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Adobe analytics web & app are two separate report suite. As a result they are two separate schema and hence two separate dataset in AEP. Is there a known limitation or official document that says that adobe analytics connector can only connect to one report-suite (so one schema) in the lower sandbox env ?
I've been receiving the error below while activating to a streaming destination. Is there a way to figure out which profiles were excluded from being activated? One idea is to create the same audience as a batch audience and activate to a sftp or S3 bucket. Then identify the profiles that were excluded. Another is to query the profile snapshot to identify profiles that are part of the audience and then query them further for the existence of the required identity attribute.Is there a simpler/faster way or log where AEP would actually show you example profiles whenever it excludes them from being activated to a streaming destination? Wanting to know before I embark on researching via the approaches above.... Error description provided in the 'Dataflow Run details' screen for the destination activation: 'No valid identities were found on the profile. This can indicate that several of the exported profiles are missing an identity attribute that was set as source field in th
In Adobe AEP, Is there any way to find the average global evaluation job times over the last 12 months ?
Hello RTCDP Community users, We’re continually inspired by how you’re using Adobe Real-Time Customer Data Platform to create meaningful impact. Your insights not only showcase what’s possible but they also empower others to make smarter, more confident decisions.We’d truly appreciate it if you could take 10 minutes to share your experience on Gartner Peer Insights. Your feedback plays a key role in shaping Adobe’s position in the Voice of the Customer report and contributes to our eligibility for the Customers’ Choice recognition. Most importantly, your voice helps guide peers in choosing the right solution for their needs.As a thank you for your time, you’ll have the option to receive a $25 gift card when your review is published!Start your review here!Important details to keep in mind:Reviews are anonymous. Only your role, industry, and organization size are displayed.Updated reviews are welcome. If you submitted a review in the past and have new insights to
Hi,is there a way to limit the creation or publish or both at user/role permission level in AEP?i d like to have an approval process for audience creation and publish but i cannot find anything about this in the Permission section
in creating audiences what are the uses cases for choosing compose audience vs segment builder? thanks
hi,while creating an audience (or segment if using the old name) when is it best to an attribute or an event?let s say you want to create an audience based on users having visited the page Product.would you use the attribute page Name or the event page Name?what s the rationale of each selection?
We ran into a faulty schema-design issue that we are trying to resolve in a client's PROD sandbox. We have a profile-enabled experience-event dataset that contains about a year's worth of streaming event-data. This dataset is based on a profile-enabled schema that has 3 identities - ECID and 2 other identities, each mapped to different cross-device ID namespaces. It has been determined that the 2 identities of the schema/dataset were mapped incorrectly to existing 2-cross-device ID namespaces. We are attempting to do the following: 1. Demote the 2 attributes that are currently assigned as identities and turn them into 'regular' attributes. The dataset is the only dataset that is derived from the parent schema. There are no other datasets based on the schema.2. Assign 2 new/different attributes as identities on the schema. These new identities will be using 2 new namespaces - different from what the 2 original identities were using. ECID will remain the same - no changes
Image credits: Adobe Firefly In the last two posts, we explored how to identify prediction opportunities that align with your business goals and discussed the steps to build those predictions using Adobe Real-time CDP Customer AI. Now, let’s dive deeper into the process of translating a prediction goal into a fully functional Customer AI predictions which can be used to build intelligent audiences right away! When working with Adobe Real-time CDP Customer AI, it’s essential to know how to interpret the metrics and results to make strategic decisions. Here's a simple breakdown of key metrics and charts, explained with analogies to make them easier to grasp. 1. Trusting the Prediction Quality Using AUC What is AUC? The AUC, or Area Under the Curve, measures how well your model can distinguish between likely responders (customers who will take action) and non-responders. The closer the AUC score is to 1.0, the better the model is at separatin
We are thrilled to announce applications are now open for 2025-2026 Adobe Experience Platform. Adobe Champions represent an elite group of our most advanced users and brand ambassadors for these fundamental Experience Cloud products. Each year, a cohort of expert practitioners from around the globe submit applications to be selected to participate in the Champion Program. The individuals chosen are provided with opportunities to share their expertise, exchange best practices and learn from fellow product experts, and interact with Adobe product teams and leaders. Program ObjectivesDevelop deep connections with our most knowledgeable customers and partners to be our “voice” within Adobe’s customer communityActivate Champions for feedback, exclusive thought leadership and speaking opportunities, customer references, and to help drive product adoptionDrive customer advocacy and evangelism of Adobe Experience Platform products and the Adobe brand Apply now to become an Adobe
Hello Team,If an event happens in the past but gets sent late, will streaming segmentation still use it, or does it only count for batch or scheduled segment updates?
