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.

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Feature Experimentation

Showing 52

Full Stack tests show as an ID number instead of Experiment Name.

Expected Experience Full stack tests should be reported using Flag Names and not flag id numbers on https://app.optimizely.com/v2/accountsettings/account/usage . Makes review difficult. Actual Experience (please describe what you see): For the acc...
almost 2 years ago in Feature Experimentation / Project / Account Configuration / Settings 1 Future consideration

Handle the error the occurs when copying rules from another environment

When one environment already has an experiment in it, and you try to add a new rule by copying over the rules from another environment, the UI throws a confusing error that says "Updating production ruleset for flag <flagKey> failed. {"Inval...
almost 2 years ago in Feature Experimentation / Feature Flagging Workflows 1 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...
almost 2 years ago in Feature Experimentation / Other 1 Future consideration

Supporting Custom Javascript or some inbuilt functions in the Audience Builder

We would like to be able to perform some minimal data manipulation before matching when creating audiences. Either supporting custom javascript in Audience Builder in the Full Stack version, or accommodating common Javascript or optimizely custom ...
almost 2 years ago in Feature Experimentation / SDKs & Agent 0 Future consideration

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 ...
about 2 years ago in Feature Experimentation 0 Future consideration

Add possibility to define Variations directly within a Rule

Currently, Variations are created separately. It should be similar to Page targeting settings in Web, which also can be defined separately and reused, OR defined directly in the experiment
about 2 years ago in Feature Experimentation / Experiment Authoring 1 Future consideration

On any listing page there should be sorting options

No description provided
about 2 years ago in Feature Experimentation 1 Future consideration

On the Results page, the Name of the Flag that an experiment is based on should be displayed

Currently, only the "Rule key" is displayed, not the Flag name or key. The Rule keycan include the name (/key) of the Flag, but it doesn't have to. So especially when having multiple Results pages open side by side, it's very difficult to distingu...
about 2 years ago in Feature Experimentation 1 Future consideration

Make React SDK Provider less brittle

React SDK provider should just be a context provider with its own useOptimiselyContext hook for getting and setting context. If setting the client and user id were separated either with their own functions or even when initialising context somehow...
about 2 years ago in Feature Experimentation 0 Future consideration

Notification listeners - send data to analytics reporting only experiment decision data, NOT everyone that was evaluated for the flag.

(SDK 4.0) Considering an experiment which is set on top of a flag with only % of traffic being assign to it, the 'leftovers' (users not assigned) receive the same control experience as assigned in expriment (flag/variant = Off). Because of this, w...
about 2 years ago in Feature Experimentation 0 Future consideration