Adobe Analytics

When it comes to reporting on your data, there’s more than one way to do just about everything. That’s why it’s important to have standardization across your organization. For this week, I’m going to talk about some best practices for setting up and reporting on your analytics, and why they’re important.   Documentation Some people love it and some people hate it, but documentation is one of the most important aspects of your analytics implementation. People change roles and jobs all the time, so it’s very possible that the person (or even entire team) who set up your analytics implementation is no longer around. Once they’re gone all that’s left behind is anything they’ve written down. If a new analyst needs to understand what data is being captured, or if something looks like it’s broken, it’s vital to be able to refer to the documentation around what has been set up. There are some best practices to follow when it comes to your documentation.   First, you want to make sure

CJA Experimentation Reporting Over the last four weeks, we have looked at CJA Golden Nuggets, Tips & Tricks, Best Practices, and Integrations.  Today we'll enter the homestretch as we look at a specific use case - experimentation.  Adobe has recently launched an experimentation panel that many teams may find very useful.  A similar panel is available for some Analytics users, but in CJA it has greater availability and is easy to set up. CJA unlocks several new use cases.  Today we’ll focus on experimentation and the ease of beginning an analysis.  We’ll walk through ensuring the experimentation components are set up correctly, the process of building the analysis, and we’ll close with some ways this feature could be expanded to bring more value. The new experimentation panel makes it easy to generate accurate reporting.  This allows the experimentation team to focus more on ideating and implementing testing.  This panel simplifies t

Real-Time Report: Real-time reporting showcases the traffic for the active visits on the site and ranks the dimensions. This real-time view helps to make decisions on changing circumstances of the performance, campaigns and respond to the changes quickly.   Configuring Real-Time Reports: Navigation: Analytics > Admin > Report Suites > Select a Report Suite > Edit Settings > Real-Time > Save or Save and View Report Enable Real-Time toggle to enable the real-time reports. You can create up to 3 real-time reports. You can add 1 metric, 1 primary dimension and 2 secondary dimensions per report. There are only few metrics and dimensions are supported in real-time reports. The selected dimensions should be unique. Some dimensions do not persist in real-time, if you select a non-persistent metric, you will see the below warning eVars are not supported in real-time reports. If you have created classifications, they will appear under the defined dimension. Once the r

Over the last three weeks, we have looked at CJA Golden Nuggets, Tips & Tricks, and Best Practices.  Today we will look at integrating CJA with other data and tools that can unlock new insights for your organization.  Here we’ll look primarily at bringing data into CJA.  We’ll touch only briefly at ways to get data out of CJA. Overview One of CJA’s benefits is the ability to analyze online and offline customer engagement holistically.  Having a clear understanding of CJA’s datasets, requirements, and how to integrate the data is important to ensure the data is useful in addressing key business questions. Use cases There are almost a limitless number of use cases where data can be integrated with CJA.  Today we’ll focus on three typical use cases.  Customer service interactions – For many companies, the ability to better understand the full customer journey is essential.  Being able to see person-focused web and customer service interaction seamles

  Introduction Adobe Customer Journey Analytics (CJA) is built on three types of datasets to gather actionable insights into your customers' journeys. These dataset types, Event, Lookup, and Profile, each play a unique role in capturing and presenting different aspects of customer data. Event datasets are structured to record detailed interactions at specific points in time, covering every key action that a customer takes on your platforms. In contrast, Lookup datasets serve as reference points, offering metadata context to the recorded event values. Profile datasets, however, concentrate on the individuals behind those actions, combining the data into customer attribute metadata. Each dataset type serves a unique purpose and provides specific data points critical to understanding customer interactions. This blog post offers an overview of these three CJA dataset types. It highlights their key characteristics and potential applications, helping you understand their functionaliti

