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A / B testing as one of the most important tools for site and application optimization is a test suitable for measuring two versions of a website or application, which ultimately improves the user experience and ultimately increases site traffic and behavior by analyzing user behavior and behavior. The rate is converted. In this article, we will introduce you to 15 successful implementation steps and 4 advantages of A / B testing.

What is an A / B test?

The A / B test, also used as a split test, is a marketing test in which you divide your audience to evaluate changes to a campaign and determine which ones work best. In other words, you can show version A of one piece of marketing content to half of your audience and show version B to the rest.

To run the A / B test, you must create two different versions of a piece of content with changes to a variable. You then show these versions to two audiences of the same size and analyze which one performs better over a period of time (a period in which you have enough time to draw conclusions from your results).

A / B testing helps marketers see how one version of one piece of marketing content performs better than another. Here are two types of A / B tests you can use to increase your conversion rate:

Example 1: User experience testing

You may want to see if placing a call button at the top of the home screen instead of placing it in the sidebar will increase click-through rates.

To test this with the A / B test, create an alternative webpage that incorporates the same change. This existing design or control is called your version A. Version B is called Challenger. You then show these two versions to a predetermined percentage of site visitors. The percentage of visitors who view each version should be the same. Learn how to easily test an A / B component of your website with HubSpot's Marketing Hub.

Example 2: Design test

You may want to know if changing the call button will increase your click-through rate.

To test this theory in A / B, you need to design an alternative call button with a different color that leads to the same landing page. Best Alexa Rank Services To Buy Online If you use the red call button in your marketing content and the green button gets a higher click-through rate after testing, it will change the default color of your call button to green from now on.

A / B testing and SEO

Google licenses and endorses A / B testing, stating that performing A / B testing or multivariate testing poses no risk to a website 's search ranking. However, it is possible that your search rank will be compromised by misusing the A / B testing tool for purposes such as hiding.

Google has announced some of its best practices to ensure that this does not happen.

No concealment

Hiding is a way to show different content in search engines instead of displaying normal content to a user. Hiding may cause your site to be downgraded or removed from search results. To avoid concealment, do not abuse the fact that the visitor wants to show different content to Google Bot based on the IP address or user agency.

Use rel = ”canonical”

If you run the splitter test with multiple URLs, you must use the rel = ”canonical” attribute to show the changes in the original version of the page. Doing so will not confuse Google Bot with multiple versions of the same page.

Use 302 redirects instead of 301 redirect

If you are using an A / B test that redirects the original URL to a variable URL, use a 302 (temporary) redirect instead of a 301 (permanent) redirect. This tells search engines like Google that the redirect is temporary and they should keep the original URL instead of indexing the test URL.

Experiment only when needed

Running the test for too long, especially when you are switching to your page for a higher percentage of users, should be taken as an attempt to deceive search engines. Google recommends that you update your site and remove all test changes from your site as soon as the test is completed and avoid long-term testing.

Advantages of A / B testing

A / B testing brings benefits to the marketing team depending on what test you decide to take. In addition, these tests are of great value to the business because they are low cost but the results are excellent.

Suppose you hire a content producer with a salary of $ 50,000 a year. This content producer has produced 5 articles per week for the company's blog, which eventually reaches 260 articles per year. If the average post on a corporate blog generates 10 leads, it can be said that creating business leads to only $ 192 ($ 50,000 ده 260 articles = $ 192 per article), which is a significant change.

  1. Increase website traffic

Test whether using different blog posts or different titles on a web page will change the number of people who click on a hyperlinked title to go to your website. As a result, it increases website traffic.

  1. 2. Higher conversion rates

Testing the use of different locations, different colors, or even different anchor text (clickable text in the link) in the call can change the number of people who click on these calls to come to your landing page, and this increases the number of people who click on Your website will fill out a form, send you their contact information and they will become a clue.

  1. Lower jump rates

If your website visitors leave (or jump) to your website immediately after visiting, testing different blog post introductions, different fonts, or different images can reduce this bounce rate or bounce rate and get more visitors. Maintain.

