I tried passing some cookie values to the growthbook attributes so that I can exclude users with those cookies. I was very surprised that attributes with a value of undefined passed the override rule test “if cookie1 exists”. Is this the intended behavior?

// js-cookie returns a string value of the cookie or undefined if it doesn't exist
const thirdPartyCookies = {
  cookie1: Cookies.get("cookie1"),
  cookie2: Cookies.get("cookie2"),
  cookie3: Cookies.get("cookie3"),
};

gbInit.setAttributes({
  ...gbInit.getAttributes(),
  ...thirdPartyCookies,
  id: svc.userId,
});

Hi, not sure if this a bug, or if I doing something wrong (on GB Cloud) When I start a experiment, I can see the updated experiment details on https://cdn.growthbook.io/api/features/sdk-[APIKEY] Now, when I manually Stop the experiment ("Not Finished"), the experiment details on https://cdn.growthbook.io/api/features/sdk-[APIKEY] do not update, they are still there set to "running". Only when I change the experiment details (e.g. change percentage split) and republish, these changes are updated in the payload (now "running" of course). So it generally seens to work, just the stop trigger doesn't seem to take effect. Haven't tested what happens when the experiment ends by itself. That means the variation seems to keep being delivered (tested with console.log), even when I stopped the experiment. Tested it a few times and could reproduce it.

I am running an A/B Test using the google analytics cookie as the Assignment Attribute. To my understanding that's all I need todo, and everything appears to be working as it should, but I am seeing the Multiple Exposures Warning as seen in the image below. Could anyone from the team share some possible reasons I am seeing this warning? I am open to answer any clarifying questions.

Might be a stupid question, but wondering why the metrics I sat up in GB, which seems to work fine (image 1), is not working when I run them on an experiment (image 2) The error message says _*Table “my_table” must be qualified with a dataset e.g. dataset.table*_ But can’t seem to understand where I can edit that query. Hope someone can help 🙂

I found some error in python SDK version 1.0.0. I think in file growthbook.py line 870 have bug.

Hi team, every now and then I see the following error in the console. Everything seems to be working fine generally though. I guess this is maybe a race condition?

Hi all, is there a way in v2.4.0 to see which variant was rolled out if an experiment won as in the first screenshot below? It seems that info is gone in this latest update (see second screenshot), but it was a very handy reference for my team (cc @ambitious-apartment-58735 @orange-magician-36994)

I'm not sure if this is the best place to report bugs (please let me know if not): When adding a variation and then deleting it again, the underlying logic does not update correctly. This also carries through to the payload being sent to the site. Copying a test doesn't help. Only solution I have found is recreating the test from scratch.

has renamed the channel from "feedback" to "give-feedback"

set the channel topic: Provide feedback or bug reports here. Use #request-features for that purpose. All other questions should go in #ask-questions or an SDK-specific channel.

set the channel description: Provide feedback or bug reports here. Use #request-features for that purpose. All other questions should go in #ask-questions or an SDK-specific channel.

Had some issues uploading images to an experiment

set the channel topic: Provide feedback or bug reports here. Use #request-features to request new features. All other questions should go in #ask-questions or an SDK-specific channel.

set the channel description: Provide feedback or bug reports here. Use #request-features to request new features. All other questions should go in #ask-questions or an SDK-specific channel.

[2.4.0 - self-hosted] When editing a metric to change the cap user values to go from an absolute cap to a percentile cap the edit doesn't save and no error is shown. (attempted

0.99

and

.99

etc as values in case there was some validation happening that it was between 0 and 1)

Hi! About ad-hoc reports - love then! 🎉 A couple of improvement suggestions. 1. It would be great if one could add an end date in retrospect. Right now I cant find a way of adding it again if it has been removed (picture 2) 2. Would be great to be able to copy an ad hoc report, or create another one from the existing report (picture 1)

Hi! I’ve just realized that the p-value that can be found in the frequentist report is based on two-sided hypothesis test. Is there a way to choose what type of hypothesis test I need (two-tailed or one-tailed) so I get the correct p-value? I actually found one-sided calculations in the source code but can’t find the appropriate setting in the interface.

Hi, it seems image upload for variants has stopped working on GB Cloud. I used it before, but now when I upload images (PNG), they don't show anymore.

