9 A/B Testing Examples From Real Businesses (2022)

Whether you're looking to increase revenue, sign-ups, social shares, or engagement, A/B testing and optimization can help you get there.But for many marketers out there, the tough part about A/B testing is often finding the right test to drive the biggest impact — especially when you're just getting started.

So, what's the recipe for high-impact success?

Truthfully, there is no one-size-fits-all recipe. What works for one business won't work for another — and vice versa.

But just because you can't replicate the same test and expect the same result doesn't mean you can't get inspired by other companies' tests.

In this post, let's review how an hypothesis will get you started with your testing, and review excellent examples from real businesses using A/B testing. While the same tests may not get you the same results, they can get you inspired to run creative tests of your own.

A/B Testing Hypothesis Examples

A hypothesis can make or break your experiment, especially when it comes to A/B testing. When creating your hypothesis, you want to make sure that it is:

  1. Focused on one specific problem you want to solve or understand
  2. Able to be proven or disproven
  3. Focused on making an impact (bringing higher conversion rates, lower bounce rate, etc.)

When creating a hypothesis, following the “If, then” structure can be helpful, where if you changed a specific variable, then a particular result would happen. Here are some examples of what that would look like in an A/B Testing Hypothesis:

  • Shortening contact submission forms to only contain required fields would increase the number of sign-ups.
  • Changing the call-to-action text from “Download now” to “Download this free guide” would increase the number of downloads.
  • Reducing the frequency of mobile app notifications from 5 times per day to 2 times per day will increase mobile app retention rates.
  • Using featured images that are more contextually related to our blog posts will contribute to a lower bounce rate.
  • Greeting customers by name in emails will increase the total number of clicks.

Let’s go over some real-life examples of A/B testing to prepare you for your own.

A/B Testing Examples

  1. HubSpot's Site Search
  2. Groove's Landing Page Design
  3. Csek Creative Homepage Design
  4. Humana's Site Banners
  5. HubSpot's Email vs. In-App Notification Center
  6. Unbounce's Tweet vs. Email CTA
  7. HubSpot's Mobile Calls-to-Action
  8. Houseparty’s Mobile Onboarding Design
  9. HelloFresh Menu Display

1. HubSpot's Site Search

Most websites contain a search bar at the top of the page that gives users the ability to search for a specific topic or term.

Based on previous data, HubSpot found that non-bounce desktop users who engage with search have a 163.8% higher blog lead conversion rate than those who do not. However, only a very small percent of blog traffic interacts with the search bar. That's why HubSpot decided to test the visual prominence and functionality of the site search bar.

HubSpot used three variants for this test, using offer thank you page views as the primary metric.

For variant A, the site search bar increased visual prominence and altered the placeholder text to "search by topic."

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For variant B, the search bar had increased visual prominence, the placeholder text was altered to "search by topic," and the search function searched the blog, rather than the whole site.

For variant C, the search bar had increased visual prominence, the placeholder text was changed to "search the blog," and the search function searched the blog, rather than the whole site.

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As a result, HubSpot found that all three variants increased the conversion rate. However, variant C showed a 3.4% increase in conversion rate and a 6.46% increase in users who engage in the search bar.

2.Groove's Landing Page Design

Every marketer will have to build a landing page at some point. But building a landing page that'll convert is hard.

Groove experienced that first hand when the company learned one of its landing pages was only converting at 2.3%.

However, Groove wasn't sure why the page wasn't converting. To figure it out, its team went on a journey. They looked up resources and talked to marketing experts to figure out why their site wasn't working.

That's when the company learned that the messaging was all wrong. To figure out how to appeal to its customers, Groove decided to reach out and actually talk to real users.

Then, when the team rebuilt their landing page, they focused on copy first, and design second. Only when the copy was completely finished and approved did they start the visual aspect of designing.

Overall, the tweaks to messaging ultimately doubled their conversions to 4.7%.

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3.Csek Creative Homepage Design

The copy on your homepage is important because it helps users decide whether they want to continue looking deeper into your site.

In this example, a digital agency decided to test the tagline on its homepage. Ultimately, the goal was to decrease the bounce rate.

Before the A/B test, Csek's tagline read: "Csek Creative is a Kelowna based digital agency that delivers the results that make business sense."

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To make the copy less vague and more explanatory of the services it offered, Csek Creative changed the verbiage to: "Csek Creative is a digital agency that helps companies with their online and offline marketing needs."

