Flutter SDK quickstart

Part 1: Create a sample app

1. Access or create your account

You need an Optimizely account to follow this guide. If you do not have an account, you can register for a free account. If you already have an account, navigate to your Flags-enabled project.

2. Get your SDK key

To find your SDK key in an Optimizely project:

Go to Settings > Primary Environment.
Copy and save the SDK Key for your primary environment.

📘
Note
Each environment has its own SDK key.

3. Copy the sample code

To work with the SDK:

Install the Flutter plugin in Android Studio.
In Android Studio, create a new Flutter project (File -> New -> New Flutter Project...) called optimizely_flutter_quickstart.
Select Java for Android language. Select Swift for iOS language.
Toggle Android and iOS for Platform.

Click Finish.
To install the Optimizely Feature Experimentation Flutter SDK. Open the pubspec.yaml file and add:

dependencies:
  optimizely_flutter_sdk: ^1.0.1

📘
Note
The Flutter SDK is currently in open beta.
It has been fully tested but if you see any bugs, please use the Suggest Edits on the top right of this doc or contact your Customer Success Manager.

The full source code is available on GitHub.

Copy the following code sample into the main.dart file (located in the lib directory) for your app. Replace <Your_SDK_Key> with the SDK key you found in a previous step.

import 'dart:math';
import 'package:flutter/material.dart';
import 'package:optimizely_flutter_sdk/optimizely_flutter_sdk.dart';
import 'dart:async';

// NOTE: You need to change this SDK key to your project's SDK Key
const String sdkKey = "Your_SDK_Key";
const String logTag = "OPTIMIZELY_QUICK_START";

void main() {
  runApp(const MyApp());
  var productSorter = ProductSorter();
  productSorter.initializeQuickStart();
}

class MyApp extends StatefulWidget {
  const MyApp({Key? key}) : super(key: key);

  @override
  State<MyApp> createState() => _MyAppState();
}

class _MyAppState extends State<MyApp> {
  String uiResponse = 'Unknown';

  @override
  void initState() {
    super.initState();
  }

  @override
  Widget build(BuildContext context) {
    return MaterialApp(
      home: Scaffold(
        appBar: AppBar(
          title: const Text('Quick start example app'),
        ),
        body: Center(
          child: Text(uiResponse),
        ),
      ),
    );
  }
}

class ProductSorter {
  String _datafileHost = "https://cdn.optimizely.com";
  String _datafileSuffixAndroid = "/datafiles/%s.json";
  String _datafileSuffixIOS = "/datafiles/%@.json";

  Future<void> initializeQuickStart() async {
    // Setting up custom datafile URL format
    Map<ClientPlatform, DatafileHostOptions> datafileHostOptions = {};

    datafileHostOptions[ClientPlatform.android] =
        DatafileHostOptions(_datafileHost, _datafileSuffixAndroid);

    datafileHostOptions[ClientPlatform.iOS] =
        DatafileHostOptions(_datafileHost, _datafileSuffixIOS);

    // Initializing OptimizelyClient
    var flutterSDK = OptimizelyFlutterSdk(
        sdkKey, datafileHostOptions: datafileHostOptions);
    var response = await flutterSDK.initializeClient();
    if (response.success) {
      flutterSDK.addConfigUpdateNotificationListener((msg) {
        runQuickStart(flutterSDK);
      });
      await runQuickStart(flutterSDK);
    }
  }

  Future<void> runQuickStart(OptimizelyFlutterSdk flutterSDK) async {
    /* --------------------------------
     * to get rapid demo results, generate random users. Each user always sees the same variation unless you reconfigure the flag rule.
     * --------------------------------
     */
    // simulate 50 users
    var rangeMax = 9999;
    var rangeMin = 1000;
    var range = Random();
    var hasOnFlags = false;

    for (int i = 0; i < 10; i++) {
      var userId = "${range.nextInt(rangeMax - rangeMin) + rangeMin}";
      /* --------------------------------
       Create hardcoded user & bucket user into a flag variation
       --------------------------------
      */
      var user = await flutterSDK.createUserContext(userId);
      // "product_sort" corresponds to a flag key in your Optimizely project
      var decisionResponse = await user!.decide("product_sort");
      var decision = decisionResponse.decision;
      // did decision fail with a critical error?
      if (decision?.variationKey == null) {
        print("\n\n$logTag decision error: ${decisionResponse.reason}");
      }
      // get a dynamic configuration variable
      // "sort_method" corresponds to a variable key in your Optimizely project
      String sortMethod = decision?.variables["sort_method"] as String;

