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Execute A/B tests with feature flags

Summary of steps#

  1. Enable On-Device Decisioning for your organization
  2. Create an A/B activity
  3. Define your A and B
  4. Add an audience
  5. Set traffic allocation
  6. Set traffic distribution to variations
  7. Set up reporting
  8. Add metrics for tracking KPIs
  9. Implement code to execute A/B tests with feature flags
  10. Activate your A/B test with feature flags

NOTE: Suppose you want to determine whether your fall-themed redesign of your homepage would be received well by your users. You decide to test it by running an A/B experiment in Adobe Target. You also want to make sure the experiment is delivered with great performance so that a negative or slow user experience does not skew the results.

Enable On-Device Decisioning for your organization#

Enabling on-device decisioning ensures an A/B activity is executed at near-zero latency. To enable this feature, navigate to Administration > Implementation > Account details in Adobe Target, and enable the On-Device Decisioning toggle.

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NOTE: You must have the Admin or Approver user role to enable or disable the On-Device Decisioning toggle.

After enabling the On-Device Decisioning toggle, Adobe Target begins generating rule artifacts for your client.

Create an A/B activity#

In Adobe Target, navigate to the Activities page, then select Create Activity > A/B test.

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In the Create A/B Test Activity modal, leave the default Web option selected (1), select Form as your experience composer (2), select Default Workspace with No Property Restrictions (3), and click Next (4).

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Define your A and B#

  1. In the Experiences step of activity creation, provide a name for your activity (1) and add a second experience, Experience B, by clicking the Add Experience (2) button. Enter the name of the location (3) within your application where you want to execute your A/B test. In the example shown below, homepage is the location defined for Experience A. (It is also the location defined for Experience B.)

    Experience A defines the control, which is the current homepage design.

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    Experience B defines the challenger, which will represent a redesigned homepage. Click to change default content (1).

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  2. In Experience B, click to change the content from Default Content to the redesigned content by selecting Create JSON Offer as shown below (1).

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  3. Define the JSON with attributes that will be utilized as flags to enable your business logic to render the newly redesigned homepage, rather than the current homepage in production.

NOTE: When Adobe Target buckets a user to see Experience B (the redesigned homepage), the JSON with the attributes defined in the example will be returned. In your code, you will need to check the attribute values to decide whether to execute the business logic to render the redesigned homepage. You get to define the names, values, and number of attributes in this JSON response.

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Add an audience#

Suppose you want to first test the redesign on your loyal customers, whom you can identify based on whether or not they are logged in.

  1. In the Targeting step, click to replace the All Visitors audience, as shown.

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  2. In the Create Audience modal, define a custom rule where logged-in = true. This defines the group of users who are logged in. Use this audience in your activity.

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Set traffic allocation#

Define the percentage of your logged-in users against which you want to test your new homepage redesign. In other words, to what percentage of your users do you want to roll out this test? In this example, to deploy this test to all logged-in users, keep the traffic allocation at 100%.

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Set traffic distribution to variations#

Define the percentage of your logged-in users that will see the current design of the homepage or the completely new redesign. In this example, keep the traffic distribution as a 50/50 split between Experiences A and B.

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Set up reporting#

In the Goals & Settings step, choose Adobe Target as the Reporting Source to view activity results in the Adobe Target UI, or choose Adobe Analytics to view them in the Adobe Analytics UI.

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Add metrics for tracking KPIs#

Choose a Goal Metric to measure the A/B test. In this example, a successful conversion is based on whether the user reaches the bottom of the page, indicating engagement. Therefore, Conversion is determined based on whether the user viewed the location named bottom-of-the-page.

Implement code to execute A/B tests with feature flags into your application#


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1const TargetClient = require("@adobe/target-nodejs-sdk");
2const options = {
3 client: "testClient",
4 organizationId: "ABCDEF012345677890ABCDEF0@AdobeOrg",
5 decisioningMethod: "on-device",
6 events: {
7 clientReady: targetClientReady
8 }
10const targetClient = TargetClient.create(options);
12function targetClientReady() {
13 return targetClient.getAttributes(["homepage"]).then(function(attributes) {
14 const flag = attributes.getValue("homepage", "feature-flag");
15 // ...
16 });


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1import com.adobe.target.edge.client.ClientConfig;
2import com.adobe.target.edge.client.TargetClient;
3import com.adobe.target.delivery.v1.model.ChannelType;
4import com.adobe.target.delivery.v1.model.Context;
5import com.adobe.target.delivery.v1.model.ExecuteRequest;
6import com.adobe.target.delivery.v1.model.MboxRequest;
7import com.adobe.target.edge.client.entities.TargetDeliveryRequest;
8import com.adobe.target.edge.client.model.TargetDeliveryResponse;
10ClientConfig config = ClientConfig.builder()
11 .client("testClient")
12 .organizationId("ABCDEF012345677890ABCDEF0@AdobeOrg")
13 .build();
14TargetClient targetClient = TargetClient.create(config);
15MboxRequest mbox = new MboxRequest().name("homepage").index(0);
16TargetDeliveryRequest request = TargetDeliveryRequest.builder()
17 .context(new Context().channel(ChannelType.WEB))
18 .execute(new ExecuteRequest().mboxes(Arrays.asList(mbox)))
19 .build();
20Attributes attributes = targetClient.getAttributes(request, "homepage");
21String flag = attributes.getString("homepage", "feature-flag");

Activate your A/B test with feature flag#

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