9 A/B Testing Examples From Real Businesses (6)

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Expecting minor results, this change actually resulted in an 8.2% increase in click-throughs to other pages on the site.

4.Humana's Site Banners

Many landing pages showcase large banners at the top of the page. That's valuable real estate, and if the banner isn't optimal, it could end up doing more harm than good.

That's why Humana, a healthcare insurance provider, decided to test its landing page banners.

In the control, Humana had been using a banner that displayed a lot of copy, a weak CTA, and no clear and concise message.

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However, for variation B the company decided to simplify the message. This variation ended up receiving 433% more clickthroughs than the control.

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Humana didn't stop there. Once variant B became successful, the company decided to make it the new control and wanted to test the CTA.

With variation C, Humana switched the CTA language to include language that was a harder sell, such as "Shop." The company decided this would be a good approach because customers signing up for Medicare have a limited window to make a decision.

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The change in language resulted in a 192% increase in clickthrough.

Email A/B Testing Example

5. HubSpot's Email vs. In-App Notification Center

Gathering reviews from users isn't always an easy task. That's why HubSpot decided to A/B test ways to reach out to customers. The methods tested? In-app notifications versus email.

HubSpot decided to send an in-app notification and email alerting users that they were the champion user of the month and would receive a $10 gift card if they left a review on the Capterra site.

For variant A, HubSpot sent a plain text email to users.

9 A/B Testing Examples From Real Businesses (10)For variant B, HubSpot used a certification, templated email.

9 A/B Testing Examples From Real Businesses (11)

For variant C, HubSpot sent an in-app notification.

9 A/B Testing Examples From Real Businesses (12)

HubSpot found that unlike with emails, in-app notifications are often overlooked or missed by users. The emails outperformed in-app notifications by 1.4x. From both emails, 24.9% of those who opened the email left a review, compared to 10.3% of those who opened the in-app notification.

6. Unbounce's Tweet vs. Email CTA

On most landing pages, marketers typically ask users for an email address to deliver their content offers.

However, Unbounce decided to test whether customers would rather give an email address or just tweet about a product.

Both options have pros and cons for the company. Asking for an email address means your company can build a list of potential prospects while asking people to tweet can build viral momentum and increase social exposure.

The first landing page in this A/B test asked users to give their email address in exchange for an ebook.

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9 A/B Testing Examples From Real Businesses (13)

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The second landing page asked users to send a tweet in exchange for the ebook.

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Overall, people far preferred giving out an email address. In the end, the email landing page had a 24% conversion lift.

Mobile A/B Testing Example

7. HubSpot's Mobile Calls-to-Action

HubSpot uses several different calls-to-action in its blog posts. For instance, on this blog, you'll notice anchor text in the introduction, a graphic CTA at the bottom, and a slide-in CTA when you scroll through the post.

However, on mobile, these CTAs might seem intrusive. That's why HubSpot tested mobile CTAs.

Previous A/B tests revealed that HubSpot's mobile audience was 44% more likely to click through to an offer landing page and 18% more likely to convert on the offer if all CTAs were stripped from blog posts and there was only one CTA bar at the bottom of the page with no ability to exit.

So, HubSpot decided to test different versions of the bottom-of-the-page CTA bar, using thank you page views as the primary metric and CTA clicks as the secondary metric.

HubSpot used four variants for this test.

For variant A, the control, the traditional placement of CTAs remained unchanged.

For variant B, the CTA had a maximize/minimize option so readers could dismiss the CTA. This could be accomplished by an up/down caret.

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For variant C, the CTA had an X that would completely dismiss the CTA from the post. At this point, there would be no formal CTA on the blog.

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For variant D, the CTA had no X or minimize/maximize option.

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Overall, variant B saw a 7.9% increase, variant C saw an 11.4% decrease, and variant D saw a 14.6% increase.

From those numbers, HubSpot was able to project that using variant D on mobile would lead to about 1,300 additional submissions each month.

8. Houseparty’s Mobile Onboarding Design

Houseparty is a social app where users can have face-to-face conversations with their close friends. The business had a goal to incrementally improve the functionality and design of the app without causing significant dips in metrics, so it opted to use multiple A/B tests.

One of the things Houseparty aimed to improve was the onboarding funnel and how users are prompted to add friends through push notifications. Originally, users received permission requests to access their phone contacts with little context, and most users clicked “Don’t Allow” (as shown in the image below), making it difficult to connect with friends on the app.

