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How to Do It Right



How to Do It Right

Facebook offers many ways to test the performance of your Facebook ads before they go live.

marketer creating ab tests on facebook

One of the most popular tools Facebook offers is A/B testing, which allows you to find out which imagery and copy resonates most with your audience.

Here, let’s dive into how you can A/B test your marketing ads on Facebook step-by-step. Even if you’re a beginner, don’t fear — split testing on Facebook is easy, and the boost in ROI can be exponential. Let’s get started.

A/B Testing Facebook Ads

A/B testing, or split testing, is a term used to describe the process of running marketing experiments to see which version connects better with your audience. Usually, they’re tested simultaneously, and the variables can be anything from layout to copy to multimedia.

A/B testing on Facebook is popular because it gives marketers an idea of what types of ads earn the highest conversion rates. Essentially, if you run a split test on Facebook, you can identify patterns in your highest performing ads and posts. This allows you to publish better and better ads, boosting your ROI.

On Facebook, you can create A/B tests in multiple ways. This is dependent on your preferred workflow; the results are virtually the same.

First, you can create an A/B test within the Ads Manager Toolbar. The Toolbar will let you use an ad campaign you’ve already created as a jumping-off point for your new test. Alternatively, you can manually duplicate a campaign or use the Experiments tool.

First, let’s go over the Toolbar method.

The simplest way to split test Facebook ads is by using the Toolbar on your Ads Manager dashboard. Here’s how.

1. Go to Facebook Ads Manager.

a/b testing on facebook: ads manager web page

Ensure you’re logged into your Facebook account when you access the web page. Then, click on “Go to Ads Manager.” You’ll arrive at your dashboard, which has several tabs: Campaigns, Ad sets, and Ads. Today, we’ll work exclusively in the Campaigns tab.

a/b testing on facebook: campaigns tab in ads manager

2. Select the campaign you’d like to A/B test.

To complete A/B tests, you’ll need to have an existing campaign. However, you can set up an A/B test as you create an ad, too. In the second screen of the ad creation process, toggle the “Create A/B test” button under “Campaign details.”

a/b testing on facebook: ab test toggle

Otherwise, if you’re not creating a new ad, select the existing campaign you’d like to optimize from the list in the Campaigns tab.

3. On the toolbar, click “A/B Test.”

a/b testing on facebook: a/b test button on toolbar

Once you’ve selected your campaign, you can begin creating your A/B test. At the top of your list of campaigns is a toolbar. Click the “A/B Test” button or beaker symbol, as shown below.

a/b testing on facebook: funnel button on toolbar

Alternatively, depending on your screen size, tap the button that reads “More”, then click “A/B Test” in the drop-down menu.

a/b testing on facebook:  a/b test button under more

4. In the A/B test workflow, tap “Get Started.”

a/b testing on facebook: a/b test workflow

A pop-up will appear. Tap the blue “Get Started” button to begin. You’ll immediately be able to either make a copy of your ad to edit, or pick an existing ad you’ve already made.

a/b testing on facebook: duplicate ad options

For this tutorial, we’ve chosen “Make a copy of this ad.” After you choose your preferred option, click “Next.”

5. Choose a variable to test.

a/b testing on facebook: pick the variable

There are several different options for variable testing, and they’re categorized based on the goals of your campaign.

The variables are as follows:

  • Audience: This variable will look at the effectiveness of your ads based on the audiences you aim to reach. For instance, you can test different audiences based on region.

  • Creative: Creative A/B tests will focus on the visual assets of your ad. So if you want to test different images, videos, or carousels, you will choose the “Creative” option.

  • Placements: If you want to test where on Facebook your ad will be most effective, you’ll want to pick “Placements.” This option allows you to test automatic placements.

6. Name your test and determine the winning criteria.

a/b testing on facebook:  choose test name

Name your test and choose the metrics you’ll use to determine the winner. You can also choose the time frame for how long your ad will run. After you’re done, tap “Duplicate Ad set.”

7. Edit and publish the alternate version of your ad.

In the next screen, you’ll be able to change your duplicate ad as desired. We recommend changing one variable, such as a single line of copy, an image, or another parameter. After you’re finished, click “Publish” in the bottom right-hand corner.

a/b testing on facebook: edit and publish duplicate ad

All done! You’re ready to perform your test. You can check the status of your test in Ads Manager.

If you find that you want to go with a different route for your A/B test, there are also options to set them up differently. For instance, let’s talk about duplication next.

Alternative Methods for Split Testing Facebook Ads

Method 1: Use Duplication to Create Facebook A/B Tests

When you choose this option, you can easily create a test by changing one variable in a nearly identical campaign or ad set. Note: This is for ads or campaigns that have already been created.

