Getting Started with Target SDKs

Last update: Mon Jul 17 2023 00:00:00 GMT+0000 (Coordinated Universal Time)

Topics:
APIs/SDKs

CREATED FOR:

Developer

In order to get up and running, we encourage you to create your first on-device decisioning feature flag activity in the language of your choice:

Node.js
Java
.NET
Python

Summary of steps

Enable on-device decisioning for your organization
Install the SDK
Initialize the SDK
Set up the feature flags in an Adobe Target A/B Test activity
Implement and render the feature in your application
Implement tracking for events in your application
Activate your A/B Test activity

1. Enable on-device decisioning for your organization

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

alt image

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.

2. Install the SDK

For Node.js, Java, and Python, run the following command in your project directory in the terminal. For .NET, add it as a dependency by installing from NuGet.

Node.js (NPM)

npm i @adobe/target-nodejs-sdk -P

Java (Maven)

<dependency>
   <groupId>com.adobe.target</groupId>
   <artifactId>java-sdk</artifactId>
   <version>2.0</version>
</dependency>

.NET (Bash)

dotnet add package Adobe.Target.Client

Python (pip)

pip install target-python-sdk

3. Initialize the SDK

The rule artifact is downloaded during the SDK initialization step. You can customize the initialization step to determine how the artifact is downloaded and used.

Node.js

const TargetClient = require("@adobe/target-nodejs-sdk");

const CONFIG = {
   client: "<your target client code>",
   organizationId: "your EC org id",
   decisioningMethod: "on-device",
   events: {
      clientReady: targetClientReady
      }
};

const tClient = TargetClient.create(CONFIG);

function targetClientReady() {
   //Adobe Target SDK has now downloaded the JSON artifact locally, which contains the activity details.
   //We will see how to use the artifact here very soon.
}

Java (Maven)

ClientConfig config = ClientConfig.builder()
   .client("testClient")
   .organizationId("ABCDEF012345677890ABCDEF0@AdobeOrg")
   .build();
TargetClient targetClient = TargetClient.create(config);

.NET (C#)

var targetClientConfig = new TargetClientConfig.Builder("testClient", "ABCDEF012345677890ABCDEF0@AdobeOrg")
   .Build();
this.targetClient.Initialize(targetClientConfig);

Python

from target_python_sdk import TargetClient

def target_client_ready():
   # Adobe Target SDK has now downloaded the JSON artifact locally, which contains the activity details.
   # We will see how to use the artifact here very soon.

CONFIG = {
   "client": "<your target client code>",
   "organization_id": "your EC org id",
   "decisioning_method": "on-device",
   "events": {
      "client_ready": target_client_ready
   }
}

target_client = TargetClient.create(CONFIG)

4. Set up the feature flags in an Adobe Target A/B Test activity

In Target, navigate to the Activities page, then select Create Activity > A/B test.
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), then click Next (4).
In the Experiences step of activity creation, provide a name for your activity (1) and add a second experience, Experience B, by clicking Add Experience (2). Enter the location name of your choice (3). For example, ondevice-featureflag or homepage-addtocart-featureflag are location names indicating the destinations for feature flag testing. In the example shown below, ondevice-featureflag is the location defined for Experience B. Optionally, you may add Audience Refinements (4) to restrict qualification to the activity.
In the CONTENT section on the same page, select Create JSON Offer in the drop-down (1) as shown.
In the JSON Data text box that appears, type your feature flag variables for each experience (1), using a valid JSON object (2).

Enter the feature flag variables for Experience A.

(Sample JSON for Experience A, above)
{ "enabled" : true, "flag" : "expA" }
Enter the feature flag variables for Experience B.

(Sample JSON for Experience B, above)
{ "enabled" : true, "flag" : "expB" }
Click Next (1) to advance to the Targeting step of activity creation.
In the Targeting step example shown below, Audience Targeting (2) remains on the default set of All Visitors, for simplicity. This means the activity is untargeted. However, note Adobe recommends you always target your audiences for production activities. Click Next (3) to advance to the Goals & Settings step of activity creation.
In the Goals & Settings step, set Reporting Source to Adobe Target (1). Define the Goal Metric as Conversion, specifying the details based on your site’s conversion metrics (2). Click Save & Close (3) to save the activity.

5. Implement and render the feature in your application

After setting up the feature flag variables in Target, modify your application code to use them. For example, after getting the feature flag in the application, you can use it to enable features and render the experience for which the visitor qualified.