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After running A/B tests to improve this experience for customers, Houseparty notifies users of pop-up notifications and their context before they occur to understand why giving access is important (as shown in the image below).

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The final version, which was A/B tested, found that users sent 2X more friend requests on their first day, and there was a 15% increase in permissions to access contacts.

9. HelloFresh Menu Display

HelloFresh is a meal kit subscription service that delivers recipes to global users. As its user base grew, its recipe count grew, but it became more difficult for users to navigate through the app and find what they needed.

The business set out to redesign its menu pages for a seamless user experience while also drawing attention to upselling opportunities. HelloFresh ran an experiment that compared the impact of the original control menu display to a new version. The image below shows the control menu display.

9 A/B Testing Examples From Real Businesses (20)

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And the image below displays the variant and final version, which contributed to a 7% increase in upselling revenue.

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A/B Testing Takeaways for Marketers

A lot of different factors can go into A/B testing, depending on your business needs. However, there are a few key things to keep in mind:

  • Every A/B test should start with a hypothesis focused on one specific problem that you can test.
  • Ensure you’re testing a control variable (your original version) and a treatment variable (a new version that you think will perform better).
  • You can test various things, like landing pages, CTAs, emails, or mobile app designs.
  • The best way to understand if your results mean something is to determine statistical significance once the experiment is over.
  • There are a variety of goals to focus on for A/B testing (increased site traffic, lower bounce rates, etc.), but they should be testable and able to be supported or disproven.
  • When testing, ensure you’re splitting your sample groups equally and randomly, so your data is viable and not due to chance.
  • Take action based on the results you obtain.

These companies all saw these amazing results because they started testing. If you want to get the same results, you've got to get started, too. For more information, be sure to check out the on-demand webinar "Optimize Your Online Marketing Channels," hosted by Optimizely and HubSpot.

Editor's note: This post was originally published in October 2014 and has been updated for comprehensiveness.

Originally published Oct 12, 2021 2:00:00 PM, updated October 12 2021

Topics:

(Video) A/B Testing for Data Science (with Python & R)

a-b-testing

FAQs

What is an example of AB testing? ›

Here are some examples of what that would look like in an A/B Testing Hypothesis: Shortening contact submission forms to only contain required fields would increase the number of sign-ups. Changing the call-to-action text from “Download now” to “Download this free guide” would increase the number of downloads.

How do companies use AB tests? ›

About 77 percent of businesses run A/B tests on their websites (including landing pages) to identify design, font, and other such issues. This helps reduce cart abandonment by highlighting what causes buyers to abort a cart. There can be a variety of reasons such as a poor layout, hidden costs, etc.

What is AB testing in business? ›

A/B testing, also known as split testing, refers to a randomized experimentation process wherein two or more versions of a variable (web page, page element, etc.) are shown to different segments of website visitors at the same time to determine which version leaves the maximum impact and drives business metrics.

Where you can use AB test on things other than web pages? ›

10) Can you run A/B tests on things other than web pages? Yes! In addition to landing pages and webpages, many marketers run A/B tests on emails, PPC campaigns, and calls-to-action. Email: Email testing variables include the subject line, personalization features, and sender name, among others.

What is meant by AB testing in marketing Mcq? ›

Internet Marketing MCQs

A/B testing (also known as split testing) is the process of comparing two versions of a web page, email, or other marketing asset and measuring the difference in performance. You do this by giving one version to one group and the other version to another group.

What is AB testing on Social Media? ›

A/B testing is some of the most basic testing you can do on social media. The definition of an A/B test is a test where you change one variable and keep everything else the same. For example, if you want to learn which type of content results in the highest engagement on Instagram, you could test photo content vs.

What industries use AB tests? ›

A/B testing is used by data engineers, marketers, designers, software engineers, and entrepreneurs, among others. Many positions rely on the data from A/B tests, as they allow companies to understand growth, increase revenue, and optimize customer satisfaction.

What is AB testing in Facebook? ›

A/B testing lets you compare two versions of an ad strategy by changing variables such as ad creative, audience or placement. We show each version to a segment of your audience and ensure that nobody sees both, then determine which version performs best.

What is AB testing in simple words? ›

A/B testing (also known as split testing) is the process of comparing two versions of a web page, email, or other marketing asset and measuring the difference in performance. You do this giving one version to one group and the other version to another group.

Why are AB tests used? ›

There are several benefits of A/B testing. A/B testing lets you increase user engagement, reduce bounce rates, increase conversion rates, minimize risk, and effectively create content. Running an A/B test can have significant positive effects on your site or mobile app.