1. Access Ads Manager.

When you go to Ads Manager, go to your “Campaigns” tab. Here, you’ll see a list of your campaigns that are currently running. You’ll also see your drafted campaigns. You can choose either for duplication.

2. In the toolbar, select “Duplicate.”

a/b testing on facebook: duplicate button on toolbar

After you’ve decided which campaign or ad set you want to test, click the “Duplicate” button in the toolbar.

3. Click “New A/B test.”

a/b testing on facebook: ad duplication options

In the pop-up, select the “New A/B test” option. Remember, this option will let you choose a variable to change to analyze performance, so choose a campaign that fits that criteria.

4. In the A/B test workflow, choose a variable to test.

From here, the steps are the same as in the previous method. If you’re choosing an ad set to duplicate, Facebook will provide suggestions of which variable to change for you, and you can pick from there.

5. Name your test and determine the winning criteria.

Give a name to your A/B test and choose how you’ll determine the winner. Then, click “Duplicate Ad set.”

6. Edit and publish the alternate version of your ad.

After choosing your variable, you’ll see your tests next to each other in a preview. After making any necessary changes in this stage, click “Publish.”

When you publish your test, audiences will be able to interact with them, so make sure you’ve ironed out all the details before finalizing. However, you’ll be able to check back on your test in Ads Manager to access the most current insights.

Next, we’ll cover how to create an A/B test using the Experiments tool.

Method 2: Use Experiments to Create Facebook A/B Tests

The Experiments tool lets you create or duplicate ad campaigns to test. The difference between using Experiments is minor — the results are the same. Only use this option if it feels more user-friendly.

First, create the campaigns you’d like to test by clicking the green “Create” button and going through the steps. Duplicate the first campaign, change a single variable, and then head over to Experiments. Here’s how:

1. Go to Experiments.

a/b testing on facebook: hamburger menu on ads manager

In your Ads Manager dashboard, tap the three vertical lines of the menu, which will show you the “All tools” pane. Then, tap “Experiments.”

a/b testing on facebook: experiments button

You can also search “Experiments” in Ads Manager’s built-in search tool.

2. Click “Get started” on the A/B Test card.

a/b testing on facebook: get started in experiments page

Click “Get Started.” When you do this, you’ll be taken to a page that lets you fill in the ad details.

3. Select your A/B test options.

a/b testing on facebook: test settings on experiments

Choose the campaigns you’d like to test. It’s important to have created the campaigns you’d like to test beforehand, or they won’t appear in the list. You can also schedule the run time of your test and fill in the test name.

4. Determine the winning criteria.

a/b testing on facebook:  determine winning factor

Choose which metrics Facebook should use to pick the winner. After you’re done, click “Review Test Details.”

5. Review your test and tap “Create Test.”

a/b testing on facebook:  review test details

In the next screen, you’ll have an opportunity to see a summary of your test. If you’re happy with the results, click “Create Test.” If not, click “Edit” and make any necessary changes.

6. View all your experiments.

a/b testing on facebook:  experiments dashboard

In the Experiments homepage, you can see all of your scheduled and running A/B tests. These include any you’ve created using the Experiments tool or through the Toolbar in the Campaigns dashboard.

Facebook uses the same base technology to run your A/B tests. The different versions of tests you can run help you make the best choices to optimize ad performance.

Next, let’s go over some best practices for running your A/B test on Facebook.

Facebook A/B Test Best Practices

Keep these best practices in mind before you begin your split test — they’ll help you run tests that are valuable and applicable to your next campaign.

1. Stay organized with tracking spreadsheets.

Because A/B tests can influence the future of your Facebook advertising strategy, it’s important to approach the process methodically and have clear goals and tracking in place. Utilizing an A/B test tracking spreadsheet ensures you can collect and analyze your data to make the most insightful, metrics-backed decisions.

ab testing trackerDownload this Template

2. Choose one variable that’ll help you reach your goals.

When you A/B test on Facebook, make sure you’re only choosing one variable to test. There’s a separate multivariate test that you can run, but for A/B, one variable is key. Your test results will be more conclusive with only one variable.

3. Pick audiences that you want to reach with ads.

Choose a new audience for your test. They should be large enough to provide measurable results, but shouldn’t be the exact same audience as a campaign you’re already running. If they’re the same as a drafted campaign, that’s okay because they’re not published.

However, if you choose the exact same audience as a campaign you’re already running, Facebook’s system might mix up your ads and provide contaminated results.

4. Use hypotheses that are measurable and valuable.

In order to analyze your test results so they’re the most valuable to you, make sure your hypothesis is measurable. To put it another way: Make sure your hypothesis is clear, easy to understand, and able to be determined with an A/B test.

Your hypothesis can be as simple as, “Which method of delivery do my audience members respond the best to?” This question can be answered by using the Delivery Optimization A/B test on Facebook.