Enjoying the project, thank you 🙏 It'd be great to open source the docs (if not already) to allow the community to contribute With Google Optimize retirement you'll no doubt have an influx of people coming across from that product (myself included) The journey of implementing growthbook via GTM was not the smoothest During installation I found this page misleading for 2 clear reasons: https://docs.growthbook.io/guide/google-tag-manager-and-growthbook 1. It's not clear in this configuration that you need to pass

url

as a user attribute a. Most other web based A/B testing packages detect URL via their own script and don't rely on that being passed through b. When you first create an account, the URL attribute is set up automatically c. The visual editor prompts you to do URL targeting d. URL targeted experiments wont work unless url is passed as a user attribute, I had to scrutinise a lot of pages to detect this issue. 2. It'd be great to provide an example in javascript of generating a UUID for anonymous users, a reliable example was hard to come by. but additionally when using GTM it needs to be an instance which does not use ES6

In SDK integration for GA4, it is recommended to get the user Id and/or Client ID attribute, and adjust the trackingCallback to send the experiment exposure. It is not obvious what adjustments the doc is referring to since passing the ID to the GA event should not be necessary.

I understand it’s a very long shot, but are there any plans to implement some functionality that would allow us to detect primacy and novelty effects? The literature is very scarce on the methodology but I’ve been trying to decypher this paper: https://arxiv.org/pdf/2102.12893.pdf but been having trouble

Was wondering what the plans are for slack. Would love to see things like: 1. Alert for experiment reaching significance 2. Alert for when a team stops and experiment

So when we implemented the self hosted version of Growthbook there was no information about implementing our own database solution and we just now sadly lost the data in our mongo db instance after our server ran out of RAM and we restarted it. Are there some docs regarding how to connect it to a separate database or any guidelines regarding how it should be implemented? 🙂

Hey Team, My colleagues and myself are interested in a session where different stakeholders across our org would like to ask questions and possibly a quick demo to outline features, roadmap, etc. How can I initiate this ?

Would be awesome to be able to see histograms of the metric data, and also for there to be normality- and heteroscedasticity test integrated. Do you have some thoughts on that? 😊

It would be really helpful if it was possible to duplicate tests between projects without loosing the targeting setup and feature configuration

Ahoi @fresh-football-47124 and @future-teacher-7046, the GrowthBook documentation page is down with 402 payment required. Can you bring it up again, please? Alternatively, is there a locally renderable version available as well? FYI @adventurous-dream-15065

Hi, there's an annoying lil bug with eventName on metrics. It doesn't seem to save the first time I create a new metric. After saving I have to edit and enter the eventName in again for it to save properly. Note: I've only tried this via duplicate metric.

Still having big problems with old data sources/metrics, that have been severely exacerbated by the new experiments system Context: we originally used Growthbook directly with Mixpanel (and our very oldest archived experiments are set to it), but moved to BigQuery We archived all the Mixpanel metrics (and seemingly these are now entirely invisible in the metrics list?), but it won't let us delete the Mixpanel data source, and there's no concept of archiving It was super annoying but not that big a deal - we just renamed it to

zzz do not use: Mixpanel

, though sadly it still appears first and is the default But with the new experiments system, every single experiment gets assigned to it automatically. Every single one requires our staff to go in and realize it's wrong and to update it, and if they don't, the results will be wrong/confusing Please could this be fixed somehow? Archiving data sources, or allowing us to delete the metrics, or setting a default source or something

We did also hit one other super annoying problem with the new experiments system. Overall we do really like it, it's much easier. But it's far less capable/expressive with complex conditions In many cases we use features more as sources of config with various rules, not just for rollouts etc. A lot of our features look like this - where we have long-standing/maintained behavior that continues after the actual analysis has long-since finished, but we need to preserve the behavior for the exact specific users In a lot of these cases, we also need to have the same experiment apply to multiple features (this seems to work okay) The key problem is that we sometimes need to have combined rules - i.e. additional conditions beyond those in the experiment targeting. e.g. if the experiment is on this variant, and the user is on the web version of the app, use this value. Whereas if they're on another version, use another value Ideally it'd be possible to add additional conditions on experiment rules, like the legacy ones allow