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Comprehensive Technical Tutorial for AEP
  • Comprehensive Technical Tutorial for Adobe Experience Platform
    • Architecture
    • Video Overview
  • 0 - Getting started
    • 0.0 Which environment do I use?
    • (Deprecated) Install the Chrome extension for the Experience League documentation
    • 0.1 Use Demo System Next to setup your Adobe Experience Platform Data Collection client property
    • 0.2 Create your Datastream
    • 0.3 Set up the website
    • 0.4 Set up the mobile app
    • 0.5 Ingest Data to AEP through the Website
    • 0.6 Ingest Data to AEP through the Mobile App
    • 0.7 Visualize your own Real-time Customer Profile - UI
    • 0.8 See your Real-time Customer Profile in action in the Call Center
    • 0.9 Set up and use the AEP API to visualize your Real-Time Customer Profile
    • 0.10 Install the Experience Platform Debugger Extension
    • 0.11 What if I want to demonstrate basic AEP concepts directly on a live website?
  • 1 - Adobe Experience Platform Data Collection and the Web SDK extension
    • 1.1 Understanding Adobe Experience Platform Data Collection
    • 1.2 Edge Network, Datastreams and Server Side Data Collection
    • 1.3 Introduction to Adobe Experience Platform Data Collection
    • 1.4 Client-side Web Data Collection
    • 1.5 Implement Adobe Analytics and Adobe Audience Manager
    • 1.6 Implement Adobe Target
    • 1.7 XDM Schema requirements in Adobe Experience Platform
    • Summary and Benefits
  • 2 - Data Ingestion
    • 2.1 Explore the Website
    • 2.2 Configure Schemas and Set Identifiers
    • 2.3 Configure Datasets
    • 2.4 Data Ingestion from Offline Sources
    • 2.5 Data Landing Zone
    • Summary and Benefits
  • 3 - Real-time Customer Profile
    • 3.1 Visit the website
    • 3.2 Visualize your own real-time customer profile - UI
    • 3.3 Visualize your own real-time customer profile - API
    • 3.4 Create a segment - UI
    • 3.5 Create a segment - API
    • 3.6 See your Real-time Customer Profile in action in the Call Center
    • Summary and benefits
  • 4 - Query Service
    • 4.0 Prerequisites
    • 4.1 Getting Started
    • 4.2 Using the Query Service
    • 4.3 Queries, queries, queries... and churn analysis
    • 4.4 Generate a dataset from a query
    • 4.5 Query Service and Power BI
    • 4.6 Query Service and Tableau
    • 4.7 Query Service API
    • Summary and benefits
  • 5 - Intelligent Services
    • 5.1 Customer AI - Data Preparation (Ingest)
    • 5.2 Customer AI - Create a New Instance (Configure)
    • 5.3 Customer AI - Scoring Dashboard and Segmentation (Predict & Take Action)
  • 6 - Real-time CDP - Build a segment and take action
    • 6.1 Create a segment
    • 6.2 Review how to configure DV360 Destination using Destinations
    • 6.3 Take Action: send your segment to DV360
    • 6.4 Take Action: send your segment to an S3-destination
    • 6.5 Take Action: send your segment to Adobe Target
    • 6.6 External Audiences
    • 6.7 Destinations SDK
    • Summary and benefits
  • 7 - Adobe Journey Optimizer: Orchestration
    • 7.1 Create your event
    • 7.2 Create your journey and email message
    • 7.3 Update your Data Collection property and test your journey
    • Summary and benefits
  • 8 - Adobe Journey Optimizer: External data sources and custom actions
    • 8.1 Define an event
    • 8.2 Define an external data source
    • 8.3 Define a custom action
    • 8.4 Create your journey and messages
    • 8.5 Trigger your journey
    • Summary and benefits
  • 9 - Adobe Journey Optimizer: Offer Decisioning
    • 9.1 Offer Decisioning 101
    • 9.2 Configure your offers and decision
