — expected to grow to 11 by the end of 2025 — integration will be key to managing this complexity effectively.

Questions to ask a vendor:

• Is your AI fully embedded in the campaign management platform, or does it rely on external systems?
• How does integration improve time-to-insight and time-to-action?
• Does your solution support seamless collaboration across campaign and analytics teams?

Cross-channel insights: connecting the dots for better decisions

Commerce media spans multiple channels. AI must interpret performance across all of them to provide accurate recommendations and ensure that results are viewed in the proper context.

Without cross-channel insights, AI may misinterpret performance. For example, attributing last week’s retail media success to the wrong factors if it’s unaware that search spending was significantly increased at the same time. This disconnected approach can lead to misguided recommendations.

A commerce media AI must bridge these silos, connecting data points from across platforms to offer a unified view of performance. This holistic perspective ensures that marketers can allocate budgets effectively, understand the true drivers of success, and prevent overspending in one area at the expense of another.

As Guy Cohen puts it: “Commerce media thrives when data flows seamlessly across channels. To unlock growth, marketers need AI that connects the dots and delivers clarity in a fragmented landscape.”

Questions to ask a vendor:

• How does your AI connect insights across multiple channels to ensure holistic recommendations?
• Can your AI identify when one channel’s performance impacts another?
• How does your AI adjust recommendations when cross-channel dependencies shift?

Real-time insights: acting at the speed of commerce media

In commerce media, the value of insights diminishes over time. Real-time AI ensures marketers can act on the freshest data to make agile, impactful decisions.

The fast-paced nature of commerce media requires marketers to act with precision and speed. Real-time insights empower them to address shifts in performance, inventory, or market dynamics as they unfold, ensuring decisions are based on the most relevant data. Without this immediacy, marketers risk missing critical opportunities or, worse, making adjustments that inadvertently harm performance rather than help it.

Using public AI requires marketers to output reports, upload them into the AI, and sift through the insights manually. By the time the necessary changes are made to the campaign, the opportunity may be over.

Meanwhile, integrated, purpose-built AI goes beyond timely updates — it drives proactive, real-time decision-making by identifying trends before they fully emerge. Whether reallocating budgets, refining bids, or addressing underperforming ads, these insights allow marketers to stay ahead of competitors and make impactful moves at just the right moment.

And especially during high-stakes periods like product launches or holiday peaks, real-time AI becomes indispensable, keeping campaigns aligned with evolving conditions. It also bridges gaps across traditionally siloed touchpoints, creating a unified view that ensures swift and informed responses. In today’s dynamic landscape, acting quickly isn’t just an advantage—it’s a necessity.

Questions to ask a vendor:

• Does your AI provide real-time or near-real-time (i.e., refreshed daily) insights?
• How does your AI help marketers respond to emerging trends faster than competitors?
• Can your AI flag critical changes, like inventory issues or performance dips, as they happen?

Conclusion: Don’t wait. AI is critical to commerce media success.

AI is changing the game across industries, and advertising is no exception. In commerce media, it’s redefining how marketers approach data, decision-making, and strategy, offering new ways to tackle challenges and drive results in a competitive landscape.

Now is the time to act. The rapid evolution of commerce media leaves no room for delay—marketers who adopt the right AI solutions today will gain a significant advantage, while those who hesitate risk falling behind. In a space this dynamic, speed and precision are non-negotiable.

This is uncharted territory for many. Even the most experienced marketers are navigating the complexities of evaluating artificial intelligence for the first time. But that shared challenge means we’re all learning together. With the right focus and the right tools, commerce media success is within reach. Stay tuned as we dive deeper into these critical capabilities to help guide you forward.