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Facebook pulls ‘pseudoscience’ from its list of targeted ad categories

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Even as Mark Zuckerberg touted the “hundreds of thousands of pieces of misinformation related to COVID-19” that the site had pulled in recent months, Facebook continued to offer targeted ads classified as “pseudoscience.” It was an odd choice from a social network so publicly declaring its own campaigns to remove junk science amid a global pandemic.

Using Ad Manager, advertisers were able to serve ads to some 78 million people “who have expressed an interest in pseudoscience.” Following an investigation by The Markup that found the site buying ads to target that category, Facebook says it’s done with the pseudoscience tag.

In a statement to TechCrunch, the company reconfirmed the move. “This interest category of advertising should have been removed in a previous review and we’ve removed it,” Director of Product Management Rob Leathern said. There was never a great time to run junk science ads, of course, but the issue has come to a head in recent weeks and months, as COVID-19 has become a massive hotbed for conspiracy and dangerous cures.

As Zuckerberg noted in his piece last week, popular theories flagged by the company include the notions that “drinking bleach cures the virus or that physical distancing is ineffective at preventing the disease from spreading.” It’s unclear (beyond the obvious answer of ad revenue) why Facebook continued to offer the category until it was essentially called out on the matter.

Other ad networks and social media sites have been taking pains to slow the spread of misinformation. Twitter recently added 5G-related conspiracies to its list of COVID-19 related guidance, while Google just announced that it would be extending its ID verification for its ad systems.

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5 Effective Ways to Run Facebook Ads A/B Tests

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Facebook Ads A/B Tests or split tests help them try different versions of ads with various campaign elements. This process helps them arrive at the best version for the organization’s target. 

A/B Tests offer a vast pool of resources to try out various versions. You may get caught up and lose your way to arriving at the best version in a limited time. To better understand this topic you can read the Facebook ad testing guide. Here are five effective ways to run Facebook Ads A/B Tests-

1) Start with the minimal number of variables

This approach will help you analyze the impact of a variable much better. The lesser the variables, the better will be the relevant results and more conclusive. Once you have various versions, you will need to run them through the A/B Significance Test to determine if the test results are valid.

2) The second way is to select the correct structure. 

There are two structures in A/B tests. One is a single ad test, and the other is multiple single variation ad sets. All the variations will go under one ad set in the first structure. Each variation will be under a separate ad set in the second one. Out of the two, the second one works out to be better and gives better results.

3) Use of spreadsheets is important to stay organized. 

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These spreadsheets help collect and analyze data to get meaningful insights and arrive at data-backed decisions.

4) Do target advertising and set realistic time goals. 

One approach is to choose an entirely new set of audiences. Also, the data pool should be vast and not the same as some existing campaigns. The reason for choosing a different audience is that Facebook may mix up your ads and give contaminated output. 

Another approach to choosing the right audience is to pick geography. It works better, especially when you have business in a particular region.   

It’s also essential to set a realistic timeline for your testing. Facebook suggests one should run a test for at least four days, but you can choose to run the test for up to 30 days.   

5) Set an ideal budget. 

The concept of a perfect budget is subjective. But, you can fix it yourself, or Facebook can do that for you based on your testing data. A large part of the test budget is spent on avoiding audience duplication. If the same audience sees variations, it could affect the test results.

Besides these top five effective ideas, you will need to take a few more action points to make the testing process efficient. Make sure you put the website’s domain link and not the landing page link in the ad, as that doesn’t look good. Put appropriate Call To Action Button, such as ‘Learn More,’ ‘Buy Now,’ etc. It’s also important to see how your ad is coming across on various electronic gadgets- mobile, tablets, etc.

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Another strategy that works is trying to engage the customer. You may add social engagement buttons such as ‘Like’ or ‘Comment.’ Use high-resolution images as they work better with the customers. Low-quality, highly edited images are often not liked and trusted by the consumers.

You can learn more about the audience behavior patterns with A/B test results. Conducting these tests on Facebook streamlines the entire process and makes it smooth for you. With the test results, advertisers and marketers can work on the creatives they need to utilize.

To sum it up, you can run an effective A/B test campaign within the specified budget. You don’t need to spend massive amounts to get your advertisement right. You’ll make the correct assumptions about the performance of variations with a good understanding of business and consumers.

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