Adobe Target

We would like to thank the 550 customers who registered for this event.The objective of this webinar was to provide a "sneak preview" and a look under the hood to discover what our engineering and product team are working on.Watch the recording of our May 12 webinar here:  Agenda:Major UI releases: Insights Home Page, Allowlist URLs, Flicker Manager, CDN Experimentation SDK Sum up of main Roadmap Features Experimentation Accelerator 🎉 Big Announcement: Adobe Target MCP server is generally available! Adobe is officially connecting your Adobe Target environment directly to your favorite AI assistants. More information here  Slides are attached to this post and can be downloaded as a PDF attachment 👇For customers who want to share their feedback, you are welcome to submit the following MCP Form multiple times as new ideas or feedback come up. Thank you for helping us shape the future of Target.The Q&A file for this event is coming soon.CC: ​​​​​​@VittoriaZocco for visibility 

Hi,I’ve missed the last 2 Adobe Target Engineering Webinar’s (#4 and #5). Were these recorded and if so would it be possible to share the links please? 

Hi all, I have created two activities with two different location names for the android app. the activity with the location name bottom-sheet-mbox-fragement is delivering as expected, but the activity with the location name target-global-mbox is not delivering. has anyone faced this scenario before?

Can Auto-Target and Auto Personalisation’s machine-learning use audiences created in the Target Audience Library directly?The documentation (What Data is Collected to Build Machine-Learning Algorithms? | Adobe Target) specifically references audiences created in Experience Cloud (with examples of Adobe Analytics and Adobe Audience Manager), as well as audiences created in Platform CDP, but it is not clear whether audiences created in Target’s audience library are used by the machine-learning.For context: We have a single mbox parameter which contains a comma delimited string of identifiers which relate to audiences defined in an external platform. We create audiences in the Target Audience Library to split out each separate audience and make it usable. The string itself will be relatively useless to the ML models. Ideally the audiences we already create in the Target UI will be available.Thanks!

With Claude or Cursor, is anyone using any MCPs that are helping either with code, workflow or analytics within work being done in Adobe Target?

Hi, I am looking to see if there is a way to get notifications to a webhook when Activities are created/updated in Target? 

We are looking for some help as we currently blocked in our tracking implementation of this Adobe target server side implementation. We can successfully retrieve a4tpayload/tnta from the backend and sending in the first analytics call through global page rules, but it never appears on the first Analytics b/ss call also nothing appears in the Analytics report either

I'm struggling to find an efficient way to debug Recommendations. With at.js, I used mboxTrace, which provided a very clear "Recs Box" showing exactly which criteria were used, which entities were returned, and why certain items were excluded.Now that I'm using Web SDK and the AEP Debugger, I find the debugging process much more difficult. I can see the network calls, but I miss that high-level summary of the Recommendations logic.What I've tried: Using the AEP Debugger Extension to look at Edge Traces. Digging through the interact response payloads in the Network tab. My Questions: Is there a way to get a visual "Recs box" similar to the old mboxTrace functionality in at.js? In the AEP Debugger, where exactly should I look to see the Criteria details and Exclusion reasons for a specific Recommendations activity? Are there any third-party tools or specific "Edge Trace" configurations that make the JSON output more readable for Recs-heavy implementations? How do you effectively

When using the Target Admin API, I’m creating new JSON offers. My requests are returning a ‘201 Created’ response, but when looking at the Target UI, I’m not seeing the offers in the default workspace. I can confirm that the API has access to the correct workspaces, and response shows the offer created in workspace: default. The response also shows an OfferId that looks accurate.Additionally, some time has passed (>60 minutes), and no offer has appeared yet. Should the Offers be accessible from the Target UI after creation with the API?

I’m seeing a mismatch between the public Adobe Target Admin API for AB activities and the Adobe Target UI.The issue is that additional metric configuration shown in Goals & Settings is not fully available in the public REST activity model.Observed behaviorFor additional metrics in the UI, Adobe Target stores extra per-metric state such as:whether the metric is `conversion`, `engagement`, or `revenue` for conversion metrics, the selected action such as: `Viewed a page` Viewed an mbox` `Clicked on Mbox` In the browser editor model, this appears as a separate structure like:"successCriteria": [  { "metricLocalId": 32767, "successCriteria": "conversion" },  { "metricLocalId": 1100, "successCriteria": "engagement" },  { "metricLocalId": 1027, "successCriteria": "conversion" }]But the public REST API does not expose this field:GET /{tenant}/target/activities/ab/{id}and also rejects it on update:{  "errorCode": "InvalidProperty.Json",  "message": "Invalid Json. Unrecognized property nam

I am implementing Adobe Target Recommendations via AEP Web SDK and Launch. While the network calls appear to be firing correctly with the necessary entity attributes, the Target Recommendations Catalog has not updated with these product details, even after waiting 24+ hours.Implementation:I am using a "Send Event" action within a Launch rule. Because my data layer is fully populated later in the page load, I have mapped the entity attributes to the "Web Webpagedetails Page Views" event type.Current Rule Configuration (See attached images): Extension: Adobe Experience Platform Web SDK Action Type: Send Event XDM: %XDM Payload: All Page Views% Data: %adobe-target-parameters [xdm]% (This is where my __adobe.target entity data is mapped). The Payload:In the browser network tab (interact call), the payload looks correct: events[0].data.__adobe.target.entity.id is present. entity.name, entity.value, and entity.pageUrl are all populating with the expected strings/numbers.   The Sequ

