New Way to Run Facebook Ads In 2024 | It's Actually Better than Before ️‍🔥

Damini Tripathi

29 Jul 202409:28

Summary

TLDRThe video script discusses strategies for running ads on Facebook in 2024, emphasizing the importance of learning from the platform's AI, Meta. It explains how Meta's AI analyzes campaigns to deliver the best results, including targeting, audience frequency, and budget optimization. The script also covers the concept of 'learning phase' for ads and how Meta has reduced the time and conversion requirements to exit it, allowing for quicker results and more efficient testing of ads, creatives, and targeting. The presenter suggests experimenting with broad targeting for e-commerce businesses and highlights the benefits of using AI in ad creatives and audience definition.

Takeaways

😀 The speaker has been updating and learning about Facebook advertising for the past five years, emphasizing the importance of watching the video until the end for insights on running ads in 2024.
🔍 Discusses the concept of 'Learning Phase' in Facebook ads, explaining how it analyzes campaigns to provide the best results.
📈 Highlights the importance of targeting in advertising, using the example of targeting for selling bed sheets and how Meta's AI analyzes various factors for optimal ad performance.
📊 Mentions how Meta's AI checks how often ads should be shown to the audience to convert into sales or leads, and also how it manages the budget for ad display.
📝 Talks about the importance of campaign structure, stating that a well-structured campaign allows Meta's AI to better analyze and optimize ad performance.
🚀 Explains that changes in ad creatives or targeting can cause the ad to re-enter the learning phase, affecting its performance.
📉 Describes the previous requirement of achieving 50 conversions within seven days to exit the learning phase, which was a challenge for many with smaller budgets.
🎯 Meta has reduced the learning phase duration, now requiring only 10 conversions within three days, making it easier for advertisers to optimize their campaigns quickly.
📉 Discusses the benefits of the reduced learning phase, allowing for quicker exit with lower ad budgets and easier adjustments for underperforming ads.
🛠 Suggests using broad targeting in ad campaigns, especially for e-commerce businesses, to test and see if it works well, as Meta's AI is smart enough to define the audience.
🔬 Emphasizes the importance of testing different ad elements such as creatives, targeting, and custom audiences to understand what works best for the audience and improve ad performance.

Q & A

What is the main focus of the video script?
-The video script focuses on how to effectively run ads on Facebook in 2024, emphasizing the importance of learning from the platform's AI capabilities and adapting to its features like learning phase and targeting.
What does the speaker suggest is the first step in understanding Facebook ads?
-The speaker suggests that the first step is to understand the concept of 'learning phase' in Facebook ads and how it impacts the performance and optimization of ad campaigns.
How does the AI from Meta analyze ad campaigns?
-The AI from Meta analyzes ad campaigns by examining various targeting options and determining the best ways to deliver results, including how often to show ads to the audience to achieve sales or leads.
What is the significance of campaign structure according to the speaker?
-The speaker emphasizes that a well-structured campaign is crucial because it allows Meta's AI to better analyze and optimize the ad's performance in the actual environment.
What was the previous requirement to exit the learning phase for an ad campaign?
-Previously, to exit the learning phase, one had to achieve 50 conversions within 7 days, which was a challenge for many, especially with a limited budget.
How has Meta adjusted the learning phase requirements to make it easier for advertisers?
-Meta has reduced the learning phase requirement to achieving just 10 conversions within 3 days, making it easier and faster for advertisers to exit the learning phase.
What benefits do advertisers get from the reduced learning phase duration?
-The reduced duration allows advertisers to quickly exit the learning phase even with a small ad budget and makes it easier to test and optimize ads without spending too much time.
Why is it suggested to test multiple ad creatives and targeting options?
-Testing multiple ad creatives and targeting options helps advertisers to find the most effective combinations that resonate with their audience and improve ad performance.
What role does AI play in ad creatives and audience targeting today?
-AI now plays a significant role in developing ad copy based on user preferences and in deciding the audience for ads, making the ad creation and targeting process more efficient and personalized.
What is the speaker's experience with broad targeting in a dropshipping sales campaign?
-The speaker found that using broad targeting without selecting any specific interests, except for age and location, resulted in sales from the early days of the campaign, indicating that broad targeting can work well in some cases.
Why is it important to test the audience for ads even after using AI tools for optimization?
-Testing the audience is important because even with AI tools, understanding what works for your specific audience is crucial for achieving good results, and AI tools work best when provided with well-tested audience data.

Outlines

00:00

📈 Learning Phase in Facebook Ads

The first paragraph discusses the learning phase of Facebook ads, where the AI analyzes the campaign to optimize results. It explains how targeting and ad creatives are tested and adjusted, and the importance of the campaign structure for effective analysis. The speaker emphasizes that changes to the ad during the learning phase can reset it, and how the learning phase duration has been reduced from 7 days to 3 days for 10 conversions, allowing for quicker optimization and results.