How do you do ab test on Google ads? ›

To create an A/B test:
  1. Go to your Optimize Account (Main menu > Accounts).
  2. Select your container.
  3. Click Create experiment.
  4. Enter an experiment name (up to 255 characters).
  5. Enter an editor page URL (the web page you'd like to test).
  6. Click A/B test.
  7. Click Create.

Why do companies use scientific A B tiny experiments? ›

By running experiments, debugging the results (which we will discuss in a little bit), and interpreting them, companies will not only gain valuable experience with what metrics work best for certain types of tests but also develop new metrics.

What are the most common types of a B tests? ›

Common Uses

A/B Testing is the least complex method of evaluating a page design and is helpful in various situations. One of the most common ways of A/B testing is to test two very different design directions against one another. You can do this in Optimizely using a redirect experiment.

Which of the following companies provides AB testing tools? ›

Google Optimize

Google Optimize offers a set of tools under the Google Marketing Platform to help brands improve their website's performance. Their A/B testing tool, in particular, offers more than just the standard A/B testing.

Is AB testing the same as hypothesis testing? ›

The process of A/B testing is identical to the process of hypothesis testing previously explained. It requires analysts to conduct some initial research to understand what is happening and determine what feature needs to be tested.

How do you answer AB test questions? ›

How to design A/B testing interview questions
  1. Focus on what you're trying to understand about the candidate's knowledge and skills. ...
  2. With product management roles, focus on how they make decisions. ...
  3. With data science roles, focus on statistical skills. ...
  4. Design questions that are relevant to your company's day-to-day.
15 Jun 2022

What falls under the A B testing tools Mcq? ›

50) __________ falls under the A/B testing tools. Explanation: Visual Website optimizer (VWO), Google Content Experiments, and Optimizely are the most commonly used A/B testing tools.

What is AB testing in data science? ›

A/B testing is a type of experiment in which you split your web traffic or user base into two groups, and show two different versions of a web page, app, email, and so on, with the goal of comparing the results to find the more successful version.

Can you a B test on LinkedIn? ›

A/B testing on LinkedIn is an effective and relatively easy way to optimize your targeting and make sure you're engaging your target audiences with your messages or posts.

What is media testing in advertising? ›

Media testing: measure the performance of alternative media plans before making your decision.

How do you do ab test content? ›

6 Highly Productive Ways To AB Test Content Marketing
  1. Split Test Your Headlines. Your headline is arguably the most important piece of your content. ...
  2. Split Test Your Featured images. ...
  3. Find Your Ideal Content Length. ...
  4. Take Your Opt-in Forms Seriously. ...
  5. Split Test Your CTAs.
18 Oct 2016

What is an AB test Netflix? ›

We split a random sample of Netflix members into two groups using random assignment. Group “A” receives the current product experience, while Group “B” receives some change that we think is an improvement to the Netflix experience. Here, Group “B” receives the “Upside Down” product experience.

When should you not use an AB test? ›

4 reasons not to run a test
  • Don't A/B test when: you don't yet have meaningful traffic. ...
  • Don't A/B test if: you can't safely spend the time. ...
  • Don't A/B test if: you don't yet have an informed hypothesis. ...
  • Don't A/B test if: there's low risk to taking action right away.
13 Dec 2015

What is a hypothesis in AB testing? ›

A hypothesis is a prediction you create prior to running an experiment. It states clearly what is being changed, what you believe the outcome will be and why you think that's the case. Running the experiment will either prove or disprove your hypothesis. Hypotheses are bold statements, not open-ended questions.

How many ads are in AB test? ›

To get valid A/B test results, you'll need at least 100 conversions per each ad variation. If your cost-per-conversion is $2.50 and you want to test 4 different ad variations, your testing budget should be around $2.5 x 4 x 100 = $1,000.

How will you create an AB test for a marketing campaign? ›

To conduct an A/B test, you change one aspect of your campaign and run both variants, collecting data on performance. You can then implement the change that got the better results. For example, you might write two different phrases for your call-to-action (CTA) button on a landing page.

What is product a B testing? ›

An A/B test is used to determine which version or variant of something will perform more effectively in the market. This strategy is commonly used by marketing and advertising professionals, who show multiple versions of an ad, marketing email, or web page to randomly selected users, and then analyze the results.