Hi Community,we are currently experiencing an issue when introducing new Adobe Target locations, while the existing setup is mainly based on the Global Mbox.At the moment, activities configured on the Global Mbox are correctly evaluated and returned in the response. However, when we attempt to create and use a new dedicated location for more targeted personalization, the Web SDK response consistently returns the following error:"errors": [{"type": "ODE-0001-404","detail": "The Decisioning Package was not found."}]On the AEP / Web SDK side, we are following the official documentation available here:https://experienceleague.adobe.com/en/docs/platform-learn/implement-web-sdk/applications-setup/setup-targetbut the error still persists.From the Adobe Launch side, there is a rule that sends a sendEvent call on page load once the required data is available in the data layer.In this call:personalization parameters derived from the data layer are passed to Target, a decisionScope is set with th

If an AB activity is running on Page X, then help me understand how a visit is counted in A4T for below scenario?User comes to Page X and leaves. This user comes back again in a new visit but doesn’t visit Page X (where activity is running) - Will this new visit be included in my AB activity? NOTE: We only do Visits level reporting in A4T for AB tests.

The activity was created with Adobe Analytics as the reporting source, but it is not present in Analytics Workspace.  

I’d like to use attribute weighting in an item-based criterion in a way that makes sense to me but apparently didn’t occur to Adobe devs. The current setup has a weighting % slider, then you choose the attribute, then an operator, then you must enter a static value, so this is really just a leaky filter.What I want I want from your AI is this:Look at the attributes of the current item Look at which attribute(s) I’ve selected to weight Then look at the catalog items that also have this/these attribute(s) Recommend items with rank based first on similarity in these attribute values Ideally, you could also apply an operator here to tailor matching vs. anti-matching, e.g., highly recommend items that are more or less different in these attribute values

In our SPA, we observed a specific behavior of Target activities: Even with renderDecisioning=false, some activities continued to trigger. The activities are present but not rendered. Since this is a SPA and there is no page refresh, in the subsequent Rule Page View we could not find the activities with the key expected by Target. Important: before user login, there were no Rule Page Views. Activities were therefore only processed after login, and everything worked correctly in that phase. Implemented SolutionTo properly handle the SPA flow without page refresh, the following was implemented: In the Rule Page View, after login, a custom code was added to handle view changes:   function onViewChange() {   var viewName = window.location.pathname || 'viewNamePage';   if (viewName.startsWith('/')) {     viewName = viewName.substring(1);   }   alloy("sendEvent", {     renderDecisions: true,     xdm: {       eventType: "view",       web: {         webPageDetails: {           name: view

Hello - Has anyone else had a similar experience that when you made the transition to the MobileSDK your post_tnt_action field in your data feed no longer was populating?  Looking for any type of troubleshooting ideas -- checkboxes that we might be missing, a step that is often overlooked, something new that needs to be setup, etc.  Thanks!

Hi, Can we use the Geo Audience for the Adobe Target usecases for the Apps or it only limited to the website?

i need to create a profile script to identify the last visited bike pdp by a visitor in real time and using that create an audience accordingly for each bike models mutually exclusive

I have a list of 3,784 users that I want to target with specific data. To achieve this, I created segments in Adobe Analytics, where I defined the condition as User ID equals any of x, y, z, using approximately 500 user IDs per segment. These segments are visible in Adobe Target via A4T, and I have used them to create an experience. However, I am unable to see the experience being delivered to the intended audience. Could you help identify what might be causing this issue?

I’m looking to enable the AI capabilities in Adobe Target. If you’ve already done this, I’d be interested in learning which use cases you tried.

I am trying to implement Experience Targeting using Adobe Target.Requirement:If a user visits a specific page (for example: /services-assessment-workshop), then when the same user later lands on the homepage, I want to display a different CTA button with a different URL redirection.Example scenario: User visits:https://example.com/services-assessment-workshop Later the same user visits the homepage On the homepage I want to: Replace the default CTA Show a different CTA Redirect the CTA to another URL Questions: What is the best way to implement this in Adobe Target? Should this be implemented using Experience Targeting (XT) or Profile Scripts? Is it possible to use previous page URL / user behavior as the targeting condition? Would this require storing the visited page in a profile attribute or cookie? Any guidance or recommended approach would be helpful.Thanks!

I recently created a Recommendation activity, but the products are not appearing on the website. The activity qualifies, but the recommendation slot is not rendering any products.Has anyone else faced a similar issue while setting up recommendation activities?Also, are there any specific troubleshooting steps to identify why the recommendations are not showing? For example, checks related to criteria, entity attributes, mbox calls, catalog ingestion, or delivery calls.