Integrations in Wingify’s Feature Experimentation (FE) – Wingify

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Integrations help you connect Wingify’s Feature Experimentation (FE) product with other tools you use daily.

They let you dive deeper into your feature experiments, expand experimentation targeting options, and effectively power up personalized experiences.

Types of Integrations in FE

Integrating Wingify’s FE with any third-party tool

The callback function allows you to integrate Wingify with virtually any external tool. It lets you send data about feature flags and experiments directly to platforms like GA4, Mixpanel, Tealium, RudderStack, and more.

What exactly is a callback function?

A callback function is a custom code you write that is automatically executed by Wingify whenever certain events occur, such as when a user experiences a feature or participates in an experiment.

Example - Integrating GA4 with a callback

Whenever users interact with an experiment variation, Wingify triggers your callback function, sending structured data like feature ID, user ID, variation details, and custom variables to GA4.

You can then analyze this data in GA4 alongside your other metrics.

Here is an example code for implementing GA4 integration with Node. To implement it, you must replace the placeholders (SDKKey and accountId) with your Wingify credentials.

const wingifyClient = await wingify.init({
   sdkKey: 'your-sdk-key', // replace with your SDK key
   accountId: 'your-account-id', // replace with your account ID
   integrations: {
     callback(properties) {
       window.gtag('event', 'Wingify_Experiment', {
         feature_name: properties.featureName,
         feature_id: properties.featureId,
         user_id: properties.userId,
         variation_id: properties.experimentVariationId,
         experiment_key: properties.experimentKey,
         custom_variables: properties.customVariables
       });
     }
   }
});

Here's a snapshot of the data structure your callback receives as a response from Wingify:

JSON

{
featureName: "NewCheckout",
featureId: 123,
featureKey: "checkout_update",
userId: "user_456",
api: "getFlag",
customVariables: {"location": "USA"},
rolloutId: 789,
rolloutKey: "rollout_checkout",
rolloutVariationId: 1,
variationTargetingVariables: {"device": "mobile"},
experimentId: 321,
experimentKey: "exp_checkout_test",
experimentVariationId: 2
}

You can implement this easily in your preferred SDK:

Integrating FE with cloud storage

You can export your raw experiment and feature usage data directly to your AWS S3 bucket or Google Cloud Storage, which connects seamlessly with all popular data warehouses.

To find out how you can configure and set up these integrations, please refer to:

Integrating FE with warehouses

You can also send the data to your data warehouses directly in a table format. For more information on how to implement this for the two most popular data warehouses, see Integrating Wingify with Snowflake and Integrating Wingify with BigQuery.

This helps your data teams analyze results across multiple dimensions and metrics you might not have initially configured in Wingify while setting up the experiment. You can combine experimentation data with your internal dashboards and play with data freely for deeper insights.

Integrating FE with code editor

The Wingify Feature Management extension for Visual Studio Code allows developers to efficiently manage feature flags directly within their editor, eliminating the need to switch to the Wingify dashboard.

Key functionalities include:

Feature flag explorer: View, organize, and manage feature flags by environment.
Quick toggles: Enable or disable flags without leaving the editor.
Environment selection: Easily switch between development, testing, and production environments.
Code snippets: Quickly insert code for initializing Wingify SDK, retrieving feature flags, and handling flag variables tailored to your coding language.
Contextual actions: Manage rules and variations through intuitive right-click menus.
Easy search: Find flags quickly by name or associated rules

Setup involves entering your Wingify Account ID and API Access Token to fetch and manage environments.

NOTE: This extension requires Visual Studio Code v1.54.0 or higher and an active Wingify account.

Learn more about the usage and commands. Check out the extension available on the VS Code Marketplace.

Need more help?

For further assistance or more information, contact Wingify Support.

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