5. Make time frames that are ideal.

Recall that when you set up your A/B test, you can choose a time frame. You can choose to run your test for up to 30 days. Facebook’s Business Center suggests at least four days, which is enough time for the technology to produce accurate results.

6. Choose a budget that works for your business.

Facebook can provide an ideal budget for you based on your test details, or you can choose an ideal budget for yourself when you’re filling in test details. Setting an ideal budget will help you determine a winning strategy — it factors in Ad Spend into the success of your test.

According to one of HubSpot’s Paid Ads specialists, Nicole Ondracek, “A big value of split testing is being able to prevent audience overlap so you know that the same audience is not seeing multiple variants which could affect the results. That way, you can confidently say which one is the clear winner.”

A/B testing gives you a better understanding of audience behavior. Performing them on Facebook streamlines the process and gives you more comfortability with Facebook’s ad system.

Additionally, Ondracek mentions that depending on split testing results, advertisers can begin to shape what type of creative they need to use for the future.

This post was originally published in March 2013 and has been updated for comprehensiveness.

The Ultimate A/B Testing Kit

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YouTube Ad Specs, Sizes, and Examples [2024 Update]



YouTube Ad Specs, Sizes, and Examples


With billions of users each month, YouTube is the world’s second largest search engine and top website for video content. This makes it a great place for advertising. To succeed, advertisers need to follow the correct YouTube ad specifications. These rules help your ad reach more viewers, increasing the chance of gaining new customers and boosting brand awareness.

Types of YouTube Ads

Video Ads

  • Description: These play before, during, or after a YouTube video on computers or mobile devices.
  • Types:
    • In-stream ads: Can be skippable or non-skippable.
    • Bumper ads: Non-skippable, short ads that play before, during, or after a video.

Display Ads

  • Description: These appear in different spots on YouTube and usually use text or static images.
  • Note: YouTube does not support display image ads directly on its app, but these can be targeted to through Google Display Network (GDN).

Companion Banners

  • Description: Appears to the right of the YouTube player on desktop.
  • Requirement: Must be purchased alongside In-stream ads, Bumper ads, or In-feed ads.

In-feed Ads

  • Description: Resemble videos with images, headlines, and text. They link to a public or unlisted YouTube video.

Outstream Ads

  • Description: Mobile-only video ads that play outside of YouTube, on websites and apps within the Google video partner network.

Masthead Ads

  • Description: Premium, high-visibility banner ads displayed at the top of the YouTube homepage for both desktop and mobile users.

YouTube Ad Specs by Type

Skippable In-stream Video Ads

  • Placement: Before, during, or after a YouTube video.
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Vertical: 9:16
    • Square: 1:1
  • Length:
    • Awareness: 15-20 seconds
    • Consideration: 2-3 minutes
    • Action: 15-20 seconds

Non-skippable In-stream Video Ads

  • Description: Must be watched completely before the main video.
  • Length: 15 seconds (or 20 seconds in certain markets).
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Vertical: 9:16
    • Square: 1:1

Bumper Ads

  • Length: Maximum 6 seconds.
  • File Format: MP4, Quicktime, AVI, ASF, Windows Media, or MPEG.
  • Resolution:
    • Horizontal: 640 x 360px
    • Vertical: 480 x 360px

In-feed Ads

  • Description: Show alongside YouTube content, like search results or the Home feed.
  • Resolution:
    • Horizontal: 1920 x 1080px
    • Vertical: 1080 x 1920px
    • Square: 1080 x 1080px
  • Aspect Ratio:
    • Horizontal: 16:9
    • Square: 1:1
  • Length:
    • Awareness: 15-20 seconds
    • Consideration: 2-3 minutes
  • Headline/Description:
    • Headline: Up to 2 lines, 40 characters per line
    • Description: Up to 2 lines, 35 characters per line

Display Ads

  • Description: Static images or animated media that appear on YouTube next to video suggestions, in search results, or on the homepage.
  • Image Size: 300×60 pixels.
  • File Type: GIF, JPG, PNG.
  • File Size: Max 150KB.
  • Max Animation Length: 30 seconds.

Outstream Ads

  • Description: Mobile-only video ads that appear on websites and apps within the Google video partner network, not on YouTube itself.
  • Logo Specs:
    • Square: 1:1 (200 x 200px).
    • File Type: JPG, GIF, PNG.
    • Max Size: 200KB.

Masthead Ads

  • Description: High-visibility ads at the top of the YouTube homepage.
  • Resolution: 1920 x 1080 or higher.
  • File Type: JPG or PNG (without transparency).


YouTube offers a variety of ad formats to reach audiences effectively in 2024. Whether you want to build brand awareness, drive conversions, or target specific demographics, YouTube provides a dynamic platform for your advertising needs. Always follow Google’s advertising policies and the technical ad specs to ensure your ads perform their best. Ready to start using YouTube ads? Contact us today to get started!