      if (decision!.enabled) {
        // Keep count how many visitors had the flag enabled
        hasOnFlags = true;
      }
      /* --------------------------------
         Mock what the users sees with print statements (in production, use flag variables to implement feature configuration)
         --------------------------------
      */
      var userIdResponse = await user.getUserId();
      // always returns false until you enable a flag rule in your Optimizely project
      print("\n\n$logTag Flag ${(decision.enabled
          ? "on"
          : "off")}. User number ${userIdResponse.userId} saw flag variation: ${decision
          .variationKey} and got products sorted by: ${sortMethod} config variable as part of flag rule: ${decision
          .ruleKey}");
    }
    if (!hasOnFlags) {
      print(
          "\n\n$logTag Flag was off for everyone. Some reasons could include:" +
              "\n1. Your sample size of visitors was too small. Rerun, or increase the iterations in the FOR loop" +
              "\n2. By default you have 2 keys for 2 project environments (dev/prod). Verify in Settings>Environments that you used the right key for the environment where your flag is toggled to ON." +
              "\nCheck your key at  https://app.optimizely.com/v2/projects/YOUR_PROJECT_ID/settings/implementation");
    }
  }
}

📘
Note
Do not run your app yet. You still need to set up the flag and flag delivery rule in the Optimizely app.

Part 2: Run your app

At this point, your app does nothing. You first need to create a flag and a flag delivery rule in the Optimizely app to enable the app.

1. Create the feature flag

A feature flag lets you control which users to expose new feature code to in your app. For this quickstart, imagine you are rolling out a redesigned sorting feature for displaying products.

Create a flag in Optimizely named product_sort and give it a variable named sort_method:

Go to Flags > Create Flag.
Name the flag key product_sort and click Create Flag, which corresponds to the flag key in your sample app.
Go to Default Variables and click New (+).
Set the variable type to String.
Name the variable sort_method, which corresponds to the variable key in your sample app.
Set the variable default value to alphabetical. This represents your old sorting method.

Click Save in the lower right corner to save the variable.
Go to Variations and click the default "on" variation. A variation is a wrapper for a collection of variable values.
Set the sort_method variable value to popular_first. This represents your new sorting method.

Click Save.

2. Create the flag delivery rule

Your sample app still does not do anything. Next, you need to make and enable a flag delivery rule in the app.

Make a targeted delivery rule for the "on" variation for the product_sort flag. A targeted delivery lets you gradually release a feature flag to users, but with the flexibility to roll it back if you encounter bugs.

Verify you are in your primary environment since you are using the primary environment SDK key:

verify the environment in which you make the rule — Verify the environment in which you made the rule

Click Add Rule and select Targeted Delivery.
Set the traffic slider to 50%. This delivers the flag to 50% of users who trigger the flag in this environment. You can roll out or roll back the product_sort flag to a percentage of traffic whenever you want.
From the Deliver drop-down, select On.
Click Save.

configure a targeted delivery — Configure a targeted delivery

Toggle the flag to On to enable it for your flag delivery rule:

3. Run your sample app

In Android Studio, start an emulator. Click Run to execute the sample app code you created earlier. Your output appears similar to the following:

Flag on. User number 6998 saw flag variation: on and got products sorted by: popular_first config variable as part of flag rule: targeted_delivery

Flag on. User number 1177 saw flag variation: on and got products sorted by: popular_first config variable as part of flag rule: targeted_delivery

Flag on. User number 9714 saw flag variation: on and got products sorted by: popular_first config variable as part of flag rule: targeted_delivery

Flag on. User number 4140 saw flag variation: on and got products sorted by: popular_first config variable as part of flag rule: targeted_delivery

Flag on. User number 4994 saw flag variation: on and got products sorted by: popular_first config variable as part of flag rule: targeted_delivery

Flag off. User number 8700 saw flag variation: off and got products sorted by: alphabetical config variable as part of flag rule: default-rollout-208-19963693913

Flag off. User number 9912 saw flag variation: off and got products sorted by: alphabetical config variable as part of flag rule: default-rollout-208-19963693913

Flag on. User number 6560 saw flag variation: on and got products sorted by: popular_first config variable as part of flag rule: targeted_delivery

Flag on. User number 9252 saw flag variation: on and got products sorted by: popular_first config variable as part of flag rule: targeted_delivery

Flag on. User number 6582 saw flag variation: on and got products sorted by: popular_first config variable as part of flag rule: targeted_delivery

📘
Note
You will not get exactly 50% of your user traffic in the "on" variation, since you are working with such a small number of visitors. Also, users who get an "off" flag will not make it into the 50% traffic you set, so they fall through to the default "off" rule (default-rollout in the preceding print statements):

4. How it works

So far, you:

Created a flag, flag variable and a flag variation (wrapper for your variables) in the Optimizely app
Implemented a flag in your app with the Decide method

What is going on in your sample app?