What is a B testing in email? ›

A/B testing, in the context of email, is the process of sending one variation of your campaign to a subset of your subscribers and a different variation to another subset of subscribers, with the ultimate goal of working out which variation of the campaign garners the best results.

How long do you run a B testing? ›

For you to get a representative sample and for your data to be accurate, experts recommend that you run your test for a minimum of one to two week. By doing so, you would have covered all the different days which visitors interact with your website.

How do you make a successful testing program? ›

A beginners guide to establishing a successful testing and optimization program
  1. Organize the program & identify your goals. ...
  2. Identify opportunities & build pipeline. ...
  3. Develop tactical strategy. ...
  4. Get your first test live. ...
  5. Establish regular testing cadence. ...
  6. Evangelize wins.
13 Apr 2018

What significance level would you target in an a B test? ›

Ideally, all A/B test reach 95% statistical significance, or 90% at the very least. Reaching above 90% ensures that the change will either negatively or positively impact a site's performance. The best way to reach statistical significance is to test pages with a high amount of traffic or a high conversion rate.

How is an AB lift test calculated? ›

Step 2: Calculate Incremental Lift in Revenue Per Session

Formula: Subtract revenue per session of the control from the test treatment. Then, divide that number by the revenue per session of test treatment and multiply the answer by 100.

Does Google Ads have AB testing? ›

Google Ads A/B testing helps the AI to learn your audience's preferences. As you test more and more campaigns, you'll gain a deeper analytic view of your audience segments. As well as the marketing they respond to best. The way that Google's machine learning works means that it can optimize to your audience.

How do I verify a Google ad copy? ›

Overview of the ad copy testing process
  1. Select or create an ad group that receives, at a minimum, 10000 impressions per week. ...
  2. Decide on the goal such as click-through rate or action rate, that you want the ad group to achieve.
  3. Choose the statistical significance that you want to the ad copy test to achieve.

How do I set up AB test on Facebook? ›

When you access Ads Manager, go to the "Campaigns" tab. Under that tab, you'll see an option for "A/B Test." Keep in mind that you'll need to have an existing ad campaign or campaign draft in order to complete the test. Select your desired campaign, and then you can choose which variable you want to test.

Is a B testing legal? ›

A/B Testing Pricing Is Legal* and Ethical* but Can't Replace a Pricing Strategy.

What is the main reason to run a B tests or split tests for campaigns? ›

Split testing, commonly referred to as A/B testing, allows marketers to compare two different versions of a web page — a control (the original) and variation — to determine which performs better, with the goal of boosting conversions.

Which of the following is a significant disadvantage of a B testing? ›

A/B testing can take a lot longer to set up than other forms of testing. Setting up the A/B system can be a resource and time hog, although third-party services can help. Depending on the company size, there may be endless meetings about which variables to include in the tests.

What is an example of AB testing? ›

Here are some examples of what that would look like in an A/B Testing Hypothesis: Shortening contact submission forms to only contain required fields would increase the number of sign-ups. Changing the call-to-action text from “Download now” to “Download this free guide” would increase the number of downloads.

What are the types of AB testing? ›

There are three subtypes of A/B testing w=that you should know about:
  • Split testing. In split testing, you test a completely new version of an existing web page to analyze which one performs better. ...
  • Multivariate testing. ...
  • Multi-page testing.
24 Apr 2022

What are the types of testing? ›

The different types of tests
  • Unit tests. Unit tests are very low level and close to the source of an application. ...
  • Integration tests. ...
  • Functional tests. ...
  • End-to-end tests. ...
  • Acceptance testing. ...
  • Performance testing. ...
  • Smoke testing.

What is VWO AB testing? ›

A/B testing is the practice of comparing multiple variations of elements on your webpage at a time and picking out the best. You can perform A/B tests at different levels- you can test different colours of the CTA button, change the headlines, etc.

Is Google optimize free? ›

And Optimize is now immediately available to everyone — for free. This is not a test: You can start using it today. A recent survey showed 45% of small and medium businesses don't optimize their websites through A/B testing.

What is Vwo testing? ›

VWO is the world's leading web testing and conversion optimization platform that enables growing businesses to optimize their web experience across desktop, mobile, and other devices, to deliver a unique experience.

How do you test a null hypothesis? ›

The typical approach for testing a null hypothesis is to select a statistic based on a sample of fixed size, calculate the value of the statistic for the sample and then reject the null hypothesis if and only if the statistic falls in the critical region.