  1. Leave fewer payment pages

According to MightyCall, e-commerce businesses have found that 40 to 75 percent of their customers have left the site despite choosing products in their shopping cart. This process is called "leaving the shopping page." Test whether using different product images, different page design, and even shipping costs can reduce cracking rates.

It is now best to use a checklist to get started and evaluate the A / B test.

Steps of performing A / B test

Before the A / B test

Remember to do the following steps before performing the test.

  1. Select a variable to perform the test

As you optimize your web pages and emails, you may find the variables you are trying to test, but to evaluate how effective this change will be, you need to isolate a standalone variable and evaluate its performance. Otherwise you cannot be sure which variables have changed the performance.

You can use more than one variable for a web page or email. Just be sure to test them at the same time. Take a look at the various elements in resources and their alternatives to design, word, and layout. Other things you can test include email subject lines, sender name, and other ways to personalize your email.

  1. 2. Identify your goal

Although you have several criteria for each test, consider one initial criterion before running the test. In fact, do it before you make the second change. This is called your "dependent variable". Think about where this variable is going to be at the end of the split test. You may make a formal hypothesis and evaluate your results based on this prediction.

If you have been waiting until then to see which metrics are most important to you, what your goals are, and how the changes you are proposing might affect user behavior, you may not run the test as you should.

  1. Create a control and a challenger

You now have the independent variable, the dependent variable, and the desired result. Use this information as a control to run an unmodified version of everything you are testing. If you are testing a webpage, this is an unmodified webpage that already exists. If you are testing a landing page, this is the design and copy of the landing page that you normally use. From there, make a change or a challenge to test the login page or email you want to control. For example, if you are confused as to whether placing a certificate on the landing page makes a difference, run your control panel without a certificate, then apply the change with a certificate.

  1. Divide your sample groups randomly and evenly

In tests where you have more control over the contacts, such as emails, you have to test with one or more contacts with the same number to get definitive results.

How you do this depends on the type of A / B testing tool you are using. If you are a HubSpot Enterprise customer running an A / B test on an email, HubSpot automatically divides the traffic for any changes you make. Therefore, each change you receive receives a random sample of visitors.

  1. Specify your sample size (if applicable)

How you determine the size of your sample depends on the A / B test tool and the type of A / B test you perform. If you are testing the A / B of an email, you may want to send an A / B test to a smaller section of your list so that you can get statistical results. Finally, you select a winner and send the winner change to the rest of the list (see the divisor test science e-book at the end of this article so you can calculate your sample size more accurately). If you are a HubSpot Enterprise customer, you can help determine the size of your sample group using a slider. This slider allows you to run a 50/50 A / B test of any sample size - although other sample dividers require a list of at least 1,000 recipients.

  1. Decide on the importance of your results

Once you have chosen your target criteria, think about the importance of your results to know which change to choose over the other. Statistical significance is another very important part of the A / B testing process that is often misunderstood. If you need a review about the statistical significance from a marketing point of view, I recommend reading this blog post.

  1. Make sure you run only one test per campaign

Testing more than one thing for a campaign can complicate your results even if that test is not done on the same asset. For example, if you test an email campaign that redirects to a landing page and at the same time tests the landing page A / B, how do you know which change has increased the lead?

During the A / B test

The following steps are also important during the A / B test

  1. Use the A / B testing tool

You must use the A / B testing tool to test A / B on a website or in an email. If you are a HubSpot Enterprise customer, HubSpot software has features that allow you to test A / B emails, calls, and sales pages. For the non-HubSpot Enterprise customer, other options include Google Analytics tests, which allow you to test more than ten A / B versions of a web page and compare its performance using a random sample of users.

  1. Test both changes simultaneously

Scheduling plays an important role in the results of your marketing campaign, this schedule can be hour of the day, day of the week or month of the year. If you are going to run version A over the course of a month and version B over the next month, how do you know if the modified performance is different due to the design or a different month?

When you perform the A / B test, you must make both changes at all times. Otherwise, your results are secondary.