How it works: decide to show a user a flag

The Flutter SDK’s Decide method determines whether to show or hide the feature flag for a specific user.

📘
Note
You can reuse this method for different flag rules, for example for delivering more traffic or running an experiment to show different sorting methods to just a portion of users.

After you learn which sorting method works best to increase sales, roll out the product sort flag to all traffic with the method set to the optimum value.

In your sample app:

var user = await optimizelyClient.createUserContext(userId);
// "product_sort" corresponds to the flag key you create in the Optimizely app
var decideResponse = await user!.decide("product_sort");

📘
Note
Optionally include attributes when you create your user (not shown in your sample app), so you can target specific audiences. For example:
var attributes = <String, dynamic>{};
attributes["logged_in"] = true;
var user = await optimizelyClient.createUserContext("user123", attributes);

How it works: configure flag variations

You can dynamically configure a flag variation using flag variables. In your sample app:

// always returns false until you enable a flag rule in the Optimizely app
if (decideResponse.decision!.enabled) {
  // "sort_method" corresponds to variable key you define in Optimizely app
  var sortMethod = decideResponse.decision!.variables["sort_method"] as String;
  print("sort_method: $sortMethod");
}

For your product_sort flag, you can configure variations with different sort_method values, sorting by popular products, relevant products, promoted products and so on. Set different values for the sort method at any time in the Optimizely app.

Part 3: Run an A/B test

This tutorial guided you through a targeted delivery, which is the simplest flag rule. However, you often want to A/B test how users react to feature flag variations before you roll out a feature flag delivery.

The following table shows the difference between flag deliveries and A/B tests:

Targeted delivery rule	A/B test rule
You can roll out your flag to a percentage of your general user base (or to specific audiences) or roll it back if you find bugs.	Experiment by A/B testing a flag before you invest in delivering, so you know what to build. Track how users behave in flag variations, then interpret your experiment results using the Optimizely Stats Engine.

Be sure to A/B test the "on" variation of your product_sort flag!

1. Add event tracking

You need to add a Track Event method to your sample app, so you can mock up user events, then view the metrics.

Delete your old sample code, then paste in the following code, remembering:

Replace your SDK key again
Do not run your app yet. You first need to set up the A/B test in the Optimizely app

import 'dart:math';
import 'package:flutter/material.dart';
import 'package:optimizely_flutter_sdk/optimizely_flutter_sdk.dart';
import 'dart:async';
import 'package:optimizely_flutter_sdk/src/user_context/optimizely_user_context.dart';

// NOTE: You need to change this SDK key to your project's SDK Key
const String sdkKey = "Your_SDK_Key";
const String logTag = "OPTIMIZELY_QUICK_START";

void main() {
  runApp(const MyApp());
  var productSorter = ProductSorter();
  productSorter.initializeQuickStart();
}

class MyApp extends StatefulWidget {
  const MyApp({Key? key}) : super(key: key);

  @override
  State<MyApp> createState() => _MyAppState();
}

class _MyAppState extends State<MyApp> {
  String uiResponse = 'Unknown';

  @override
  void initState() {
    super.initState();
  }

  @override
  Widget build(BuildContext context) {
    return MaterialApp(
      home: Scaffold(
        appBar: AppBar(
          title: const Text('Quick start example app'),
        ),
        body: Center(
          child: Text(uiResponse),
        ),
      ),
    );
  }
}

class ProductSorter {
  String _datafileHost = "https://cdn.optimizely.com";
  String _datafileSuffixAndroid = "/datafiles/%s.json";
  String _datafileSuffixIOS = "/datafiles/%@.json";

  Future<void> initializeQuickStart() async {
    // Setting up custom datafile URL format
    Map<ClientPlatform, DatafileHostOptions> datafileHostOptions = {};

    datafileHostOptions[ClientPlatform.android] =
        DatafileHostOptions(_datafileHost, _datafileSuffixAndroid);

    datafileHostOptions[ClientPlatform.iOS] =
        DatafileHostOptions(_datafileHost, _datafileSuffixIOS);

    // Initializing OptimizelyClient
    var flutterSDK = OptimizelyFlutterSdk(
        sdkKey, datafileHostOptions: datafileHostOptions);
    var response = await flutterSDK.initializeClient();
    if (response.success) {
      flutterSDK.addConfigUpdateNotificationListener((msg) {
        runQuickStart(flutterSDK);
      });
      await runQuickStart(flutterSDK);
    }
  }

