AI can’t make a good ad. Or at least, it can’t make one from scratch. Too many important details will be altered, distorted or missing altogether. Brands need their logos to remain intact, and they require their products to be accurately represented. The sizing must meet the brand’s requirements and the context in which the ads are displayed.
Generative AI is simply not up to the task.
The problem is that Commerce Media could greatly benefit from using AI to overcome creative barriers. Scaling a campaign is particularly costly when you consider the needs of commerce media advertising. In addition to the brand requirements mentioned earlier, you must also contend with the complexities involved in advertising across multiple retail media networks (RMNs).
“In commerce, media retailers have very specific requirements of what you can and cannot do with their proprietary formats and sizes (…) and then, of course, the brands themselves want their font, their logo.” — Jivox CEO and Founder, Diaz Nesamoney.
The Generative and Agentic AI Combo to Tame Commerce Media Challenges
Jivox just launched DaVinci Commerce—the industry’s first AI-native personalization platform for commerce media. With DaVinci Commerce, the goal was first to solve the problem of creative production in commerce media and then to reduce the time to launch.
“How do we reduce a campaign launch—about 40 to 60 days, believe it or not—down to a couple of minutes. And I believe we did achieve that.” — Diaz Nesamoney.
A Refresher on Commerce Media Challenges
- Advertising across multiple retail media networks (RMNs) adds complexity to commerce media advertising.
- Brands have to produce ads that meet their own specifications and the requirements of each RMN.
- The retailer approval process can slow campaign launch to a crawl with frequent back-and-forth between the brand and the retailer/commerce entity.
- Campaign latency makes deep personalization nearly impossible.
To produce a creative that passed a gauntlet of requirements, Diaz quickly realized that they needed to utilize a combination of generative AI and agentic AI.
What Is The Difference Between Agentic And Generative AI?
Generative AI can perform a task when prompted, but it can’t work independently of human requests. Agentic AI, conversely, is an autonomous agent that can work out the steps required to achieve a goal. It operates more like a human employee rather than simply responding to prompts from a user.
See more definitions in our Commerce Media Marketing Glossary >>
Agentic AI, much like a human, can analyze a creative brief, use existing assets, activate generative AI to produce images and then check against a retailer’s guidelines. The platform leverages existing assets and information that can be combined with generative AI images. Not only do you get ads that meet internal requirements, but they also have a much higher likelihood of passing retailer approvals.
How DaVinci Commerce Continually Adapts And Learns When Retailer Requirements Change
Jivox has bespoke relationships with retail media networks, so that the DaVinci platform is continuously updated with retailer requirements. In the future, this process is likely to be automated between AI agents, allowing for immediate implementation without human intervention.
How To Avoid AI Ad Slopification
As mentioned above, the platform is using a combination of agentic AI and generative AI to address commerce media’s unique challenges with scale. What hasn’t been mentioned is that DaVinci Commerce utilizes a templated approach.
“The brand logo, the retailer logo, are in the template. They’re baked into the template, and they’re not changeable by AI (…) the product image and the product content are not changeable.” — Diaz Nesamoney.
Brand Consistency: Generative AI is adept at creating lifestyle images and other visuals that alter the context of the ad, which is crucial for efficient personalization. However, the brand logo and product, for example, cannot be changed by gen AI. This helps maintain brand consistency while meeting a retailer’s requirements.
Using templates and AI, DaVinci Commerce can very quickly produce compliant ads. A process that typically takes months is now completed in minutes.
Is True Personalization Possible in Commerce Media?
Commerce media introduced a few exciting opportunities for marketers that have helped it grow rapidly in the last few years. The initial offering focused on hosting ads near the point of purchase, typically on a retailer’s website. This is how commerce media began. However, the larger potential lies in the transaction data that commerce media has.
“I always thought of retail media as a data product.” — Diaz Nesamoney.
Granular Audience Targeting: Personalization at the category level is somewhat limited. Still, when transaction data is added to the mix, the level of personalization becomes much more detailed and more reliably relevant to the consumer. Having access to this data is a significant performance enhancer, allowing for the efficient generation of creative content with AI and templates. Without these key efficiencies, it wouldn’t be possible to utilize Commerce Media’s first-party data fully.
Is Handing Over So Many Marketing Tasks to AI Risky?
With agentic and generative AI working in tandem, many of the risks associated with AI use are heavily reduced. However, the technology isn’t perfect, and mistakes need to be prevented.
Humans in the Loop: DaVinci Commerce platform avoids AI risks by keeping humans involved at every stage. A human is always checking the work and approving the template, for example.
However, before personnel do their review, agentic AI has already conducted some checks of its own. An AI compliance checker has already reviewed the ads generated to make sure they will pass retailer inspection, increasing the odds of approval.
Legal Compliance Bottlenecks: Some ads are subject to more scrutiny than others. There are legal compliance issues involved in the pharmaceutical industry, for example. The copy must be accurate and specific, in accordance with regional rules and regulations.
“Alcohol advertising is not allowed by most retailers. If somebody inadvertently shows a whiskey bottle in the background, we can tell the foundation models not to allow that kind of content generation.” — Diaz Nesamoney.
Whenever you need to involve a legal team, it significantly slows down the launch of a campaign. However, with a compliance checker tool taking a pass first, you can speed up the time it takes for a legal team to assess the ads. There will be less back and forth between teams with fewer errors made.
The Results Of Using The Agentic And Generative AI Tandem In Commerce Media
In commerce media advertising, you have to produce ads in many different proprietary formats, and also for multiple retail media networks. Some brands have dedicated entire teams to individual RMNs just to handle the workload. When you use AI to automate most of the process, you save significantly on production costs.
Cost Reductions: For a large alcohol brand, DaVinci Commerce achieved a 76% reduction in production costs. That’s a significant, immediate and very measurable return.
Personalization is Back: Since production costs were previously very high, advertisers largely skipped personalization at the SKU level. However, now that production costs are so low, this level of addressability poses no significant financial burden. On the other end, however, there’s a performance lift anywhere between 30 and 50%.
Are We Headed Toward a Future of Fully Self-driving Campaigns and Agent Buyers?
AI Is Not Driving Itself Just Yet: While platforms like DaVinci Commerce involve a lot of AI, Diaz believes we’re still quite far away from self-driving campaigns. A lot of trust still needs to be earned from AI before it completely takes over the driver’s seat.
“Mark Zuckerberg said, ‘By 2026, you’ll be able to push a button and then it’ll just create the ad for you and launch it. That’s a bit of a scary proposition, frankly, if you ask me.” — Diaz Nesamoney.
The Gift of Shopping Agents: However, agentic commerce is a promising concept for the time being. While it won’t entail shopper agents magically making all your purchases for you anytime soon, they will automate a significant portion of the buying process and offer something very valuable that’s currently missing from online shopping: discovery.
Shopper agents will give consumers a sense of discovery through conversation, much like talking to a sales clerk in a store who has memorized their inventory levels. That will be a highly positive development for both consumers and brands.
You can listen to the full interview on the CPG Guys Podcast.