Advantage+ Shopping Campaigns: The Latest and Greatest in Meta Ads
We all either hate it or love it (or sometimes both): Advantage+ Shopping Campaigns, commonly known as ASC. This innovative advertising approach has taken the marketing world by storm, and for good reason. After attending Meta's ASC Office Hours, I was able to gather valuable insights into why Meta promotes ASC so vigorously and the techniques they suggest to maximize its potential.
Advantage+ Shopping Campaign & Best Practices
So, what exactly is Advantage+ (ASC) and why is it considered the pinnacle of Meta ads? In a nutshell, ASC is an automated end-to-end campaign that utilizes artificial intelligence (AI) to optimize and streamline the advertising process. It's recommended for "always on" performance, meaning it consistently delivers results without requiring constant manual intervention. With ASC, Meta takes on the heavy lifting, enabling advertisers to focus on other crucial aspects of their marketing strategy.
One of the standout features of ASC is its ability to retarget and prospect for you. This means that ASC not only helps you reach potential customers who have already shown interest in your products, but also identifies and targets new audiences that are likely to engage with your brand. This dynamic approach ensures maximum exposure and relevance, leading to improved campaign performance. In order to have the greatest success letting the machine learning find your target audience, however, it’s imperative to use broad targeting parameters. The wider the audience reach, the better the AI can optimize your campaign for maximum effectiveness.
When it comes to setting up an ASC campaign, there are several key factors to consider. First and foremost, it's essential to have a mix of image, video, and catalog assets. By diversifying your creative assets, you cater to different customer preferences and increase the likelihood of capturing attention. Meta recommends having at least 10 creative assets in each ASC campaign. This variety of assets ensures that the AI has sufficient material to work with and can optimize performance effectively.
Budget allocation and duration are also vital considerations. The Learning Phase of an ASC campaign typically lasts around 2-4 weeks, during which the AI gathers data and optimizes performance. Adequate budgeting allows the AI to make informed decisions and deliver the desired outcomes. When optimizing ASC campaigns it is likely Meta will recommend a budget; for best results apply the recommended budget (within reason and within your budget’s capabilities).
Let’s go back to that Learning Phase period: it can span up to 4 weeks, compared to legacy Meta campaigns that typically take closer to 2 weeks. So, it’s crucial to be patient when assessing the success of an ASC campaign. If the campaign doesn't meet your goals during this period, it's recommended to follow best practices and avoid making changes that could reset the learning process. If doubts persist, performing an A/B test with a regular campaign can provide valuable insights.
Sending customers to your Meta shop is a recommended practice for ASC campaigns. By directing traffic to your online store, you create a seamless customer journey that enhances the likelihood of conversions. However, it's important to note that the ideal budget per ad can vary depending on the specific circumstances. Facebook Ads Manager provides recommendations and alerts if your budget is too low for effective campaign performance.
What to do if my Adv+ campaign is underperforming?
If you notice your ASC is not achieving your outlined goals Meta emphasizes the tool of A/B testing between an ASC campaign and a standard conversion campaign. By keeping all variables the same except for the campaign type, advertisers can compare the performance and determine which approach yields better results. However, it's crucial not to pause ads that aren't performing well within the ASC campaign, especially if the campaign is still in the Learning Phase. Removing such ads may disrupt the AI's learning process. Instead, let the algorithm decide and trust that it will make the necessary adjustments for optimal performance.
Disadvantages to ASC?
While ASC offers numerous benefits, it's essential to acknowledge its drawbacks. Making any changes to the campaign, such as budget adjustments, asset modifications, or copy updates, triggers a re-entry into the Learning Phase. This restarts AI learning, leaving advertisers with limited options until the campaign exits the learning phase. A potential solution to avoid disrupting a well-performing campaign is to set up an entirely new ASC campaign and allow the successful one to continue without interference.
Another limitation is the inability to allocate budget to specific platforms within ASC (e.g., Instagram vs. Facebook). To address this, Meta recommends conducting an A/B test with a standard conversion campaign with identical creatives, copy, and budget to compare performance across platforms.
To achieve the best results with ASC, it's crucial to follow Meta's best practices for campaign setup and optimization. Once the campaign is built, it's advisable to adopt a hands-off approach and let the AI do its magic. However, if an ASC campaign doesn't meet expectations, running an A/B test with a standard campaign can help determine the more successful approach.
Conclusion
All in all, Advantage+ Shopping Campaigns represent a significant advancement in Meta ads, leveraging AI and automation to deliver optimized and efficient advertising solutions. By adhering to Meta's best practices, giving the AI room to learn and optimize, and running A/B tests when necessary, advertisers can unlock the full potential of ASC and drive exceptional results for their businesses.