Hello, I am trying to use the SFTP Destination Connector in RTCDP and running into an authentication error. The destination is SFMC and I have created a SSH key and added it to my FTP account in SFMC following the documentation listed below. Ive also followed the Adobe documentation on troubleshooting such errors but I am still getting an authentication error when trying to connect to the destination. Any tips on how to resolve this would be greatly appreciated!
Server-side tag management offers several advantages over traditional client-side tag management, particularly in terms of performance, security, and data accuracy. Adobe event forwarding allows you to send collected event data from Adobe Experience Platform Edge Network to non-Adobe destinations for server-side processing, it is a powerful way to streamline data collection and distribution while improving website performance and data governance. Here are the key points about Adobe event forwarding: Purpose: It allows you to send data to third-party, non-Adobe vendors directly from Adobe's Edge Network instead of from the client-side browser (in some cases in addition to client side data sent). Benefits: Improved Website Performance: Server-side tag management reduces the load on the client’s browser by handling tag execution on the server. This leads to faster page load times and a better user experience, as fewer scripts need to be executed on the client side. Enhanced Data Secur
Description:Introduce a Destination Activation Replay feature that tracks failed or missed activation (e.g., due to API downtime, schema mismatch, rate limits) and allows for automatic or manual reprocessing once the destination becomes healthy again - ensuring no critical activation is permanently lost. Why is this feature important?Ensures activation reliability - campaigns or journeys shouldn't silently miss users due to transient destination errors.Helps marketers and engineers troubleshoot and recover from downstream failures without rebuilding segments or pipelines.Supports auditability and compliance, with logs showing which profiles were successfully activated, which failed, and which are pending retry.Prevents data loss during outages, especially when targeting time-sensitive audiences like flash sales or churn interventions.Current Behavior:If a destination (e.g., Facebook, Google Ads, webhook, custom API) fails during profile export, the activation fails silently or log
Description:Introduce a Source Health Dashboard that monitors the status, freshness, volume, and latency of incoming data sources (batch and streaming) in real time. Add alerting features for drops in ingestion, data schema mismatches, or unusual data volume patterns. Why is this feature important?Ensures data quality and trust across the platform by surfacing real-time issues with source integrations.Reduces diagnostic time for ingestion failures that silently impact audience building or segmentation.Proactively alerts technical and marketing teams to source failures, stale data, or delays, preventing downstream impacts on campaigns and decisioning.Supports data governance and operational excellence in data-driven organizations. Current Behavior:Source connection status (e.g., for streaming or scheduled batch uploads) is not actively monitored in a centralized dashboard.Failures may go unnoticed until audience segments look wrong or campaigns underperform.There is no built-i
Description:Introduce a real-time audience fatigue scoring mechanism that tracks user responsiveness (or lack thereof) across channels (email, push, ads, etc.) and automatically adjusts frequency caps or suppresses the user from further campaigns until engagement improves. Why is this feature important?Prevents over-messaging and burnout, which leads to unsubscribes, opt-outs, and negative brand perception.Allows more intelligent campaign pacing - showing restraint can often improve long-term engagement.Reduces manual guesswork around send frequency by making decisions based on real-time engagement signals (opens, clicks, site visits, etc.).Optimizes deliverability and compliance, especially in regulated regions with communication limits.Current Behavior:Frequency capping is usually static and channel-specific (e.g., max 3 emails/week).No native cross-channel fatigue detection or unified scoring that evaluates all touchpoints.CDP does not dynamically adjust campaign eligibility ba
Description:Introduce a predictive LTV (Lifetime Value) model natively inside Real-Time CDP that scores customers dynamically based on their engagement, transactions, browsing behavior, and other attributes - allowing marketers to automatically prioritize higher-value users for premium campaigns, offers, and loyalty experiences.Why is this feature important?Maximizes ROI by investing marketing resources in users who are likely to bring more revenue over time.Enables smarter segmentation beyond simple past-purchase or recency-frequency models.Enhances personalization by aligning offer types, discount levels, and campaign intensity based on user potential value.Improves strategic planning by giving marketing, sales, and service teams a predictive view of customer quality, not just quantity.Current Behavior:Marketers manually segment users based on historical transactions like total purchase value or number of orders.No predictive scoring available natively in Real-Time CDP; advanced LTV
Description:Enable dynamic suppression of users from active marketing campaigns in real time based on recent negative experiences - such as failed transactions, customer complaints, or product returns - using Adobe Real-Time CDP signals and event-based triggers.Suppressed users can be re-evaluated for reactivation once an issue is resolved. Why is this feature important?Prevents wasting marketing budget by sending promotions to frustrated customers who are temporarily disengaged.Improves brand perception by respecting user sentiment and avoiding tone-deaf marketing outreach during sensitive moments.Reduces churn by showing customers you are listening and responding appropriately to their issues.Current Behavior:Audience suppression typically relies on static exclusion lists updated periodically (daily or weekly).No native real-time suppression based on live customer service data, failed transactions, or dissatisfaction signals.There’s no automated mechanism in Real-Time CDP to tem
