Hi team. is this a acceptable practice to use multiple useFeature in a page ?

const Sample: React.FC = () => {
  const feature1 = useFeature('feature1');
  const feature2 = useFeature('feature2');

  return (
    <>
      <Button color={feature.value || 'blue'}>feature1</Button>
      <Button color={feature.value || 'blue'}>feature2</Button>
    </>
  );
};

export default Sample;

And also do we get experiment for multiple a/b testings in trackingCallback: async (experiment, result) ?

Hi, We are using BigQuery with a custom event source and are trying to set up the Experiment Assignment Queries for the data source. Have some questions about that process: 1. Confused on how to get the

viewed_experiment

table in BigQuery. Are the records in this table supposed to be events triggered by the SDK's

trackingCallback

? 2. We want to add Dimensions to this table (like the GrowthBook UI suggests). If Dimensions = Targeting Attributes, how do we get those into the same event that populates the

viewed_experiment

table? It doesn't seem like the

trackingCallback

returns with the Targeting Attributes, what's the best practice here?

We have Growthbook set up in our React app already, but are looking to set it up for our landing pages, which are currently built on Webflow. Do you have any recommendations on the best setup practices for a website built in an external Website builder (noting that we can add in customer code, including HTML / script tags). We'd prefer not to use Google Tag Manager.

re: bayesian - is there a way for us to tell the engine what are our informed priors? or does the engine just assume an alpha=1,beta=1 prior? ideally we'd like to use the previous x months of conversion data as the prior going into the evaluation (but it would be good if this could also be configured). one of the reasons GB is particularly attractive is its use of bayesian probabilities - but in order for us to maximize the value there we would need to supply the calculation process with our prior distribution data.

Hey are you planning to include a way of updating the value of a feature flag in the sdk for JavaScript? Something like:

gb.updateFeatureFlag('feature-flag-key', true);

Is there a way to automatically stop an experiment when certain number of users has been reached? We want to make sure that experiments don’t run longer than needed and automatically stop when the required sample size has been reached.

Hi. We use GB to run A/B tests, often with many variations. Often, when developing or QAing a change, we'll want to force a specific variation to be served. Currently, we have two ways to do this: • Serve 100% of that variation on Staging environment. ◦ This is annoying because it requires that we go into GB for each change, and for larger changes when we want multiple people to review, it requires lots of coordination etc • Use incognito or multiple browsers and re-open/refresh so that we get a new user id and thus served a new version ◦ This is annoying because its non-deterministic and doesn't work if the A/B test is being run deeper into the experience I'm wondering if theres a good way / known pattern to allow for forcing a specific version without modifying the split.

Hey! Loving that we now can create ratio metrics where the analysis unit <> randomization unit. We have a lot of use cases for this, so thanks! 🙌 🙌 I have created a couple of them, and they seem to calculate the rate ok, but the violin plot and Chance to beat control calculation is off (see picture). Is this the case for others too, or is it just with us? Both the nominator and denominator work well by itself.

Hi, is there a way to change the table that the experiments in growthBook look for? "viewed_experiment" does not align with our naming standards

Hi - We are looking to self host Growthbook for a POC, and will host the required components in Azure. Is using Cosmos DB or MongoDB Atlas on Azure instead of a standalone Mongo DB instance a tested and valid configuration ?