Adobe Analytics

For a travel ticket booking site, we collect various data points throughout the user journey, including product type, category, customer details (non-PII), and other details at each step (product view, add to cart, details filled, checkout) before a purchase is made. I am considering three different setups for configuring these rules. Could you help me understand the differences and recommend the ideal setup? Can we also use props to make the tracking better for any scenario?Thank you 

Adobe Analytics workspace question SKU can be part of any shopping cart events (prodView, OpenCart, cartView, CheckOut etc)How do we create a segment for customer having SKU=ABC as part of prodView in their latest event for that SKU ? Here are the sample example of customer events sorted in time ascending order:Customer 1Time1: SKU=ABC, ProdViewTime2:SKU=ABC, OpenCartTime3:SKU=XYZ, ProdViewTime4:SKU=DEF, ProdViewTime5:SKU=DEF, OpenCartTime6:SKU=ABC, ProdViewTime7:SKU=PQR, ProdViewTime8:SKU=PQR, cartViewTime9:SKU=PQR, CheckOut Customer 2Time1: SKU=ABC, ProdViewTime2:SKU=ABC, OpenCartTime3:SKU=XYZ, ProdViewTime4:SKU=DEF, ProdViewTime5:SKU=DEF, OpenCartTime6:SKU=ABC, ProdViewTime7:SKU=ABC, OpenCartTime8:SKU=XYZ, ProdViewTime9:SKU=PQR, cartViewTime10:SKU=PQR, CheckOut In the Above example, customer 1 should qualify as the latest status for SKU=ABS is prodView on time6.However customer 2 would dis-qualify as the lates status for SKU=ABC is OpenCart on time7.

As you can see in the screenshot below, I have the various values for a selected marketing attribute matching the criteria of starts with "emhvasmtouch3." However, when I create a visit segment for that same criteria, it doesn't include all of the activity. Note that "emhvasmtouch320250806" returns 10 fewer visits and is missing a $49 order. Is there a way to adjust my segment to ensure it matches what the basic filtered view would show?  

We are beyond excited to celebrate a true legend in the Adobe Analytics community -  @mandygeorge, who has been named the inaugural inductee into the Adobe Analytics Rockstar Hall of Fame!  Mandy’s journey with Adobe Analytics has been nothing short of remarkable - from Rockstar attendee to Rockstar on stage, and now, a Rockstar Hall of Fame honoree. Mandy exemplifies what it means to not only master Adobe Analytics, but to share that mastery in innovative, inspiring, and deeply useful ways for the entire community. Learn more about the award here: Adobe Analytics Rockstar Hall of Fame   What Is the Adobe Analytics Rockstar Hall of Fame? Launched as an extension of the Adobe Analytics Rockstar program, the Rockstar Hall of Fame recognizes the best of the best individuals who’ve made an enduring impact on the Adobe Analytics ecosystem through years of creativity, contribution, and community leadership. While Rockstar sessions highlight the year’s top tips, the R

Hi Team,Has anyone implemented KPIs such as "Invalid Visit Rate", "Conversion Rate without Bots", and "Conversion Rate with Bots" in Adobe Analytics dashboards?Additionally, I’m looking to generate a report that answers:"How much bad bot traffic is attacking our site?"I've attached a sample dashboard for reference to provide more context. Any guidance, best practices, or examples would be greatly appreciated.Looking forward to your quick responses!Thanks in advance,Madhusudan Sura |+91-9423067216

Introduction When it comes to integrating your existing Adobe Analytics Classifications to Customer Journey Analytics (CJA), you have two options to consider. The first option is to use the Adobe Analytics Classifications Data source connection to automate the migration of your classifications to CJA. By utilizing the source connector, you can connect your existing classifications from Adobe Analytics and import them automatically into Adobe Experience Platform (AEP), and ultimately into CJA. This option can save you time and effort, particularly if you have a significant number of classifications to migrate. Please note that you need to be an Adobe Analytics Product Admin to administer the Analytics Source Connector in AEP. The second option is to recreate the Adobe Analytics classifications in CJA. This involves going through each classification and recreating them within the CJA platform as a new dedicated lookup dataset. While this option may require more time and effort, it all

A product capability suggestion - In my case, I created a metrics of revenue with tax, which added 2 existing metrics of revenue and tax.  I then would like to create a segment of visits that meet a threshold of the calculated metrics.  Currently, Adobe Analytics cannot create segments using calculated metrics.   It will be useful if segments can use calculated metrics.

Hi All, I am facing a weird issue where any clicks on Exit outbound link (different domain / social media) renders the rest of the setup not working.I have used Adobe Data collection to setup the tags and within it I am using extensions like Adobe Client Datalayer to trigger Rules based on datalayer pushes. However, in testing when I click on any social media outbound link or any other outbound click, after that any basic CTA or link tracking events on the man site are not being triggered.

Hello,I am currently exploring the migration from Adobe Analytics to Adobe Experience Platform Customer Journey Analytics (AEP CJA) for our mobile application. Our app is built using Xamarin Native (MonoAndroid), and we have integrated Adobe Analytics using the existing mobile SDK.As part of our migration planning, I have a few questions:Is there official support or recommended integration paths for AEP CJA in Xamarin Native (MonoAndroid) applications?Can we leverage our existing Adobe Analytics implementation, or will significant changes be required to support AEP CJA?Are there any SDKs, wrappers, or sample projects available for Xamarin or .NET-based mobile apps targeting AEP CJA?What are the key considerations or challenges when migrating analytics tracking from Adobe Analytics to AEP CJA in a cross-platform environment?Any guidance, documentation, or references to migration best practices would be greatly appreciated.Thank you!