  1. Take enough time to test the A / B to generate useful data

You are looking to make sure your test has enough time to run to get a significant sample size. Otherwise, it is difficult to tell if there is a statistically significant difference between the two changes. How long is the right time to run the test? Depending on the company and how you run the A / B test, statistically significant results can occur in a matter of hours, days, or weeks. An important part of how long it takes to get statistically significant results is how much traffic you receive. So if your business does not get a lot of traffic to your website, you need to spend more time running A / B testing.

  1. 11. Ask for feedback from real users

A / B testing does a lot of work with quantitative data, but it does not necessarily help you understand why people do certain things compared to others while you are doing A / B testing. Why not get quality feedback from real users? You can also buy real website traffic and is One of the best ways to get feedback from others is to use polls. You may have an outbound poll on your site asking users why they did not click the call button, or a survey on thank you pages asking visitors why they clicked a button and filled out a form.

After A / B testing

After the A / B test, consider the following:

  1. 12. Focus on your goal metrics

Although you are evaluating several metrics, focus on the primary goal metric when performing the analysis. For example, if you tested two changes to an email and considered the clue as your primary criterion, do not be distracted by click-through rates. You may find that the click-through rate is high and the conversion rate is low, in which case you may choose a change that has a lower click-through rate.

  1. Evaluate the significance of your results using the A / B test calculator

Now that you have determined which change works best, it's time to determine if your results are statistically significant. In other words, can they be trusted enough to make a difference? To know this, you need to do a statistical significance test. You can do this manually or you can give the test results to a free A / B test calculator. For each change you test, you can enter the total number of attempts you made, such as emails sent, or impressions seen. Then enter the number of goals that have been completed. Usually you look at clicks for this, but other types of conversions can be considered as well.

۱۴. Take action based on the results

If one change is statistically better than the other, you have a winner between the two changes. Complete your test by disabling the loser variable in the A / B test tool. If none of these changes are statistically better, you will find that your tested variable has no effect on the results, and you declare the test invalid. In this case, stick to the main variable or run another test. You can use the failed data to help you get the number of iterations to run your new test.

  1. 15. Plan your next A / B test

The A / B test you have just done will help you find a new way to make your marketing content more effective, but don't stop there. There is always room for optimization.

Sources:

https://t.me/BuyWebTraffic/20

A / B testing as one of the most important tools for site and application optimization is a test suitable for measuring two versions of a website or application, which ultimately improves the user experience and ultimately increases site traffic and behavior by analyzing user behavior and behavior. The rate is converted. In this article, we will introduce you to 15 successful implementation steps and 4 advantages of A / B testing.

What is an A / B test?

The A / B test, also used as a split test, is a marketing test in which you divide your audience to evaluate changes to a campaign and determine which ones work best. In other words, you can show version A of one piece of marketing content to half of your audience and show version B to the rest.

To run the A / B test, you must create two different versions of a piece of content with changes to a variable. You then show these versions to two audiences of the same size and analyze which one performs better over a period of time (a period in which you have enough time to draw conclusions from your results).

A / B testing helps marketers see how one version of one piece of marketing content performs better than another. Here are two types of A / B tests you can use to increase your conversion rate:

Example 1: User experience testing

You may want to see if placing a call button at the top of the home screen instead of placing it in the sidebar will increase click-through rates.

To test this with the A / B test, create an alternative webpage that incorporates the same change. This existing design or control is called your version A. Version B is called Challenger. You then show these two versions to a predetermined percentage of site visitors. The percentage of visitors who view each version should be the same. Learn how to easily test an A / B component of your website with HubSpot's Marketing Hub.

Example 2: Design test

You may want to know if changing the call button will increase your click-through rate.

To test this theory in A / B, you need to design an alternative call button with a different color that leads to the same landing page. Best Alexa Rank Services To Buy Online If you use the red call button in your marketing content and the green button gets a higher click-through rate after testing, it will change the default color of your call button to green from now on.

A / B testing and SEO

Google licenses and endorses A / B testing, stating that performing A / B testing or multivariate testing poses no risk to a website 's search ranking. However, it is possible that your search rank will be compromised by misusing the A / B testing tool for purposes such as hiding.

Google has announced some of its best practices to ensure that this does not happen.

No concealment

Hiding is a way to show different content in search engines instead of displaying normal content to a user. Hiding may cause your site to be downgraded or removed from search results. To avoid concealment, do not abuse the fact that the visitor wants to show different content to Google Bot based on the IP address or user agency.