  Future<void> runQuickStart(OptimizelyFlutterSdk flutterSDK) async {
    /* --------------------------------
     * to get rapid demo results, generate random users. Each user always sees the same variation unless you reconfigure the flag rule.
     * --------------------------------
     */

    /* --------------------------------
       OPTIONAL: Add a notification listener so you can integrate with third-party analytics platforms
       --------------------------------
    */
    // var notificationId = await flutterSDK.addDecisionNotificationListener((decisionNotification) {
    //   if (decisionNotification.type == "flag") {
    //
    //     var serializedInfo = decisionNotification.decisionInfo.toString();
    //     print("$logTag Feature flag access related information: ${serializedInfo}");
    //     // Send data to analytics provider here
    //   }
    // });


    // simulate 50 users
    var rangeMax = 9999;
    var rangeMin = 1000;
    var range = Random();
    var hasOnFlags = false;

    for (int i = 0; i < 10; i++) {
      var userId = "${range.nextInt(rangeMax - rangeMin) + rangeMin}";
      /* --------------------------------
       Create hardcoded user & bucket user into a flag variation
       --------------------------------
      */
      var user = await flutterSDK.createUserContext(userId);
      // "product_sort" corresponds to a flag key in your Optimizely project
      var decisionResponse = await user!.decide("product_sort");
      var decision = decisionResponse.decision;
      // did decision fail with a critical error?
      if (decision?.variationKey == null) {
        print("\n\n$logTag decision error: ${decisionResponse.reason}");
      }
      // get a dynamic configuration variable
      // "sort_method" corresponds to a variable key in your Optimizely project
      String sortMethod = decision?.variables["sort_method"] as String;

      if (decision!.enabled) {
        // Keep count how many visitors had the flag enabled
        hasOnFlags = true;
      }
      /* --------------------------------
         Mock what the users sees with print statements (in production, use flag variables to implement feature configuration)
         --------------------------------
      */
      // always returns false until you enable a flag rule in your Optimizely project
      var userIdResponse = await user.getUserId();
      print("\n\n$logTag Flag ${(decision.enabled
          ? "on"
          : "off")}. User number ${userIdResponse.userId} saw flag variation: ${decision
          .variationKey} and got products sorted by: ${sortMethod} config variable as part of flag rule: ${decision
          .ruleKey}");
      await mockPurchase(user);
    }
    if (!hasOnFlags) {
      print(
          "\n\n$logTag Flag was off for everyone. Some reasons could include:\n1. Your sample size of visitors was too small. Rerun, or increase the iterations in the FOR loop\n2. By default you have 2 keys for 2 project environments (dev/prod). Verify in Settings>Environments that you used the right key for the environment where your flag is toggled to ON.\nCheck your key at  https://app.optimizely.com/v2/projects/YOUR_PROJECT_ID/settings/implementation");
    } else {

    }
  }

  // mock tracking a user event so you can see some experiment reports
  Future<void> mockPurchase(OptimizelyUserContext user) async {
    print("\n\n$logTag Pretend that user made a purchase? y/n ");
    Random rnd = new Random();
    int yesOrNo = rnd.nextInt(2);
    // Assigning random yes and no
    String answer = yesOrNo == 1? "y" : "n";
    print("\n\n$logTag $answer");
    var userIdResponse = await user.getUserId();
    if (answer == "y") {
      // track a user event you defined in the Optimizely app
      await user.trackEvent("purchase");
      print("\n\n$logTag Optimizely recorded a purchase in experiment results for user ${userIdResponse.userId}");
    } else {
      print("\n\n$logTag Optimizely didn't record a purchase in experiment results  for user ${userIdResponse.userId}");
    }
  }
}

2. Pause other rules in free accounts

If you have a free account, you need to pause the Targeted Delivery you created earlier in this quickstart before you create your A/B test:

Select the specific Flag that contains the Targeted Delivery you created earlier in the quickstart.

Select the flag you created earlier in this quickstart guide

Select the Environment (Production) and the Targeted Delivery you want to pause.
Click Disable Rule in the upper righP corner.

pause the Targeted Delivery — Pause the Targeted Delivery

3. Create the A/B test

To create and launch an experiment in your Optimizely project:

Go to Rules for your flag.
Click Add Rule > A/B Test.

create new A/B test — Create a new A/B test

4. Add an event

In an experiment, you track users' relevant actions to measure how they react to your feature flag variations. You need to define the actions you want to track:

Click in the Metrics field.
Click Create new event.