Description:Introduce a feature in Adobe Real-Time CDP that utilizes machine learning to predict customer churn based on real-time behavioral and transactional data. The system would allow marketers to define churn-risk thresholds and automatically activate personalized retention journeys (e.g., email offers, push notifications, or loyalty incentives). It would also maintain a version history of churn prediction models for transparency, comparison, and improvement over time. Why is this feature important?Increases ROI of marketing campaigns through targeted retention efforts.Enables real-time action, which is crucial for saving at-risk customers.Provides transparency and iterative improvement through model versioning.Supports personalization at scale with minimal manual effort.Reduces revenue loss by proactively identifying customers likely to churn. Current Behavior:Adobe Real-Time CDP allows segmentation and audience activation, but lacks built-in churn prediction and autom
I'm working with streaming data sources and wanted to check if there are any known limitations or delays when it comes to processing or qualifying data in real time. Specifically, I’m curious about:Any known lags or edge cases where real-time processing might not behave as expectedBest practices to minimize delays or troubleshoot issuesWould love to hear from others who’ve worked with streaming data in RTCDP. Thanks in advance for your help!
Hi Team, in ABC named schema, i have fieldgroup 123 and identity PQRI have already moved fieldgroup to preprod environment and identity is already created in PreprodI have created package for this schema where fieldgroup and identity is already present. Concern is for identity when i try to import package in preprod environment and click on modules that either needs to be created or existing can be use. I am able to use for fieldgroup but i am not able to see identity which is present in preprod and because of which i am not able to select. i know other way is to create each field in stage but do we have any option where i can see identity and select as ues Existing? Any help would be appreciated?
Description:Introduce the ability for multiple users to collaboratively build and refine audience definitions in Adobe Real-Time CDP with support for version history, change tracking, and inline comments.This feature would help cross-functional teams (marketers, analysts, data scientists) work together more efficiently while ensuring traceability and reducing errors in audience logic. Why is this feature important to you:Audience building often involves multiple team members, and right now, it’s hard to track who made what changes or why.Sometimes, edits overwrite each other or lead to confusion without proper documentation or context. How would you like the feature to work:Each saved audience should include a version history, showing what was changed, when, and by whom.Users should be able to leave inline comments on specific filters or conditions (like commenting in Google Docs).Rollback functionality should allow users to restore a previous version if needed.Notifications
Dear Community, I am a RTCDP and AJO user who is trying to create a computed attribute that counts the amount of emails a user has opened in the previous month. I am struggling to create it and I am writing to see whether anybody can help me solving the issue. The purpose is to a have this field at profile level, even knowing that we can count the amount of emails opened when creating audiences. How was it created?It was created by applying the following settings: -select interactionType event -equals "Message opened"-Count-1 Month-Fast refresh is checked The definition looks like this: It generates the following expression:xEvent[_experience.customerJourneyManagement.messageInteraction.interactionType in ["open"]].count() After creating it, I noticed the info "Summary data is not available for this field due to lack of clustered values" in the InteractionType field. Is this somehow related to the Summaries job? I admit I didn't understand it. &n
Description - It would be nice to have at profile-level the amount of emails each profile have received and opened in the last 30 days.Why is this feature important to you - It would be possible to address journeys based on communication-engagement withouth having to do it at audience-level. How would you like the feature to work - a computted attribute that returns the count of emails a profile have received/ opened in the last 30 days, something link:xEvent[_experience.customerJourneyManagement.messageInteraction.interactionType in ["open"]].count() Current Behaviour - Computed Attributes currently do not support System generated datasets
Adobe Real-Time Customer Data Platform (RTCDP) is a powerful tool for marketers and data analysts alike. By enabling businesses to unify customer data from various sources and deliver personalized experiences in real-time, it has become an essential part of the modern marketing stack. However, to fully harness its potential, it’s important to follow best practices that ensure effective and efficient use of the platform. Below are some key strategies to get the most out of Adobe RT-CDP. 1. Establish Clear Objectives and KPIs Before diving into the technical aspects of Adobe RTCDP, it’s crucial to define what you want to achieve. Whether your goal is to improve customer retention, increase cross-sell opportunities, or enhance customer engagement, having clear objectives will guide your use of the platform. Additionally, establish Key Performance Indicators (KPIs) that align with these objectives. These metrics will help you measure the success of your efforts and make data-driven
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