Node.js

//... Code removed for brevity

let featureFlags = {};

function targetClientReady() {
   tClient.getAttributes(["ondevice-featureflag"]).then(function(response) {
      const featureFlags = response.asObject("ondevice-featureflag");
      if(featureFlags.enabled && featureFlags.flag !== "expA") { //Assuming "expA" is control
         console.log("Render alternate experience" + featureFlags.flag);
      }
      else {
         console.log("Render default experience");
      }
   });
}

Java (Maven)

MboxRequest mbox = new MboxRequest().name("ondevice-featureflag").index(0);
TargetDeliveryRequest request = TargetDeliveryRequest.builder()
   .context(new Context().channel(ChannelType.WEB))
   .execute(new ExecuteRequest().mboxes(Arrays.asList(mbox)))
   .build();
Attributes attributes = targetClient.getAttributes(request, "ondevice-featureflag");
String flag = attributes.getString("ondevice-featureflag", "flag");

.NET (C#)

var mbox = new MboxRequest(index: 0, name: "ondevice-featureflag");
var deliveryRequest = new TargetDeliveryRequest.Builder()
   .SetContext(new Context(ChannelType.Web))
   .SetExecute(new ExecuteRequest(mboxes: new List<MboxRequest> { mbox }))
   .Build();
var attributes = targetClient.GetAttributes(request, "ondevice-featureflag");
var flag = attributes.GetString("ondevice-featureflag", "flag");

Python

# ... Code removed for brevity

feature_flags = {}

def target_client_ready():
   attribute_provider = target_client.get_attributes(["ondevice-featureflag"])
   feature_flags = attribute_provider.as_object(mbox_name="ondevice-featureflag")
   if feature_flags.get("enabled") and feature_flags.get("flag") != "expA": # Assuming "expA" is control
      print("Render alternate experience {}".format(feature_flags.get("flag")))
   else:
      print("Render default experience")

6. Implement additional tracking for events in your application

Optionally, you can send additional events for tracking conversions using the sendNotification() function.

Node.js

//... Code removed for brevity

//When a conversion happens
TargetClient.sendNotifications({
   targetCookie,
   "request" : {
      "notifications" : [
      {
         type: "display",
         timestamp : Date.now(),
         id: "conversion",
         mbox : {
            name : "orderConfirm"
         },
         order : {
            id: "BR9389",
            total : 98.93,
            purchasedProductIds : ["J9393", "3DJJ3"]
         }
      }
      ]
   }
})

Java (Maven)

Notification notification = new Notification();
notification.setId("conversion");
notification.setImpressionId(UUID.randomUUID().toString());
notification.setType(MetricType.DISPLAY);
notification.setTimestamp(System.currentTimeMillis());
Order order = new Order("BR9389");
order.total(98.93);
order.purchasedProductIds(["J9393", "3DJJ3"]);
notification.setOrder(order);

TargetDeliveryRequest notificationRequest =
   TargetDeliveryRequest.builder()
      .context(new Context().channel(ChannelType.WEB))
      .notifications(Collections.singletonList(notification))
      .build();

NotificationDeliveryService notificationDeliveryService = new NotificationDeliveryService();
notificationDeliveryService.sendNotification(notificationRequest);

.NET (C#)

var order = new Order
{
   Id = "BR9389",
   Total = 98.93M,
   PurchasedProductIds = new List<string> { "J9393", "3DJJ3" },
};

var notification = new Notification
{
   Id = "conversion",
   ImpressionId = Guid.NewGuid().ToString(),
   Type = MetricType.Display,
   Timestamp = DateTimeOffset.UtcNow.ToUnixTimeMilliseconds(),
   Order = order,
};

var notificationRequest = new TargetDeliveryRequest.Builder()
   .SetContext(new Context(ChannelType.Web))
   .SetNotifications(new List<Notification> {notification})
   .Build();

targetClient.SendNotifications(notificationRequest);

Python

# ... Code removed for brevity

# When a conversion happens
notification_mbox = NotificationMbox(name="orderConfirm")
order = Order(id="BR9389, total=98.93, purchased_product_ids=["J9393", "3DJJ3"])
notification = Notification(
   id="conversion",
   type=MetricType.DISPLAY,
   timestamp=1621530726000,  # Epoch time in milliseconds
   mbox=notification_mbox,
   order=order
)
notification_request = DeliveryRequest(notifications=[notification])


target_client.send_notifications({
   "target_cookie": target_cookie,
   "request" : notification_request
})

7. Activate your A/B Test activity

Click Activate (1) to activate your A/B Test activity.

NOTE
You must have the Approver or Publisher user role to perform this step.

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