How Advantage+ Dynamic Product Ads Are Changing Facebook Advertising for eCommerce Brands

It wasn’t long ago that social advertising was all about targeting: Facebook and Instagram campaigns sank or swam based on how well you knew your audience and the combination of factors that would help you reach them. 

After the famous iOS update that weakened Facebook targeting—and other consumer privacy-focused digital marketing developments—Meta has worked to create new tools that help advertisers reach customers based on the relevance of their products. Enter Facebook’s Advantage+ campaigns. These campaigns use a novel, AI-based targeting system and can be used to deploy Dynamic Product Ads (DPAs). In this blog, we’ll explain why this combination of technologies can help eCommerce brands unlock impressive results.

What is Advantage+?

Advantage+ is Meta’s latest generation of machine learning technology. It’s designed to streamline the campaign creation process for advertisers, enabling businesses to achieve results with less targeting inputs. That means they can be more hands-off while still generating effective outcomes. Within the context of eCommerce, Advantage+ campaigns utilize a client’s existing customer list to identify users with a high likelihood of making purchases. By prioritizing identifying and prioritizing similar users for ad delivery, Advantage+ maximizes the potential for driving conversions.

What are Dynamic Product Ads (DPAs)?

While traditional ad formats will appear the same to every user they reach, DPAs leverage interest and behavioral data to deliver personalized product recommendations based on the targeted individual. That means they assemble in real time from the different creative elements in your product feed: Different items, images, and descriptions populate based on what the algorithms think users will respond best to.

Personalized Ads Capture Impulse Purchases

Paid social channels like Facebook and Instagram are typically lower-intent channels: People go on them to kill time looking at pictures of their friends, not to shop. Driving a purchase via social is often a bit trickier than on channels where a user is already showing intent, like paid search. That means the purchases that brands do get on these channels are often impulsive ones. 

Success on social involves speaking directly to users and making them feel seen and heard. The combination of Meta’s powerful Advantage+ machine learning with direct, sales-focused DPAs can do just that. By showcasing products that users are most likely to want before they even realize it, DPAs capture the attention of potential customers and drive impulse purchases. 

Unlike traditional ads that can become repetitive, DPAs offer a unique experience for each user. With DPAs, users are shown the products they’re most likely to want before they even know they want them—and with the amount of data that Meta takes in, its predictions are often extremely accurate. By dynamically customizing product recommendations, Advantage+ DPAs provide fresh and engaging content, enhancing engagement and driving higher conversion rates. 

Advantage+ and DPAs: A Recipe for eCommerce Results

A lot of these advantages might sound great in theory, but it’s what the ads do in the real world that matters—and the results they’ve produced for our clients so far have been eye-popping. 

One eCommerce client experienced a remarkable 30% month-over-month return on ad spend (ROAS) increase among new customers. Compared to traditional campaign types in that account, Advantage+ DPA ads produced a 165% better ROAS across all customers. Another client saw their total paid social revenue increase by 40% just off the strength of these ads. 

In many cases, clients who have transitioned to Advantage+ DPA campaigns have quickly moved budget to them in order to capitalize on the success they’ve seen. And improvements happen fast: The conversion and engagement leaps that clients have experienced often lead to shorter learning phases for these campaigns as well. Given that they generate more interactions and purchases, Meta gets the data it needs more quickly to optimize for even better performance.

Best Practices for Using Advantage+ DPAs:

When setting up Advantage+ DPA campaigns, there are a few important things to keep in mind to achieve the best results.

Choose the Right Size Product Sets: Curating the appropriate product sets is essential for maximizing the effectiveness of DPAs. Generally, smaller to medium-sized product sets tend to perform better as they allow for greater specificity. About 30 to 50 unique products per ad set is the sweet spot: Too many increases the likelihood of inaccurate or irrelevant ads, while too few products creates the risk of hitting users with repetitive ads—the exact thing you’re looking to avoid by opting for a dynamic ad type rather than a static one.

Test Frequently: Continuous testing is key to identifying the most effective product sets and optimizing DPA performance. To start, we typically run these campaigns alongside more “standard” campaign types for at least 4 weeks to see if they can drive better results—which they usually do. 

From there, you can begin testing within your Advantage+ DPA ads. By experimenting with different sets and monitoring the results, businesses can refine their ad strategy and improve conversion rates over time. This testing process can also be aligned with other advertising channels—like Google’s similarly-imagined Performance Max campaign types—to gain additional insights. 

Refresh Product Sets Regularly: To maintain the freshness and relevance of DPAs, it is crucial to regularly review and refresh the product sets. Seasons change, as do market trends and user preferences. Because Advantage+ DPAs simplify targeting by putting the emphasis on the appeal of your products, you need to make sure the products being shown are seasonally and contextually appropriate—and don’t run long enough to become stale to the users who are seeing them.

Limitations of DPAs (and How to Mitigate Them)

Lack of Targeting Control: While it’s inherent to the nature of Advantage+ advertising, the lack of audience-building tools does force advertisers to be more meticulous about the customer lists they upload to Meta. The specific matching algorithms that underpin Advantage+ targeting remain unknown, meaning it’s vital that advertisers use up-to-date CRM lists that are optimized for the specific high value conversions that matter most to them. 

Black Box Nature Limits Insights: Another drawback of ad campaigns based on opaque algorithms is that it can be harder to attribute success to specific factors. While this limits granular analysis, A/B testing different customer lists and product sets (whether by item category or size of set) can still help you understand what works best and what doesn’t so you can optimize your approach for the best performance. 

Not Geared Towards Brand Lift and Storytelling: While DPAs excel at driving bottom-funnel conversions through impulse purchases, they may not be the best tool for brand building or storytelling. Businesses should complement DPAs with other advertising strategies, such as brand-focused campaigns or content marketing, to create a comprehensive customer journey and build brand loyalty.

Deploying Advantage+ DPAs for eCommerce Success

While no single ad type is a magic bullet for eCommerce brands, the early returns from Advantage+ DPAs make it clear that they can be a highly-effective tool for boosting sales. And given how quickly we’ve seen outcomes improve for clients that have incorporated them into their strategy, it often doesn’t take long to determine if they’re right for your brand. If you’re interested in exploring how your eCommerce brand can take advantage of the best new tools that companies like Meta and Google offer, don’t hesitate to reach out to Accelerated Digital Media for a consultation. 

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Case Study

Applying Advantage+ DPA Ads Maximized Social ROAS

Advantage+ campaigns are great at finding high-converting social users. Combined with product listing ads, they can be an exceptional revenue driver.

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