    • 9.3 Prepare your Data Collection Client property and Web SDK setup for Offer Decisioning
    • 9.4 Combine Adobe Target and Offer Decisioning
    • 9.5 Use your decision in an email
    • 9.6 Test your decision using the API
    • Summary and benefits
  • 10 - Adobe Journey Optimizer: Event-based Journeys
    • 10.1 Configure an event-based journey - Order Confirmation
    • 10.2 Configure a batch-based newsletter journey
    • 10.3 Apply personalization in an email message
    • 10.4 Setup and use push notifications
    • 10.5 Create a business event journey
    • Summary and benefits
  • 11 - Customer Journey Analytics - Build a dashboard using Analysis Workspace on top of Adobe Experie
    • 11.1 Customer Journey Analytics 101
    • 11.2 Connect Adobe Experience Platform Data Sets in Customer Journey Analytics
    • 11.3 Create a Data View
    • 11.4 Data Preparation in Customer Journey Analytics
    • 11.5 Visualization using Customer Journey Analytics
    • Summary and benefits
  • 12 - Ingest & Analyze Google Analytics data in Adobe Experience Platform with the BigQuery Source Co
    • 12.1 Create your Google Cloud Platform Account
    • 12.2 Create your first query in BigQuery
    • 12.3 Connect GCP & BigQuery to Adobe Experience Platform
    • 12.4 Load data from BigQuery into Adobe Experience Platform
    • 12.5 Analyze Google Analytics Data using Customer Journey Analytics
    • Summary and benefits
  • 13 - Real-Time CDP: Segment Activation to Microsoft Azure Event Hub
    • 13.1 Configure your Microsoft Azure EventHub environment
    • 13.2 Configure your Azure Event Hub Destination in Adobe Experience Platform
    • 13.3 Create a segment
    • 13.4 Activate segment
    • 13.5 Create your Microsoft Azure Project
    • 13.6 End-to-end scenario
    • Summary and benefits
  • 14 - Real-Time CDP Connections: Event Forwarding
    • 14.1 Create a Data Collection Event Forwarding property
    • 14.2 Update your Datastream to make data available to your Data Collection Event Forwarding property
    • 14.3 Create and configure a custom webhook
    • 14.4 Create and configure a Google Cloud Function
    • 14.5 Forward events towards the AWS ecosystem
    • Summary and benefits
  • 15 - Stream data from Apache Kafka into Adobe Experience Platform
    • 15.1 Introduction to Apache Kafka
    • 15.2 Install and configure your Kafka cluster
    • 15.3 Configure HTTP API Streaming endpoint in Adobe Experience Platform
    • 15.4 Install and configure Kafka Connect and the Adobe Experience Platform Sink Connector
    • Summary and benefits
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On this page
  • Objectives
  • 11.4.1 Analysis Workspace UI in CJA
  • Create Your Project
  • 11.4.2 Calculated Metrics
  • Conversion Rate
  • 11.4.3 Calculated Dimensions: Filters (segmentation) & Date Ranges
  • Filters: Calculated Dimensions
  • Date Ranges: Calculated Time Dimensions
  1. 11 - Customer Journey Analytics - Build a dashboard using Analysis Workspace on top of Adobe Experie

11.4 Data Preparation in Customer Journey Analytics

Customer Journey Analytics - Data preparation in Analysis Workspace

Previous11.3 Create a Data ViewNext11.5 Visualization using Customer Journey Analytics

Last updated 2 years ago

Objectives

  • Understand the Analysis Workspace UI in CJA

  • Understand the concepts of data preparation in Analysis Workspace

  • Learn how to do data calculations

11.4.1 Analysis Workspace UI in CJA

Analysis Workspace removes all of the typical limitations of a single Analytics report. It provides a robust, flexible canvas for building custom analysis projects. Drag-and-drop any number of data tables, visualizations, and components (dimensions, