By Nanda Lella, Chief Technology Officer, Koddi
Everywhere you look, tech companies, commerce media networks (CMNs), and advertisers are touting AI capabilities that will “revolutionize” the space. Phrases like “enhanced targeting,” “automated campaigns,” and “personalized experiences” flood inboxes and conference stages alike.
These advancements are real and impactful, but the conversation often stops there—to our detriment. In 2025, merely using AI is not the goal; true success lies in performance. Commerce media networks must leverage AI specifically to deliver tangible, measurable business outcomes, such as incremental revenue growth and demonstrable ROI. If AI is indeed the best route to achieving these outcomes, let’s discuss it—but with greater clarity, rigor, and accountability. The industry must move beyond buzzwords like “relevance” and dig deeper into practical applications and results.
Commerce media networks with a true competitive edge in an ever-evolving market maintain differentiation with transparent, personalized, and performance-driven models. To prove your commerce media AI is more than just surface-level, here are three checkpoints that reveal its true sophistication (and ability to drive incremental revenue):
Optimize for incremental revenue, not just relevancy
Relevance is table stakes. If a shopper searching for “chicken” on a recipe page is shown an ad for a chicken plush toy instead of relevant grocery products, the AI has failed—not just at user experience, but at delivering meaningful value to the commerce media network and advertiser alike.
The real test of a sophisticated AI system is proving that it can drive outcomes that wouldn’t have happened otherwise. This measure of “incrementality” is what drives continual advertiser investment, and is a key outcome they want from CMNs. Many platforms optimize for clicks or even conversions—but those conversions might have happened organically. Without rigorous measurement, AI may just be accelerating inevitable purchases, not creating new value.
The philosophy for integrating AI should be centered around proving incremental sales. This requires AI that goes deeper than surface-level relevance, including:
- Sophisticated measurement: CMNs should implement rigorous methodologies, such as control/holdout groups and casual inference models, to isolate the true impact of advertising spend. This includes providing transparent reporting that clearly demonstrates this lift to advertisers, not just vanity metrics.
- Predictive modeling for value: CMNs should leverage AI to identify not just who might buy, but who represents a net-new opportunity, understanding factors like customer lifetime value, purchase propensity influenced by advertising, and the likelihood of organic conversion without an ad.
- Optimizing for profit, not just clicks: Bidding strategies and budget allocation should maximize profitable, incremental revenue, rather than simply chasing the highest click-through rate.
CMNs that integrate AI around incrementality unlock real growth—not only for advertisers, but for their own bottom line. When you can prove that your network drives sales that wouldn’t have occurred otherwise, you justify higher media value and secure long-term advertiser investment.
Maximize intelligence across omnichannel monetization
Too often, AI in commerce media operates in silos, optimizing on-site ads separately from off-site campaigns or in-store experiences. The industry today is experiencing real consequences as a result of this fragmentation: inconsistent messaging confuses consumers, optimization efforts in one channel can inadvertently counteract goals in another, and accurately measuring the holistic impact of media spend is nearly impossible. Connecting the digital shelf with off-site platforms and the physical store is no longer optional: it’s essential for delivering the seamless consumer experiences and marketing efficiency.
Intelligent automation and optimization connects the entire commerce journey, wherever it happens. Achieving this truly unified view demands a fundamental shift towards integrated technology platforms. The solution lies in leveraging intelligent automation capable of seamlessly connecting disparate systems – from on-site platforms and DSPs to in-store digital interfaces. Only through such sophisticated integration can commerce companies and brands hope to orchestrate cohesive campaigns, gain a holistic understanding of performance, and deliver the consistent, relevant experiences modern consumers expect across the entire commerce landscape.
For CMNs to achieve this, they’ll need to connect the path to purchase fluidly, crossing online and offline boundaries. Ad platforms act as the connective tissue, integrating disparate channels through smart automation:
- Seamless off-site activation: No more manual audience uploads and complex campaign mirroring. Sophisticated CMNs streamline off-site activation through intelligent integrations with major DSPs (like Google DV360, The Trade Desk) and platforms such as Skai. They automate audience synchronization and campaign setup, making off-site reach as manageable as on-site efforts.
- Bridging the physical divide: The customer journey doesn’t end online, where it’s “easier” to track. AI must use both online and in-store signals, enabling automated management and optimization of in-store digital media, from entrance signage and interactive end caps to checkout screens. This provides consistent messaging and leverages valuable first-party, in-store data signals.
- Unified omnichannel platforms: Top CMNs have an omnichannel core, providing AI-driven management and optimization across search, display, social, sponsored listings, and more. This unified view, powered by AI learning across channels, allows for smarter budget allocation and a holistic understanding of performance drivers.
By unifying the commerce journey through AI-driven tech, CMNs can intelligently automate connections between on-site, off-site (via major DSP integrations), and diverse in-store digital formats. With true omnichannel campaign management and optimization, CMN teams can streamline complex processes like audience synchronization and provide a unified interface, empowering internal teams and brands to finally execute cohesive, high-performing strategies across the entire commerce landscape.
Eliminate the AI black box: Build trust with transparency and control
Powerful AI is great, but not if it works like a “black box.” When advertisers can’t see why algorithms make certain decisions, for example, why bids change or budgets shift, it breeds distrust. Relying on AI shouldn’t mean giving up understanding or control–real partnership requires clarity.
That clarity starts with knowing how your campaigns are performing and why. This means reporting that’s easy to dig into, flexible, and offers real insights, not just surface numbers. It also means understanding how results like incrementality are measured. Proving ad spend drove new sales requires clear, trustworthy methods, like A/B testing, not just opaque claims.
Beyond seeing what’s happening, advertisers need levers to steer the AI. Automation is efficient, but it needs to align with specific business goals and market knowledge. For instance, advertisers may want to prioritize promoting seasonal inventory, influence AI-driven bidding strategies to align with high-margin product categories, or dynamically adjust targeting criteria based on regional market trends. The best AI platforms act as powerful tools that users can guide and tune, not as mysterious systems demanding blind faith. Control ensures the technology serves the strategy, not the other way around.
Giving advertisers transparency and control begins with CMNs relying on transparent tech, either through their own in-house efforts or with open partnerships. They need fast, flexible reporting tools that are designed for deep analysis right in the UI. And, they need control–from basic budget settings to advanced options for custom bidding logic and tuning core models–ensuring CMNs have the visibility and influence needed to trust and maximize their AI.
Real results, real revenue: AI in action
Sophisticated AI and transparent systems are foundational, but the ultimate measure of any commerce media technology is its ability to deliver tangible, quantifiable business outcomes. In today’s market, advertisers are rightly looking past the feature list and asking a harder, more important question: What tangible business results does this technology actually deliver? The focus has shifted decisively from theoretical potential to proven performance.
Improving efficiency metrics like ROAS or CTR is table stakes. While important, these gains don’t always tell the full story. The real differentiator lies in demonstrating incremental value– proving that advertising drove significant revenue that absolutely wouldn’t have happened otherwise. This is where many platforms fall short, often struggling to move beyond standard attribution to provide credible, quantifiable proof of true business impact across diverse clients and verticals.
The industry needs to move beyond vague success stories. Meaningful validation requires specific, documented evidence of performance lift tied directly to the technology. Platforms must commit to showcasing concrete examples – not just of optimized efficiency, but of substantial, measured incremental growth. This commitment to demonstrating real-world results is the foundation of trust and the ultimate measure of an ad tech partner’s worth.
Delivering these kinds of results consistently is the true test of AI in commerce media. Achieving outcomes like boosting ROAS by nearly 30% within a month, increasing homepage CTR by 20% through better ad quality prediction, driving over 100% increases in incremental bookings, or enabling 400% growth in revenue requires more than just standard AI; it demands a platform engineered specifically for measurable impact. These aren’t hypothetical goals; they are the concrete results forward-thinking platforms are achieving for their partners today.
Next steps for CMNs
AI must be more than a value proposition or marketing message–it should drive true business growth. CMNs ready to lead in this space must go beyond theory and take clear, measurable action. Start by aligning your AI investments with outcomes that matter: provable incrementality, full-funnel optimization, and transparent performance reporting. Prioritize tools and partners that empower you to unify omnichannel monetization, eliminate blind spots, and give advertisers both control and clarity. The technology is ready—now it’s about execution. CMNs that act decisively and deliver real results will be the ones that define the next era of commerce media.
