Changes you make in the visual editor now also show the selector of the element that was changed. This makes it easier to see which element has been changed.

Plan your experiments and define in advance when your experiments should start and end automatically.

Editor: Changes can also be deleted from edited variants.

Filter your Shopify Experiment results by the products you specify.

Carry out quality assurance before you start your experiments. With the new QA mode, this is easier than ever before.

Share the Varify results reports with your stakeholders. To do this, you can simply create shareable reports directly in the respective experiment to be shared.

Connect your experiments with PostHog - and evaluate them directly in Varify.
You can easily import your experiment data into Varify via an API interface and analyze it there centrally.

In the account history, you can see which user has made changes to your account at any given time.

With the BigQuery auto setup, you can use BigQuery directly to analyze your experiments with just one click.

Add decimal places to the traffic allocation. 

Evaluate your A/B tests directly in Varify with your Shopify data. Varify imports your Shopify data for conversions and revenue values.

The setting "Exclude Duplicate User Events" can now be used directly in every report. With this setting you define whether your goals only count once per user or are counted multiple times. 

Save your page targeting and audience targeting conditions as a segment. This way, you can easily reuse them in other experiments without having to recreate everything.

In addition to simple URL targeting, you can now also link different URLs with each other. You can also target via CSS selector or JavaScript.

Set up your web analytics integration with just one click or choose a manual custom integration.

Geotargeting conducts experiments for visitors who come from a specific and defined geographical area.

You can apply an outlier adjustment to your experiment results to improve the accuracy of statistical significance calculations for sales metrics in A/B experiments.

Update the baseline variant in the reporting of your experiments. This allows you to define a variant other than the originals as the baseline against which all other variations are compared.

With a user interface, you can now create segments to reach specific users. The interface enables targeting on devices, browsers and IP addresses. Targeting via JavaScript is still possible.

https://varify.io/nutzerdokumentation/audience-targeting/

Server calls can be configured so that the initial request does not run via app.varify.io, but is routed via your own subdomain. https://varify.io/nutzerdokumentation/cname/

Experiments are played out immediately, even without consent. With a special function, you decide as soon as the permanent variant assignment takes place and the tracking events are sent to your web analytics tool. https://varify.io/nutzerdokumentation/varify-consent-mode/

Increase the security of your login by activating multi-factor authentication.

Control and manage your experiments via the Experiment API. 

Display a notification in the GA4 tracking setup if Google Signals is activated.

You can now find details such as test start, test end and many more in each of your experiment reports.

In the reporting view of your experiments, you can now filter your results by "Device" and "New or Existing Users". 

In addition to GA4, you can now also analyze your data directly using the raw data in BigQuery. Simply select the events you want to compare in the variants of your experiment from a drop-down menu.

Now sort your experiments by update or creation date. Pagination has also been improved.

With the Chrome extension, the active experiments are displayed on every page. You can also switch between different variants within an experiment.

The editor URL can now be subsequently edited. This is useful if you want to open the editor on other URLs that are also part of the experiment.

Archive the experiments that you no longer need. GA4 Audiences are also automatically archived in GA4. This ensures that only the GA4 audiences used remain active and that you do not exceed the limit of 100 GA4 audiences.

Now simply adjust the margin or padding of your elements on the website.

If you have set up your transaction IDs in GA4, your revenue goals will now show a calculation of significance.

If you hover over a styling option in the floating editor with the mouse pointer, the name of the styling option behind it will be displayed.

Varify.io® experiments can now also be analyzed and evaluated directly in etracker. 

The start date of an experiment is now preselected in the reports and the revenue metrics now show the calculation of the Average Revenue per User (ARPU).

Evaluate your A/B tests directly in Varify.io®. A separate reporting page is available for newly created experiments. Both the uplift per variant and the significance are calculated.

By entering the Varify-Force URL parameter, the group can be assigned to any variant.

Tracking can now be deactivated for individual experiments so that tracking requests can be saved. 

With the help of the breadcrumb selector, elements below or above can be easily selected.

Change the arrangement of the elements within a container by swapping them.

With the "Add HTML" function, new content can easily be added anywhere on the website. Our user documentation contains ready-made templates that you are welcome to use.

Split URL tests can now be evaluated just as easily as all other A/B tests. It is no longer necessary to carry out the evaluation via the page location.

Varify.io now provides an Anti Flicker Script. With the Anti Flicker Script you will no longer see any flickering on the page.

Duplicates of existing variants can now be created. In addition, variants can now be renamed.

Changes using the visual editor can now also be applied to user-defined selectors. 

This integration connects Varify.io® with Snowplow so that the data from the experiments can be used there.

This extension enables the creation of unlimited variations within a single experiment.

With the Chrome extension from Varify.io, quality assurance can be carried out quickly and easily.

This integration connects Varify.io® with Matomo so that the data from the experiments can be used there.

Due to policy changes at Google, it is now necessary to insert scripts directly instead of using the account ID as before.

For the significance test of the A/B tests, we have provided the first version of the significance calculator.

For testing, the addresses localhost and *.shopifypreview.com and are now accessible in the varify.io editor.

Start or pause A/B tests with a simple mouse click and quickly check the status - live or paused - with our new indicator!

For the implementation of the platform and tracking, we have created simple step-by-step tutorials to supplement the documentation.

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