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A/B testing
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There are two options, two solutions. How to choose the best one? Today we're going to talk about a method that helps you compare and evaluate ads in all their manifestations. From design to color rendering, from layout to product description, from personal gimmicks to creative ideas.
A/B testing is a ‘fighter’ against intuitive marketing-’let's try it.’ Although the method is 100 years old, it is actively used by Google, Amazon, Fb and Netflix.
A/B testing is a marketing tool whose methodology, by dividing the audience, tests several variants of an advertising product and determines which one brings the best results. Customers, sales, profits.
In business, change is always a risk, whether it concerns products, management or advertising. Any wrong move can lead to lost profits. So how do you test your ideas without disrupting your established processes or negatively impacting your business?
A/B testing is a ‘fighter’ against intuitive marketing-’let's try it.’ Although the method is 100 years old, it is actively used by Google, Amazon, Fb and Netflix.
A/B testing is a marketing tool whose methodology, by dividing the audience, tests several variants of an advertising product and determines which one brings the best results. Customers, sales, profits.
In business, change is always a risk, whether it concerns products, management or advertising. Any wrong move can lead to lost profits. So how do you test your ideas without disrupting your established processes or negatively impacting your business?
A/B testing. Get Started Today
How does A/B testing work?
Which email generates more sales? You can find out by sending two versions of the same message to customers' emails (first, of course, you need to randomize the lists). A test of two contextual advertising ads allows you to choose the one that converts site visitors to customers more and more often.
One test, one parameter
To clearly understand what influenced the result, one experiment tests only one variable, one parameter.
That doesn't mean you can't test more than one variable. Just make sure that you are not testing them at the same time. Keep in mind that even small changes in the ad messenger can affect demand.
Which email generates more sales? You can find out by sending two versions of the same message to customers' emails (first, of course, you need to randomize the lists). A test of two contextual advertising ads allows you to choose the one that converts site visitors to customers more and more often.
One test, one parameter
To clearly understand what influenced the result, one experiment tests only one variable, one parameter.
That doesn't mean you can't test more than one variable. Just make sure that you are not testing them at the same time. Keep in mind that even small changes in the ad messenger can affect demand.
Define the goal, formulate hypotheses
Choose a key metric against which you will evaluate the effectiveness of your advertising campaigns. The test is conceived and implemented based on this metric. First of all consider CTR, number or percentage of conversions. Formulate hypotheses for the target audience and creatives.
‘Base’
You should have a base unchanged version of what you are testing. If you're experimenting with a particular page of the site, keep the original version. This will allow you to compare options and, if something goes wrong, allow you to ‘roll back’. If you're testing a landing page in a basic version, save its design or text.
Sampling: equally and randomly
For tests where you can control the target audience, such as when you send out emails to a customer base, test two or more equal audiences. It's impossible to predict the response to a particular ad in advance, so how long the test runs will directly affect the sample size.
Choose a key metric against which you will evaluate the effectiveness of your advertising campaigns. The test is conceived and implemented based on this metric. First of all consider CTR, number or percentage of conversions. Formulate hypotheses for the target audience and creatives.
‘Base’
You should have a base unchanged version of what you are testing. If you're experimenting with a particular page of the site, keep the original version. This will allow you to compare options and, if something goes wrong, allow you to ‘roll back’. If you're testing a landing page in a basic version, save its design or text.
Sampling: equally and randomly
For tests where you can control the target audience, such as when you send out emails to a customer base, test two or more equal audiences. It's impossible to predict the response to a particular ad in advance, so how long the test runs will directly affect the sample size.
Test at the same time
Analyzing the results of the test, it is important to understand on what day of the week, month and at what time the results were obtained. A/B test of two versions of the ad should be run in parallel and at the same time.
Results and segmentation of the target audience
In order to properly analyze the results of A/B testing, you need to carefully and slowly collect data on
- Which version got the most response from new visitors to the site
- which type of device or which version worked best on cell phones and which version worked best on desktop computers
- which source of traffic was most effective
- which version showed the best results given specific traffic sources
Analyzing the results of the test, it is important to understand on what day of the week, month and at what time the results were obtained. A/B test of two versions of the ad should be run in parallel and at the same time.
Results and segmentation of the target audience
In order to properly analyze the results of A/B testing, you need to carefully and slowly collect data on
- Which version got the most response from new visitors to the site
- which type of device or which version worked best on cell phones and which version worked best on desktop computers
- which source of traffic was most effective
- which version showed the best results given specific traffic sources
Testing by SyncraNova LLC.
A/B testing is not a panacea, but a great tool in the hands of professionals. SyncraNova LLC tests and validates the performance of all the marketing tools the customer uses. It helps:
1. Increase website traffic. SyncraNova marketers analyze the response to advertisements, testing: headlines, blog posts, images, text quantity, hyperlink clicks.
2. Increase conversion rates. In these A/B tests, we most often experiment with ad units, color rendering, and text size. We simulate anchor tests for CTAs and test the effectiveness of forms and applications.
3. Reduce bounce rate. SyncraNova LLC tests fonts, images, and anything else that can affect a visitor leaving the site quickly.
4. Understand the reasons why customers leave the site without completing the purchase process. When analyzing ‘abandoned carts’ they test: product photos, the design of order placement pages, the display of delivery costs, the operation of payment systems.
A/B testing is not a panacea, but a great tool in the hands of professionals. SyncraNova LLC tests and validates the performance of all the marketing tools the customer uses. It helps:
1. Increase website traffic. SyncraNova marketers analyze the response to advertisements, testing: headlines, blog posts, images, text quantity, hyperlink clicks.
2. Increase conversion rates. In these A/B tests, we most often experiment with ad units, color rendering, and text size. We simulate anchor tests for CTAs and test the effectiveness of forms and applications.
3. Reduce bounce rate. SyncraNova LLC tests fonts, images, and anything else that can affect a visitor leaving the site quickly.
4. Understand the reasons why customers leave the site without completing the purchase process. When analyzing ‘abandoned carts’ they test: product photos, the design of order placement pages, the display of delivery costs, the operation of payment systems.