05:02

🛠️ Testing and Targeting Strategies in Digital Marketing

The second paragraph focuses on the importance of testing in digital marketing, particularly with Facebook ads. It talks about the ability to perform multiple ad creative and targeting tests, leveraging AI to develop ad copies based on user personas. The speaker shares an example of a dropshipping sales campaign with broad targeting, which resulted in sales from the beginning, indicating that broad targeting can work depending on the ad's effectiveness. The paragraph also touches on the use of AI in defining audiences and the importance of testing to understand what works for one's specific audience.

Mindmap

Keywords

💡Facebook Ads

Facebook Ads is a form of online advertising where businesses can promote their products or services on Facebook's platform. In the video, the speaker discusses how to effectively run Facebook ads in 2024, emphasizing the importance of understanding the platform's advertising features to maximize results.

💡Learning Phase

The learning phase in the context of Facebook Ads refers to the initial stage of an ad campaign where the platform gathers data to optimize ad delivery. The script mentions that changes in the learning phase can affect ad performance, and the speaker explains the updated requirements to exit this phase.

💡Meta AI

Meta AI, as mentioned in the script, is the artificial intelligence system used by Meta (Facebook's parent company) to analyze and optimize ad campaigns. It helps in determining the best ways to deliver ads for better results, as illustrated by the speaker's example of targeting for a bedsheet sale.

💡Targeting

Targeting in the script refers to the process of defining the specific audience for an ad campaign. The speaker talks about how targeting can be adjusted based on actual performance, and how Meta AI analyzes various targeting options to find what works best.

💡Ad Creatives

Ad creatives are the visual and textual content used in an advertisement. The script discusses how Meta AI can analyze ad creatives based on user engagement and other factors to determine the best-performing ads, which is crucial for optimizing campaigns.

💡Pixel Integration

Pixel integration is the process of adding a tracking pixel to a website to monitor and analyze user behavior. The speaker mentions that having a pixel integrated can help Meta AI analyze data and optimize ad performance based on user interactions with the website.

💡Campaign Structure

Campaign structure refers to the organization and setup of an advertising campaign. The script emphasizes the importance of a well-structured campaign for effective analysis and optimization by Meta AI, as it impacts how the audience is defined and how results are achieved.

💡Broad Targeting

Broad targeting is a strategy where an ad campaign is aimed at a wide audience rather than a specific, narrow group. The speaker discusses the potential benefits and drawbacks of broad targeting, suggesting that it can be effective depending on the ad and business type.

💡Narrow Targeting

Narrow targeting is the opposite of broad targeting, focusing on a specific, smaller group of potential customers. The script suggests that while broad targeting may work for some businesses, others may need to narrow down their audience for better ad performance.

💡AI in Ad Creatives

The script mentions the integration of AI in creating ad creatives, where the AI develops ad copy based on user preferences. This represents an advanced use of AI to personalize ads and potentially improve engagement and conversion rates.

💡Testing

Testing in the context of the script refers to the process of trying out different ad elements, such as creatives and targeting, to see what works best. The speaker encourages testing various ad components to optimize campaigns and achieve better results.

Highlights

Learning face helps in analyzing and optimizing ad campaigns for better results.

The importance of understanding the learning phase of ads for effective marketing strategies.

Meta's AI analyzes campaigns in various ways to determine the best results.

Targeting strategies can vary, and what works in reality may be different from expectations.

The frequency of ad display to the audience is crucial for conversion into sales or leads.

Budget considerations are essential in determining how and when to display ads.

Data analysis plays a significant role in optimizing ad performance.

The structure of a campaign is vital for effective AI analysis and optimization.

Changes in ad creatives or targeting can lead the ad back into the learning phase.

Previously, to exit the learning phase, a certain number of conversions were required within a week.

The challenge of meeting conversion goals with limited budgets and the impact on ad performance.

Meta's AI couldn't deeply read related ad data, which was a mistake on Meta's part.

Changing ad objectives to meet the learning phase exit criteria, such as leads to landing page views.

Meta has reduced the learning phase duration, requiring fewer conversions in a shorter time.

The benefits of the reduced learning phase include faster exit with lower ad budgets and easier optimization.

The importance of testing ads with different creatives and targeting to find the best performing strategies.

AI integration in ad creatives, where copy is developed based on user personas.

Broad targeting can work for some businesses, but not all, and the need for testing different approaches.

The effectiveness of custom and lookalike audiences in ad campaigns compared to broad targeting.

The importance of testing ad performance with different audience data to understand what works best.

The speaker's experience with a dropshipping sales campaign using broad targeting and its success.

The role of testing in scaling businesses and the importance of understanding ad performance.