Last week we looked at several CJA Golden Nuggets.  This week we'll look at three tips & tricks that can streamline your workflows.  Through my work with CJA for multiple clients, watching various webinars, reading blog posts, and studying for my CJA Expert Certification, I’ve seen many different approaches.  These are some of the best tips & tricks I've encountered for CJA.  I'd love to hear your favorites as well!  Add them in the comments below! Modifying multiple component settings When managing components, many settings can be managed for multiple components all at once.  For example, a general best practice is using lowercase for dimension values.  When lowercase is enabled, values such as Homepage and homepage will be reported together.  Without this setting, each version of capitalization will be reported on a unique row. Data view search and settings make it easy to enable the lowercase setting to many components at once.  I

I want to share how I created an advanced Goal/Forecasting report. A goal or a forecasting report is a monitoring type report. Creating a combined Forecasting and Goal Progress (or Goal Pacing) report is a valuable way to track your progress towards a specific goal over time and forecast your future progress. Such reports can be a useful tool for monitoring and making data-driven decisions.To have goal tracking, you need a defined goal and a time period in which to achieve that goal. For example, the goal can be a target like the visitor guarantee for a sponsored program, or a traffic goal such as last year's page view count plus 10%. The time period could be a year or some other number of months or weeks.In the following sponsorship example, there is an annual visitor goal, but the monthly goals are different for each month. I will explain what the report shows and then I will explain in detail how you can make the report. This is just an example. There are other metrics and

Ever since I first learned it was possible, one of my favourite type of segments to build is the visit-in-hit segment. I've always been a fan of logic and puzzles, so learning how to build segments and understanding what type of data they return was particularly interesting. I still remember the first time I learned about segments and was told that you put smaller containers inside bigger ones, and to do it the other way would make it invalid. I took that as fact for a very long time.   Then one day I had a fallout visualization that I wanted to build a segment from. So I right clicked and selected build segment. Looking at what workspace generated I saw a visit container inside of a hit one. This went against what I had been taught, and it sent me down a rabbit hole of investigation. What I eventually learned was that segments with a bigger container inside a smaller one (like visit-in-hit or visitor-in-visit) does work and provides some very specific insights. I got a chance to

For this week's tech byte, I'm going to talk about the Data Dictionary and the importance of good documentation. If you missed the past weeks, you can check them out here: Tuesday Tech Bytes - Week 2 Tuesday Tech Bytes – Week 1   When building your implementation one of the most important steps is keeping good documentation so that when you (or those that come after you) want to understand what data is being captured, you have a solid reference. In the past this would typically be done in an SDR (solution design reference) external to Adobe. There still are some benefits to having external documentation, but now Adobe has made it possible to keep some of your documentation within the workspace platform using the Data Dictionary.   What is the Data Dictionary? The Data Dictionary contains a list of all your components, including your custom metrics and segments. It provides you an opportunity to add a description and tags, as well as “always include” or “always exclude” compon

Over the last two weeks, we have looked at CJA Golden Nuggets and Tips & Tricks.  Today we will look at best practices in CJA that can help your team work more effectively. Data friendliness The best practices we will explore today generally fall under the umbrella of things that make data easier to work with and understand.  Making data easier to work with in CJA increases the efficiency and accuracy of analysts and other users.  Adapting certain best practices also makes it easier for your audience to digest and understand the data. Approved Components & Tags For components that are frequently used and have been well vetted, admins can mark those components as approved.  Doing so adds a checkmark to the component.  Additionally, adding tags to components can simplify the process of finding the correct component.  Depending upon your use cases, you might tag components in categories such as geo dimensions, experimentation, funnel, and commerce. &

Use this thread to ask any questions related to the Getting Started with Analysis Workspace course/playlist on Experience League. Experts are monitoring this thread to ensure your questions are answered.

