Customer Feedback

We love feedback from you on our products and the problems in your daily work that you would like us to solve. Please describe the challenge you're encountering and your desired outcome. Be as detailed as possible.

For technical issues or bugs please head to Support or our Developer Community. You can assign up to 20 votes in total. Thank you for your feedback.

Status explanation: 'Future Consideration' = Continuing to collect further feedback, not planned at this time. 'Investigating' = Prioritized for deeper customer and feasibility investigations ahead of planning development.

ADD FEEDBACK

Feature Experimentation

Showing 74

Archive Unused Rules (vs deleting them)

From a customer: The options are only to “Move To Top, Duplicate or Delete”. One does not necessarily want to delete past rules, in case one wants to re-use them or use them to duplicate them to create a slightly different rule etc. Therefore, the...
over 1 year ago in Feature Experimentation / Feature Flagging Workflows 0 Future consideration

Full Stack Experiment Scheduler

What is the problem you’re trying to solve with this request?Rather than providing a solution, please try to describe the problem in as much detail as possible. Calendar Experiment scheduling - on and off Repeatability Weekly, Monthly, Yearly, Cus...
about 3 years ago in Feature Experimentation / Feature Flagging Workflows 4 Already exists

Apply Audience Automatically At The Project Level

As an experimenter I would like to be able to have an audience auto populate for an entire project. The bot filtering provided within Optimizely does not exclude additional bots that we need to remove from testing as an organization, and therefore...
4 months ago in Feature Experimentation / Feature Flagging Workflows 0

When adding multiple audiences to a rule, don't default to matching ANY

When you add multiple audiences to a new rule, the default is to match ANY of the selected audiences. We always want to match ALL of the selected audiences, but our users often forget to change ANY to ALL. They put their experiment live and don't ...
over 2 years ago in Feature Experimentation 0 Future consideration

enable optimizely node sdk to work behind proxy

If sdk is meant to be initialised in air tight environment and you are meant to use proxy for security and audit reasons, then its impossible to do so with createInstance method from neither react nor node SDKs. Datafile wont be fetched, App will ...
over 1 year ago in Feature Experimentation / SDKs & Agent 0 Future consideration

Support setting userAttribute through Optimizely agent environment variable.

We have an enhancement request for https://github.com/optimizely/agent?tab=readme-ov-file#configuration-options. We want to be able to add a property or an environment variable so that we can add a key-value pair for the userAttribute mentioned in...
12 months ago in Feature Experimentation 0

GCP Cloud Functions + Edge SDK

Since we are now on Google Cloud a customer has asked us about the possibility of Edge functions similar to AWS Lambda for GCP
over 1 year ago in Feature Experimentation / SDKs & Agent 0 Future consideration

Bounce/exit metrics in Optimizely Full Stack

Bounce and exit rate are key metrics for our business, as they often reach statistical significance and are crucial for us as an indication of experiment performance. At present, these metrics are only available in the Optimizely Web product and n...
over 2 years ago in Feature Experimentation / Other 1 Future consideration

Let Editors create flag rules in production

It would be great if our Editor-level collaborators could create flag rules in the production environment. Particularly, because some of the experiments they create are going to be integrated with Contentful. And in Contentful, we want Editors to ...
6 months ago in Feature Experimentation / Experiment Authoring 0

Support OpenFeature

As a developer I want to be able to use an Optimizely provider for the CNCF OpenFeature project so that I don't have to learn a vendor-specific SDK to integrate my codebase with Optimizely resulting in faster adoption of Optimizely in my applications
about 1 year ago in Feature Experimentation / SDKs & Agent 0 Future consideration