Google Optimize Là Gì


What is A/B testing?

A/B testing (also known as split testing or bucket testing) is a method of comparing two versions of a webpage or phầm mềm against each other to determine which one performs better. A/B testing is essentially an experiment where two or more variants of a page are shown to lớn users at random, and statistical analysis is used lớn determine which variation performs better for a given conversion goal.

Bạn đang xem: Google optimize là gì


Running an A/B chạy thử that directly compares a variation against a current experience lets you ask focused questions about changes to lớn your trang web or ứng dụng và then collect data about the impact of that change.

Testing takes the guesswork out of website optimization và enables data-informed decisions that shift business conversations from "we think" lớn "we know." By measuring the impact that changes have on your metrics, you can ensure that every change produces positive results.

How A/B testing works

In an A/B demo, you take a webpage or ứng dụng screen và modify it to lớn create a second version of the same page. This change can be as simple as a single headline, button or be a complete rethiết kế of the page. Then, half of your traffic is shown the original version of the page (known as the control) and half are shown the modified version of the page (the variation).


As visitors are served either the control or variation, their engagement with each experience is measured & collected in a dashboard & analyzed through a statistical engine. You can then determine whether changing the experience had a positive, negative sầu or neutral effect on visitor behavior.


Why you should A/B test

A/B testing allows individuals, teams and companies to lớn make careful changes khổng lồ their user experiences while collecting data on the results. This allows them lớn construct hypotheses & to lớn learn why certain elements of their experiences impact user behavior. In another way, they can be proven wrong—their opinion about the best experience for a given goal can be proven wrong through an A/B test.

More than just answering a one-off question or settling a disagreement, A/B testing can be used khổng lồ continually improve sầu a given experience or improve sầu a single goal lượt thích conversion rate over time.

A B2B technology company may want to improve their sales lead unique & volume from chiến dịch landing pages. In order to achieve that goal, the team would try A/B testing changes to the headline, visual imagery, khung fields, Hotline to action and overall layout of the page.

Testing one change at a time helps them pinpoint which changes had an effect on visitor behavior, và which ones did not. Over time, they can combine the effect of multiple winning changes from experiments lớn demonstrate the measurable improvement of a new experience over the old one.


This method of introducing changes to lớn a user experience also allows the experience lớn be optimized for a desired outcome and can make crucial steps in a marketing chiến dịch more effective.

By testing ad copy, marketers can learn which versions attract more clicks. By testing the subsequent trang đích, they can learn which layout converts visitors to customers best. The overall spover on a sale chiến dịch can actually be decreased if the elements of each step work as efficiently as possible to acquire new customers.


A/B testing can also be used by sản phẩm developers và designers lớn demonstrate the impact of new features or changes khổng lồ a user experience. Product onboarding, user engagement, modals and in-product experiences can all be optimized with A/B testing, as long as goals are clearly defined và you have sầu a clear hypothesis.

Xem thêm: Cách Làm Bánh Granola Bar Là Gì, Granola Bar Là Gì

A/B testing process

The following is an A/B testing framework you can use to start running tests:

Collect data: Your analytics will often provide insight inkhổng lồ where you can begin optimizing. It helps khổng lồ begin with high traffic areas of your site or app to allow you to lớn gather data faster. Look for pages with low conversion rates or high drop-off rates that can be improved.

Identify goals: Your conversion goals are the metrics that you are using to determine whether or not the variation is more successful than the original version. Goals can be anything from clicking a button or links to lớn hàng hóa purchases và e-mail signups.

Generate hypothesis: Once you"ve sầu identified a goal you can begin generating A/B testing ideas & hypotheses for why you think they will be better than the current version. Once you have sầu a danh mục of ideas, prioritize them in terms of expected impact and difficulty of implementation.

Create variations: Using your A/B testing software (like, make the desired changes to lớn an element of your trang web or thiết bị di động app experience. This might be changing the color of a button, swapping the order of elements on the page, hiding navigation elements, or something entirely custom. Many leading A/B testing tools have a visual editor that will make these changes easy. Make sure lớn QA your experiment lớn make sure it works as expected.

Run experiment: Kiông xã off your experiment và wait for visitors khổng lồ participate! At this point, visitors to lớn your site or phầm mềm will be randomly assigned lớn either the control or variation of your experience. Their interaction with each experience is measured, counted and compared to determine how each performs.

If your variation is a winner, congratulations! See if you can apply learnings from the experiment on other pages of your site và continue iterating on the experiment lớn improve your results. If your experiment generates a negative sầu result or no result, don"t worry. Use the experiment as a learning experience và generate new hypothesis that you can demo.


Whatever your experiment"s outcome, use your experience to inform future tests & continually iterate on optimizing your ứng dụng or site"s experience.

A/B testing & SEO

Google permits & encourages A/B testing & has stated that performing an A/B or multivariate thử nghiệm poses no inherent risk to your website’s tìm kiếm rank. However, it is possible to lớn jeopardize your tìm kiếm rank by abusing an A/B testing tool for purposes such as cloaking. Google has articulated some best practices khổng lồ ensure that this doesn’t happen:

No cloaking: Cloaking is the practice of showing tìm kiếm engines different content than a typical visitor would see. Cloaking can result in your site being demoted or even removed from the tìm kiếm results. To prevent cloaking, do not abuse visitor segmentation to display different nội dung khổng lồ Googlebot based on user-agent or IP address.

Use 302 redirects instead of 301s: If you run a kiểm tra that redirect the original URL to lớn a variation URL, use a 302 (temporary) redirect vs a 301 (permanent) redirect. This tells search engines such as Google that the redirect is temporary và that they should keep the original URL indexed rather than the demo URL.

Run experiments only as long as necessary: Running tests for longer than necessary, especially if you are serving one variation of your page to lớn a large percentage of users, can be seen as an attempt lớn deceive tìm kiếm engines. Google recommends updating your site and removing all test variations your site as soon as a thử nghiệm concludes and avoid running tests unnecessarily long.

Xem thêm: Hướng Dẫn Tải Game Company Of Heroes 2 Full Việt Hóa, Company Of Heroes 2: Ardennes Assault

For more information on A/B testing and SEO, see our Knowledge Base article on how A/B testing impacts SEO.