Use rel = ”canonical”

If you run the splitter test with multiple URLs, you must use the rel = ”canonical” attribute to show the changes in the original version of the page. Doing so will not confuse Google Bot with multiple versions of the same page.

Use 302 redirects instead of 301 redirect

If you are using an A / B test that redirects the original URL to a variable URL, use a 302 (temporary) redirect instead of a 301 (permanent) redirect. This tells search engines like Google that the redirect is temporary and they should keep the original URL instead of indexing the test URL.

Experiment only when needed

Running the test for too long, especially when you are switching to your page for a higher percentage of users, should be taken as an attempt to deceive search engines. Google recommends that you update your site and remove all test changes from your site as soon as the test is completed and avoid long-term testing.

Advantages of A / B testing

A / B testing brings benefits to the marketing team depending on what test you decide to take. In addition, these tests are of great value to the business because they are low cost but the results are excellent.

Suppose you hire a content producer with a salary of $ 50,000 a year. This content producer has produced 5 articles per week for the company's blog, which eventually reaches 260 articles per year. If the average post on a corporate blog generates 10 leads, it can be said that creating business leads to only $ 192 ($ 50,000 ده 260 articles = $ 192 per article), which is a significant change.

  1. Increase website traffic

Test whether using different blog posts or different titles on a web page will change the number of people who click on a hyperlinked title to go to your website. As a result, it increases website traffic.

  1. 2. Higher conversion rates

Testing the use of different locations, different colors, or even different anchor text (clickable text in the link) in the call can change the number of people who click on these calls to come to your landing page, and this increases the number of people who click on Your website will fill out a form, send you their contact information and they will become a clue.

  1. Lower jump rates

If your website visitors leave (or jump) to your website immediately after visiting, testing different blog post introductions, different fonts, or different images can reduce this bounce rate or bounce rate and get more visitors. Maintain.

  1. Leave fewer payment pages

According to MightyCall, e-commerce businesses have found that 40 to 75 percent of their customers have left the site despite choosing products in their shopping cart. This process is called "leaving the shopping page." Test whether using different product images, different page design, and even shipping costs can reduce cracking rates.

It is now best to use a checklist to get started and evaluate the A / B test.

Steps of performing A / B test

Before the A / B test

Remember to do the following steps before performing the test.

  1. Select a variable to perform the test

As you optimize your web pages and emails, you may find the variables you are trying to test, but to evaluate how effective this change will be, you need to isolate a standalone variable and evaluate its performance. Otherwise you cannot be sure which variables have changed the performance.

You can use more than one variable for a web page or email. Just be sure to test them at the same time. Take a look at the various elements in resources and their alternatives to design, word, and layout. Other things you can test include email subject lines, sender name, and other ways to personalize your email.

  1. 2. Identify your goal

Although you have several criteria for each test, consider one initial criterion before running the test. In fact, do it before you make the second change. This is called your "dependent variable". Think about where this variable is going to be at the end of the split test. You may make a formal hypothesis and evaluate your results based on this prediction.

If you have been waiting until then to see which metrics are most important to you, what your goals are, and how the changes you are proposing might affect user behavior, you may not run the test as you should.

  1. Create a control and a challenger

You now have the independent variable, the dependent variable, and the desired result. Use this information as a control to run an unmodified version of everything you are testing. If you are testing a webpage, this is an unmodified webpage that already exists. If you are testing a landing page, this is the design and copy of the landing page that you normally use. From there, make a change or a challenge to test the login page or email you want to control. For example, if you are confused as to whether placing a certificate on the landing page makes a difference, run your control panel without a certificate, then apply the change with a certificate.

  1. Divide your sample groups randomly and evenly

In tests where you have more control over the contacts, such as emails, you have to test with one or more contacts with the same number to get definitive results.

How you do this depends on the type of A / B testing tool you are using. If you are a HubSpot Enterprise customer running an A / B test on an email, HubSpot automatically divides the traffic for any changes you make. Therefore, each change you receive receives a random sample of visitors.

