The best decision is an informed decision, and A/B testing enables you to make data-backed decisions to improve your website. In this guide, you will learn the exact steps for running A/B tests for free.
Should you choose one design for your landing page or the other? Which one is better? How would you know?
To answer these questions and similar ones, web creators can turn to implementing A/B testing to choose the best option.
A/B testing gives you a way to make data-backed decisions and improvements to your website. Instead of trying to guess which version of a design will generate more conversions or create a more user-friendly experience, you can turn to the data to get a real answer.
Better yet, running A/B tests on WordPress isn’t that complicated and doesn’t cost any money. If you can put 30 minutes or so into some basic setup, you can start testing your site for free using a simple visual editor.
In this post, we’ll show you step-by-step how to start A/B testing WordPress and Elementor content using the free Google Optimize service.
Beyond that, we’ll also share a native WordPress plugin option for Elementor users that lets you set up split tests from inside the Elementor editor.
Ready to start testing? Let’s dig in!
#elementor #wordpress #testing
One essential skill that certainly useful for any data analytics professional to comprehend is the ability to perform an A/B testing and gather conclusions accordingly.
Before we proceed further, it might be useful to have a quick refresher on the definition of A/B testing in the first place. As the name suggests, we can think of A/B testing as the act of testing two alternatives, A and B, and use the test result to choose which alternative is superior to the other. For convenience, let’s call this type of A/B testing as the binary A/B testing.
Despite its name, A/B testing in fact can be made more general, i.e. to include more than two alternatives/classes to be tested. To name a few, analyzing click-through rate (CTR) from a multisegment digital campaign and redemption rate of various tiers of promos are two nice examples of such multiclass A/B testing.
The difference in the number of classes involved between binary and multiclass A / B testing also results in a slight difference in the statistical methods used to draw conclusions from them. While in binary testings one would straightforwardly use a simple t-test, it turns out that an additional (preliminary) step is needed for their multiclass counterparts.
In this post, I will give one possible strategy to deal with (gather conclusions from) multiclass A/B testings. I will demonstrate the step-by-step process through a concrete example so you can follow along. Are you ready?
#hypothesis-testing #a-b-testing #click-through-rate #t-test #chi-square-test #testing
Different Stages of Penetration Tests
The typical penetration testing is broken out in various phases, alike the cyberattack lifecycle. Every single phase has a goal that they require to achieve to further the attack.
#testing #penetration #penetration testing guide #a complete guide
The shift towards microservices and modular applications makes testing more important and more challenging at the same time. You have to make sure that the microservices running in containers perform well and as intended, but you can no longer rely on conventional testing strategies to get the job done.
This is where new testing approaches are needed. Testing your microservices applications require the right approach, a suitable set of tools, and immense attention to details. This article will guide you through the process of testing your microservices and talk about the challenges you will have to overcome along the way. Let’s get started, shall we?
Traditionally, testing a monolith application meant configuring a test environment and setting up all of the application components in a way that matched the production environment. It took time to set up the testing environment, and there were a lot of complexities around the process.
Testing also requires the application to run in full. It is not possible to test monolith apps on a per-component basis, mainly because there is usually a base code that ties everything together, and the app is designed to run as a complete app to work properly.
Microservices running in containers offer one particular advantage: universal compatibility. You don’t have to match the testing environment with the deployment architecture exactly, and you can get away with testing individual components rather than the full app in some situations.
Of course, you will have to embrace the new cloud-native approach across the pipeline. Rather than creating critical dependencies between microservices, you need to treat each one as a semi-independent module.
The only monolith or centralized portion of the application is the database, but this too is an easy challenge to overcome. As long as you have a persistent database running on your test environment, you can perform tests at any time.
Keep in mind that there are additional things to focus on when testing microservices.
Test containers are the method of choice for many developers. Unlike monolith apps, which lets you use stubs and mocks for testing, microservices need to be tested in test containers. Many CI/CD pipelines actually integrate production microservices as part of the testing process.
As mentioned before, there are many ways to test microservices effectively, but the one approach that developers now use reliably is contract testing. Loosely coupled microservices can be tested in an effective and efficient way using contract testing, mainly because this testing approach focuses on contracts; in other words, it focuses on how components or microservices communicate with each other.
Syntax and semantics construct how components communicate with each other. By defining syntax and semantics in a standardized way and testing microservices based on their ability to generate the right message formats and meet behavioral expectations, you can rest assured knowing that the microservices will behave as intended when deployed.
It is easy to fall into the trap of making testing microservices complicated, but there are ways to avoid this problem. Testing microservices doesn’t have to be complicated at all when you have the right strategy in place.
There are several ways to test microservices too, including:
What’s important to note is the fact that these testing approaches allow for asynchronous testing. After all, asynchronous development is what makes developing microservices very appealing in the first place. By allowing for asynchronous testing, you can also make sure that components or microservices can be updated independently to one another.
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Automation and segregation can help you build better software
If you write automated tests and deliver them to the customer, he can make sure the software is working properly. And, at the end of the day, he paid for it.
Ok. We can segregate or separate the tests according to some criteria. For example, “white box” tests are used to measure the internal quality of the software, in addition to the expected results. They are very useful to know the percentage of lines of code executed, the cyclomatic complexity and several other software metrics. Unit tests are white box tests.
#testing #software testing #regression tests #unit tests #integration tests