Which of the following are examples of real world testing? ›

An example of a real-world scenario that could be covered by a unit test is a checking that your car door can be unlocked, where you test that the door is unlocked using your car key, but it is not unlocked using your house key, garage door remote, or your neighbour's (who happen to have the same car as you) key.

What is a hypothesis also known as? ›

Synonyms. proposition, supposition, theory, thesis Visit the Thesaurus for More.

What is an AB test Netflix? ›

We split a random sample of Netflix members into two groups using random assignment. Group “A” receives the current product experience, while Group “B” receives some change that we think is an improvement to the Netflix experience. Here, Group “B” receives the “Upside Down” product experience.

What is AB testing in Facebook? ›

A/B testing lets you compare two versions of an ad strategy by changing variables such as ad creative, audience or placement. We show each version to a segment of your audience and ensure that nobody sees both, then determine which version performs best.

Is AB testing the same as hypothesis testing? ›

The process of A/B testing is identical to the process of hypothesis testing previously explained. It requires analysts to conduct some initial research to understand what is happening and determine what feature needs to be tested.

Why do we do AB testing? ›

A/B testing points to the combination of elements that helps keep visitors on site or app longer. The more time visitors spend on site, the likelier they'll discover the value of the content, ultimately leading to a conversion.

How testing is done in Netflix? ›

Real-Time allocations provide analysts with the ability to configure rules which are evaluated as the user interacts with Netflix. Eligible users are allocated to the test in real-time if they meet the criteria specified in the rules and are not currently in a conflicting test.

What Stack does Netflix use? ›

Netflix tech stack

The Netflix app is based on multiple programming languages: Python, Node. JS, Java, Kotlin, and Swift. This is done to ensure all-round compatibility of the Netflix app across multiple platforms: browsers, smart TVs, smartphones, and gaming consoles.

How many experiments does Netflix run? ›

Twenty-odd years ago, most big companies would run just a handful of experiments each year. Today, the most innovative businesses run thousands–Intuit: 1,300, P&G: 7,000–10,000, Google: 7,000, Amazon: 1,976, and Netflix: 1,000–thanks to a combination of new technologies and “lean” business approaches.

How do you do ab test on Google ads? ›

To create an A/B test:
  1. Go to your Optimize Account (Main menu > Accounts).
  2. Select your container.
  3. Click Create experiment.
  4. Enter an experiment name (up to 255 characters).
  5. Enter an editor page URL (the web page you'd like to test).
  6. Click A/B test.
  7. Click Create.

How do you do ab test on Instagram ads? ›

To perform A/B testing, also known as split testing, you separate your audience into two random groups. Each group is then shown a different variation of the same ad. After that, you compare the responses to determine which variation works better for you.

How do you do ab test content? ›

6 Highly Productive Ways To AB Test Content Marketing
  1. Split Test Your Headlines. Your headline is arguably the most important piece of your content. ...
  2. Split Test Your Featured images. ...
  3. Find Your Ideal Content Length. ...
  4. Take Your Opt-in Forms Seriously. ...
  5. Split Test Your CTAs.
18 Oct 2016

What are the most common types of a B tests you can run? ›

Common Uses

One of the most common ways of A/B testing is to test two very different design directions against one another. You can do this in Optimizely using a redirect experiment.

What is null hypothesis in a B testing? ›

The null hypothesis is a baseline assumption that there is no relationship between two data sets. When a statistical hypothesis test is run, the results either disprove the null hypothesis or they fail to disprove the null hypothesis.

How do you test a null hypothesis? ›

The typical approach for testing a null hypothesis is to select a statistic based on a sample of fixed size, calculate the value of the statistic for the sample and then reject the null hypothesis if and only if the statistic falls in the critical region.

What is AB testing in simple words? ›

A/B testing (also known as split testing) is the process of comparing two versions of a web page, email, or other marketing asset and measuring the difference in performance. You do this giving one version to one group and the other version to another group.

When should you not use an AB test? ›

4 reasons not to run a test
  1. Don't A/B test when: you don't yet have meaningful traffic. ...
  2. Don't A/B test if: you can't safely spend the time. ...
  3. Don't A/B test if: you don't yet have an informed hypothesis. ...
  4. Don't A/B test if: there's low risk to taking action right away.
13 Dec 2015

What is AB testing in statistics? ›

What Should You Know About A/B Testing? Like any type of scientific testing, A/B testing is basically statistical hypothesis testing, or, in other words, statistical inference. It is an analytical method for making decisions that estimates population parameters based on sample statistics.

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