We all regret decisions in life; in Adobe Analytics we may regret storing a number in an eVar or prop! This is because unlike custom events, you can't perform numerical calculations (such as summing or averaging) on props or eVars.Obviously, you can make changes to your implementation to capture these values in a custom event going forward. However, what can be done about your historical data? Fortunately, using a combination of Classifications and Calculated Metrics this can be taken care of. Method To explain the approach, I'm going to use the example of converting from a three-digit number stored in a prop, to a metric. However, this method can be extended to cope with any number of digits and decimal places as well. Step1: Create classifications We are going to use classifications to split our number up into separate classifications, one classification for each individual digit in the number.In this example we are dealing with a three-digit number so we will need three classificati

Issue -Earlier we used to add multiple segments as options in a segment dropdown.But since the new changes have been made, where we can select multiple segments (as OR condition) in a segment dropdown, I am not able to add more than two segments in a dropdown.Even by pressing shift, it doesn't work. Update -Spoke with support team, there seems to be an engineering bug.everyone in my org is facing this issues.Spoke to a friend in another org, they are facing this issue too.Will keep you updated, once I have any resolution from the engineering team.If you guys are facing the same issue with segment dropdown, please do mention here in replies, so that the engineering team can work on this as a priority (based on the wider impact). Also, as a good practice, please raise a ticket with the Support team.

Hello Adobe Analytics Community! Welcome back to the Tuesday Tech Bytes Series!  We had an excellent learning and engagements in Tuesday Tech Bytes series 2023. We are happy to continue the series this year as well! Tune in every Tuesday for a new discussion with our community advisors! Week 1 - Golden NuggetsWeek 2 - Tips & TricksWeek 3 - Best PracticesWeek 4 - IntegrationsWeek 5 - Use CasesWeek 6 - Tips & Tricks If you use traditional Adobe Analytics, be sure to see this thread for their Tuesday Tech Bytes as well! We warmly invite you to engage with our posts by liking, commenting, and sharing!   2023 Tuesday Tech Bytes Thread   Thanks @jagpreet_singh_ & @seanrobinson  for re-launching this initiative!  

I want to find viewers of a page from time of market close to market open for a certain time period and need to know if I should set times in PST or EST to accommodate for the time difference (markets are open 9:30 AM - 4 PM EST).

Come join Christos Voutsakis, Sarah Owen and myself, Jennifer Dungan for a webinar that shines a spotlight on real-world use cases and best practices in Adobe Analytics Workspace! https://advancedanalyticsamer2022.experienceleague.adobeevents.com/ Tuesday, 19th July, 2022 8:00am – 9:00am PT 

Hi I have a dimension of evar type where the time is mentioned in microsecond. Attached is the screenshot where it shows time spent in cart for a session id.There can be multiple  time frames for one session id, depending the number of items in cart etc.How can i convert it to metric as a sum of all the time frames ?I want something like -- 76254353 (session id) -- 54000 (time spent in cart)Please find attached the sample for a session id.

Introduction Adobe Customer Journey Analytics (CJA) is a workspace built on top of the Adobe Experience Platform (AEP). CJA enables organizations to analyze and optimize their customer journeys by providing a comprehensive view of the journey across multiple platforms, channels, and touchpoints. This empowers organizations to make informed decisions based on data-driven insights. To fully leverage CJA, it is important to ensure that the data model on AEP is robust and that the data used is at the appropriate level of granularity. This means that data brought into CJA should be structured suitably for the intended analysis. To achieve this, it is essential to establish a strong identity framework, use the correct datasets for analysis, make optimal use of CJA Data Views, and accurately configure CJA Data View components. Additionally, it is important to consider the interplay between CJA and its role in the broader AEP ecosystem of data flows and application solutions. 1. Have A Clea

Introduction   Retail sites span a range of formats, but the primary goal is always to drive sales. Some sites may display a list of products to choose from, others may recommend a product based on your browsing and user history. This can create a long list of products that are sent to Adobe Analytics when a page loads. This can prove both useful and cumbersome. Although, having every single product loaded on the page as a product view Is technically correct, it may not be the most useful method to answer all of your business questions.   With the potential deluge of product recommendations, similar products, and marketing modules pushing users to engage with new products comes an analytics conundrum: how are we going to analyze this correctly? Below we will layout a few solutions that one can implement to simplify analysis.   Problem   With so many products loading on the page, marketers want to see product views and full funnel results for primary vs secondary pro