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Why We Are Always ‘Clicking to Buy’, According to Psychologists



Why We Are Always 'Clicking to Buy', According to Psychologists

Amazon pillows.


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A deeper dive into data, personalization and Copilots



A deeper dive into data, personalization and Copilots

Salesforce launched a collection of new, generative AI-related products at Connections in Chicago this week. They included new Einstein Copilots for marketers and merchants and Einstein Personalization.

To better understand, not only the potential impact of the new products, but the evolving Salesforce architecture, we sat down with Bobby Jania, CMO, Marketing Cloud.

Dig deeper: Salesforce piles on the Einstein Copilots

Salesforce’s evolving architecture

It’s hard to deny that Salesforce likes coming up with new names for platforms and products (what happened to Customer 360?) and this can sometimes make the observer wonder if something is brand new, or old but with a brand new name. In particular, what exactly is Einstein 1 and how is it related to Salesforce Data Cloud?

“Data Cloud is built on the Einstein 1 platform,” Jania explained. “The Einstein 1 platform is our entire Salesforce platform and that includes products like Sales Cloud, Service Cloud — that it includes the original idea of Salesforce not just being in the cloud, but being multi-tenancy.”

Data Cloud — not an acquisition, of course — was built natively on that platform. It was the first product built on Hyperforce, Salesforce’s new cloud infrastructure architecture. “Since Data Cloud was on what we now call the Einstein 1 platform from Day One, it has always natively connected to, and been able to read anything in Sales Cloud, Service Cloud [and so on]. On top of that, we can now bring in, not only structured but unstructured data.”

That’s a significant progression from the position, several years ago, when Salesforce had stitched together a platform around various acquisitions (ExactTarget, for example) that didn’t necessarily talk to each other.

“At times, what we would do is have a kind of behind-the-scenes flow where data from one product could be moved into another product,” said Jania, “but in many of those cases the data would then be in both, whereas now the data is in Data Cloud. Tableau will run natively off Data Cloud; Commerce Cloud, Service Cloud, Marketing Cloud — they’re all going to the same operational customer profile.” They’re not copying the data from Data Cloud, Jania confirmed.

Another thing to know is tit’s possible for Salesforce customers to import their own datasets into Data Cloud. “We wanted to create a federated data model,” said Jania. “If you’re using Snowflake, for example, we more or less virtually sit on your data lake. The value we add is that we will look at all your data and help you form these operational customer profiles.”

Let’s learn more about Einstein Copilot

“Copilot means that I have an assistant with me in the tool where I need to be working that contextually knows what I am trying to do and helps me at every step of the process,” Jania said.

For marketers, this might begin with a campaign brief developed with Copilot’s assistance, the identification of an audience based on the brief, and then the development of email or other content. “What’s really cool is the idea of Einstein Studio where our customers will create actions [for Copilot] that we hadn’t even thought about.”

Here’s a key insight (back to nomenclature). We reported on Copilot for markets, Copilot for merchants, Copilot for shoppers. It turns out, however, that there is just one Copilot, Einstein Copilot, and these are use cases. “There’s just one Copilot, we just add these for a little clarity; we’re going to talk about marketing use cases, about shoppers’ use cases. These are actions for the marketing use cases we built out of the box; you can build your own.”

It’s surely going to take a little time for marketers to learn to work easily with Copilot. “There’s always time for adoption,” Jania agreed. “What is directly connected with this is, this is my ninth Connections and this one has the most hands-on training that I’ve seen since 2014 — and a lot of that is getting people using Data Cloud, using these tools rather than just being given a demo.”

What’s new about Einstein Personalization

Salesforce Einstein has been around since 2016 and many of the use cases seem to have involved personalization in various forms. What’s new?

“Einstein Personalization is a real-time decision engine and it’s going to choose next-best-action, next-best-offer. What is new is that it’s a service now that runs natively on top of Data Cloud.” A lot of real-time decision engines need their own set of data that might actually be a subset of data. “Einstein Personalization is going to look holistically at a customer and recommend a next-best-action that could be natively surfaced in Service Cloud, Sales Cloud or Marketing Cloud.”

Finally, trust

One feature of the presentations at Connections was the reassurance that, although public LLMs like ChatGPT could be selected for application to customer data, none of that data would be retained by the LLMs. Is this just a matter of written agreements? No, not just that, said Jania.

“In the Einstein Trust Layer, all of the data, when it connects to an LLM, runs through our gateway. If there was a prompt that had personally identifiable information — a credit card number, an email address — at a mimum, all that is stripped out. The LLMs do not store the output; we store the output for auditing back in Salesforce. Any output that comes back through our gateway is logged in our system; it runs through a toxicity model; and only at the end do we put PII data back into the answer. There are real pieces beyond a handshake that this data is safe.”

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