I am struggling with building a report based on an evar as I dont fully comprehend the nunances of evar.On my website, we have product pages. On those product pages, we use and evar to capture the product brand (evar10).The configurations of that evar are:merchandising : conversion variablebinding events: purchase event (order, revenue, units) checkout, cart additions, remove from cart, add to wishlist, remove from wishlist, product view, cart view, and cart open.allocation most recent : lastreset: do not resetexpire after: purchaseenable merchandising: enabled. Now, i want to know conversion rate for evar10 = brand_ASpecifically, I want to know 2 things :QUESTION 1. of all visits to products page where evar10='brand_A', what percentage of those visits purchased 'brand_A' products?QUESTION 2. of all visits to products page where evar10='brand_A', what percentage of those visits purchased a product (of any brand, does not have to be a brand_A product).I created a segment based on H

Hi all, Wondering how Journey Canvas or Fallout visualization treats journeys with touchpoints that have the same timestamp? There is a use case to understand how many people open, click/unsubscribe after an email is sent, but the email events are timestamped to the disposition date--meaning each sent, open and click action (when it happens on the same day) has the exact same timestamp. When using these disposition elements in a Freeform table to count People or Events etc., the numbers are accurate and match the dataset; but when I try to build out a journey in Canvas or Fallout, the numbers on the sequential touchpoints after the starting point (e.g. Sent) are slightly off (oftentimes less) than the freeform table. I presume it's because it cannot consistently interpret one disposition after the other because they have the same timestamp, but wondering if there's any other ideas. Why is that, and wondering if there are any workarounds other than altering the dataset's times

Hi Team,We’re currently implementing a strict Content Security Policy (CSP) in our web application, and we’ve encountered an issue where Adobe Analytics scripts are being blocked unless we add 'unsafe-eval' to the script-src directive.However, our security guidelines specifically aim to avoid 'unsafe-eval', so this is not a viable option for us.at.js 2.11.6

Hi Adobe Community,My organization currently uses Adobe Experience Cloud services and the Adobe Mobile SDK to send data via Processing Rules. I’m looking for documentation or examples of the event schema used in this setup—specifically how events are structured and sent to Adobe Analytics or other services.Additionally, we’re planning a future migration to Adobe Experience Platform (AEP) using Adobe Experience Platform Edge Network (AEP). I’d like to understand the equivalent XDM event schema structure for this implementation—how events are defined, what standard/custom field groups are typically used, and how to construct and send these events using the Mobile SDK.Any guidance, schema samples, or best practices would be greatly appreciated!Thanks in advance.

Hi 🙂 I was looking to identify all LLMs referring people to our site. For many they have unique referring domains, and Chat GPT seems to add their own query string parameter to URLs (thanks Open AI lol), but for things like google search ai summary, does anyone have any recommendations?Thanks! 

I am attempting to build a freeform table in CJA that tracks how many events where disposition = sent a specific person had per day, over a week or month. I have created a derived field which accurately does this using logic: case when disposition = sent, set = 1, then summarizing on person. If I pull the derived dimension into a freeform table with the date range being a week (ex 9/1-9/7), then it will accurately tell me how many people had 1, 2, 3, etc sent dispositions over the course of the whole week. The problem is, I want to see specifically, how many sent dispositions a person had per day, and then see multiple days over the course of the week in the same table (see screenshot attached for context of what I want the table to look like, with day as the rows and the columns being possibilities of number of sent dispositions). However, when I do this, instead of aggregating a person's sent dispositions over the specific days, it is aggregating them over the wee

How to track different device types ( tab, desktop, mobile) in Adobe analytics for a setup if not using a web sdk setup.I am using data collection to implement the setup. 

I have been using Adobe workspace PDF scheduled reports for a long time. Yesterday, I started noticing that my workspaces which are scheduled to be sent to multiple users by email at an hourly cadence are being sent as usual by Adobe, but Adobe has stopped attaching the PDF of the Workspace. So, essentially there is no report attached to the scheduled email. I have tried to cancel the existing schedule and add a new schedule multiple times, but it isn't helping. Is this is known issue? And, is there a solution?

Applications frequently face scenarios where the single standard datastream setup isn't sufficient to meet specific use case requirements. Whether it's refining data consumption, integrating custom processing logic within mobile apps, or managing the mobile app code release cycle, adjustments are often necessary. This discussion explores methods for modifying and overriding default datastream configurations by leveraging Data Collection (Tags), eliminating reliance on the mobile app code push cycle. As a result, updates to the datastream override can be implemented rapidly without going through the mobile app release process. The key benefit is the ability to configure datastream overrides at the Data Collection (Tags) level, rather than within the mobile app itself.  Additional Use Cases: There are various scenarios where your app may require adjustments to its datastream or dataset override configuration. In this blog, I will highlight a few key use cases to demonstrate when and

I want to see how many visitors were on a specific page between 10-10:30. In reporting,  I've filtered the time frame to look between 10-10:30 on a specific page. 1) If a user came at 9:50 and stayed idle on that page, will they be included in the total unique visitors between 10-10:30 in reporting? 2) If user came at 9:50 to the page and clicked on a CTA at 10:05, ill they be included in the total unique visitors between 10-10:30 in reporting?

Hi,I'm wondering if a TTL (time to live) for specific type of events within profiles in AEP (leveraged by both Audience Manager and CJA) affect what events are being used to stitch identities for CJA? Wondering if, when a TTL is established for profile events from a dataset, and it eliminates events from the dataset in profiles that would be needed as reference for stitching-- past that TTL time range-- would it indeed affect graph-based stitching in CJA? I.e. even though X days ago someone's ID got stitched w primary ID in their profile, once the TTL hits after that X days then the stitching reference goes away. Or, does the TTL does not affect how graph-based stitching is done for CJA, and it only affects the events that appear for a profile when building an audience in Audience Manager?