Introduction Totals are not always what they appear to be to new users of Adobe Analytics. New members on your team may not fully grasp why the total at the top of a workspace report is not the sum of the rows and in what situations it is appropriate to sum rows. In the below example we see the total for visits are less than the sum of the first 10 rows (over 6 million). The reason is that a visit takes place over a period of time and during that time a user may view products in each of the site sections. The user constitutes only one visit, but they would also appear as one visit in each of the rows (merchandising site section).     While this example is difficult enough to wrap your head around, how to handle totals for merchandising evars can vary by the metric you are totaling. A normal evar may fire when a page loads or a link is clicked. A merchandising evar fires under specific action and is not only associated with that action, but bound to a specific product. “

Introduction:Understanding and analyzing web traffic is crucial for any digital enterprise, and traffic analytics plays a pivotal role in this realm. Adobe Analytics, a leader in the digital analytics field, provides comprehensive insights into website and app performance, yet many users confront challenges when faced with instances of low traffic. These scenarios often result in underrepresented data, affecting the quality and reliability of traffic analysis. Therefore, grasping the impact of low traffic on data accuracy and decision-making processes is imperative for businesses aiming to optimize their online presence.Understanding Low Traffic in Adobe Analytics:When a report in Adobe Analytics accumulates many unique values, it employs a system to ensure that the most essential data is visible. This system includes the categorization of excess values under the label "Low-Traffic" once they surpass a predefined threshold. Specifically, Adobe Analytics sets two thresholds each month t

Hello team, I have a general query around time over time comparison within Adobe analysis workspace. Is there a way one can easily display only % change calculated metrics within a freeform table? For example, Yesterday % change, Last week % change, Last month % change, etc but hide other columns where these metrics are calculated.

    Join us at Adobe Summit 2024 for the Coffee Break Q&A Live series, a unique opportunity to network with and learn from expert users, the Adobe product team, and Adobe partners in a small group, 30 minute “ask me anything”, conversation-driven format.   Discuss recent product innovations, use cases you’re working through, and helpful tips and tricks with experts and peers who can help you elevate your knowledge. See the daily schedule below - join us and learn from the best!  Location: Community Pavilion, Adobe Booth - Experience League Community Connections area  Tuesday, March 26  Time  Topic & Solution  Speaker(s)  11:00am – 11:30am  Ask Me Anything: Adobe Target  Gentry Lin, Principal Platform Specialist – Adobe  Ryan Roberts, Principal Consultant, Proof of Concept – Adobe  Vadym Ustymenko, Principal Technology Consultant – Adobe  11:45am – 1

Organizations thrive on efficient data warehousing systems that empower users with accessibility, functionality, and control. Recognizing these needs, the latest enhancements in Adobe Analytics' Data Warehouse functionalities promise to revolutionize how users interact with data. Now, Adobe Analytics Data Warehouse users can leverage two groundbreaking features aimed at streamlining data accessibility and management: the introduction of "Make available to users in your organization" and the unveiling of "Show all destinations" toggle switches. 1. Empowering Accessibility: "Make available to users in your organization" One of the key challenges in data warehousing is ensuring that the correct data is accessible to the right users at the right time. With the introduction of the "Make available to users in your organization" toggle switch, users now possess the capability to disseminate their data requests seamlessly across the organization. Traditionally, data requests were confined to i

  Welcome to the 9th edition of the Adobe Analytics Community Lens! Adobe Analytics Community Lens is your community bulletin board highlighting the latest updates from the Adobe Analytics Community in one place. In this edition, we are sharing updates from March 2024 through June 2024, including, the most viewed Adobe Analytics content on Experience League, as well as the latest product releases, upcoming and past learning opportunities, and a lot more!   Adobe Analytics Community Lens    📅EVENTS AND OPPORTUNITIES📅 Adobe Analytics Mentorship Program: May 29th – August 23rd We are thrilled to announce the second run of ~ The Adobe Analytics Community Mentorship Program ~ aimed at empowering Community members like you to upgrade your skill level by achieving one of the valuable Adobe Certifications. This program brings our Community's experts, or – Mentors – together with our newer aspiring product learners, or – A