  1. Specify your sample size (if applicable)

How you determine the size of your sample depends on the A / B test tool and the type of A / B test you perform. If you are testing the A / B of an email, you may want to send an A / B test to a smaller section of your list so that you can get statistical results. Finally, you select a winner and send the winner change to the rest of the list (see the divisor test science e-book at the end of this article so you can calculate your sample size more accurately). If you are a HubSpot Enterprise customer, you can help determine the size of your sample group using a slider. This slider allows you to run a 50/50 A / B test of any sample size - although other sample dividers require a list of at least 1,000 recipients.

  1. Decide on the importance of your results

Once you have chosen your target criteria, think about the importance of your results to know which change to choose over the other. Statistical significance is another very important part of the A / B testing process that is often misunderstood. If you need a review about the statistical significance from a marketing point of view, I recommend reading this blog post.

  1. Make sure you run only one test per campaign

Testing more than one thing for a campaign can complicate your results even if that test is not done on the same asset. For example, if you test an email campaign that redirects to a landing page and at the same time tests the landing page A / B, how do you know which change has increased the lead?

During the A / B test

The following steps are also important during the A / B test

  1. Use the A / B testing tool

You must use the A / B testing tool to test A / B on a website or in an email. If you are a HubSpot Enterprise customer, HubSpot software has features that allow you to test A / B emails, calls, and sales pages. For the non-HubSpot Enterprise customer, other options include Google Analytics tests, which allow you to test more than ten A / B versions of a web page and compare its performance using a random sample of users.

  1. Test both changes simultaneously

Scheduling plays an important role in the results of your marketing campaign, this schedule can be hour of the day, day of the week or month of the year. If you are going to run version A over the course of a month and version B over the next month, how do you know if the modified performance is different due to the design or a different month?

When you perform the A / B test, you must make both changes at all times. Otherwise, your results are secondary.

  1. Take enough time to test the A / B to generate useful data

You are looking to make sure your test has enough time to run to get a significant sample size. Otherwise, it is difficult to tell if there is a statistically significant difference between the two changes. How long is the right time to run the test? Depending on the company and how you run the A / B test, statistically significant results can occur in a matter of hours, days, or weeks. An important part of how long it takes to get statistically significant results is how much traffic you receive. So if your business does not get a lot of traffic to your website, you need to spend more time running A / B testing.

  1. 11. Ask for feedback from real users

A / B testing does a lot of work with quantitative data, but it does not necessarily help you understand why people do certain things compared to others while you are doing A / B testing. Why not get quality feedback from real users? You can also buy real website traffic and is One of the best ways to get feedback from others is to use polls. You may have an outbound poll on your site asking users why they did not click the call button, or a survey on thank you pages asking visitors why they clicked a button and filled out a form.

After A / B testing

After the A / B test, consider the following:

  1. 12. Focus on your goal metrics

Although you are evaluating several metrics, focus on the primary goal metric when performing the analysis. For example, if you tested two changes to an email and considered the clue as your primary criterion, do not be distracted by click-through rates. You may find that the click-through rate is high and the conversion rate is low, in which case you may choose a change that has a lower click-through rate.

  1. Evaluate the significance of your results using the A / B test calculator

Now that you have determined which change works best, it's time to determine if your results are statistically significant. In other words, can they be trusted enough to make a difference? To know this, you need to do a statistical significance test. You can do this manually or you can give the test results to a free A / B test calculator. For each change you test, you can enter the total number of attempts you made, such as emails sent, or impressions seen. Then enter the number of goals that have been completed. Usually you look at clicks for this, but other types of conversions can be considered as well.

۱۴. Take action based on the results

If one change is statistically better than the other, you have a winner between the two changes. Complete your test by disabling the loser variable in the A / B test tool. If none of these changes are statistically better, you will find that your tested variable has no effect on the results, and you declare the test invalid. In this case, stick to the main variable or run another test. You can use the failed data to help you get the number of iterations to run your new test.

  1. 15. Plan your next A / B test

The A / B test you have just done will help you find a new way to make your marketing content more effective, but don't stop there. There is always room for optimization.

Sources:

https://t.me/BuyWebTraffic/20

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