Enter purchase for the Event Key and click Create Event. (To understand whether the new sorting flag helps customers figure out what to buy, track whether the user makes a purchase after they viewed the products in a new order.)

Leave the defaults (measure Increase in unique conversions).

Click Add Metric.
Leave the default "Off" variation as a control. Select the On variation you configured in a previous step:

📘
Note
The two variations in this example are not a limitation. You can also create A/B tests with multiple variations.

Click Save.

Double check your flag to ensure it is on, so your experiment can run:

5. Run the A/B test

Verify that your emulator is still running. Click Run in Android Studio and answer the command-line prompts. Your output should appear similar to the following:

Flag on. User number 1496 saw flag variation: on and got products sorted by: popular_first config variable as part of flag rule: experiment_1
Pretend that user made a purchase? y/n
n
Optimizely didn't record a purchase in experiment results for user 1496


Flag off. User number 1194 saw flag variation: off and got products sorted by: alphabetical config variable as part of flag rule: experiment_1
Pretend that user made a purchase? y/n
y
Optimizely recorded a purchase in experiment results for user 1194


Flag off. User number 5815 saw flag variation: off and got products sorted by: alphabetical config variable as part of flag rule: experiment_1
Pretend that user made a purchase? y/n
y
Optimizely recorded a purchase in experiment results for user 5815


Flag on. User number 1248 saw flag variation: on and got products sorted by: popular_first config variable as part of flag rule: experiment_1
Pretend that user made a purchase? y/n
y
Optimizely recorded a purchase in experiment results for user 1248


Flag off. User number 9580 saw flag variation: off and got products sorted by: alphabetical config variable as part of flag rule: experiment_1
Pretend that user made a purchase? y/n
n
Optimizely didn't record a purchase in experiment results for user 9580


Done with your mocked A/B test.
Check out your report at  https://app.optimizely.com/v2/projects/19957465438/reports
Be sure to select the environment that corresponds to your SDK key

6. View your A/B test results

Go to the Reports tab to see your experiment results.

Your results should look something like the following:

📘
Note

You might not see the exact user traffic percentages you configured for your flag variations until you have a larger number of users.

You might not see your user traffic immediately. Refresh the browser to refresh traffic.

Your experiment results will not tell you a winning variation until you have a larger number of visitors (on the order of 100,000 or more).

7. How it works

For an A/B test, you need a way to tell Optimizely when users make purchases in your app and map this event in your app code to the specific event you created in Optimizely. The SDK has a method for that! Use the Track Event method and pass in the key for the event you created (purchase). In your sample app:

// Track how users behave when they see a flag variation
// e.g., after your app processed a purchase, let Optimizely know what happened:
user.trackEvent("purchased");

📘
Note
Optionally add tags to your event to enrich it (not shown in your sample app). You can also use reserve tag keys like revenue to track quantitative results.

Event tracking is currently supported only for experiment rules, not delivery rules. Tracking for deliveries will be supported in a future release.

Either way, you should include event tracking when you implement a flag because it can help you integrate with a third-party analytics platform. It also gives you flexibility when you create A/B tests.

Conclusion

Congratulations! You successfully set up and launched your first Optimizely Feature Experimentation experiment. While this example focused on optimizing sales, Optimizely’s experimentation platform can support an open-ended set of experimentation use cases.

See our complete Flutter SDK documentation to learn more ways to optimize your software using experimentation.

Flutter SDK quickstart

Part 1: Create a sample app

1. Access or create your account

2. Get your SDK key

📘
Note

3. Copy the sample code

📘
Note

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Note

Part 2: Run your app

1. Create the feature flag

2. Create the flag delivery rule

3. Run your sample app

📘
Note

4. How it works

How it works: decide to show a user a flag

📘
Note

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Note

How it works: configure flag variations

Part 3: Run an A/B test

1. Add event tracking

2. Pause other rules in free accounts

3. Create the A/B test

4. Add an event

📘
Note

5. Run the A/B test

6. View your A/B test results

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7. How it works

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Conclusion

Part 1: Create a sample app

1. Access or create your account

2. Get your SDK key

📘Note

3. Copy the sample code

📘Note

📘Note

Part 2: Run your app

1. Create the feature flag

2. Create the flag delivery rule

3. Run your sample app

📘Note

4. How it works

How it works: decide to show a user a flag

📘Note

📘Note

How it works: configure flag variations

Part 3: Run an A/B test

1. Add event tracking

2. Pause other rules in free accounts

3. Create the A/B test

4. Add an event

📘Note

5. Run the A/B test

6. View your A/B test results

📘Note

7. How it works

📘Note

Conclusion

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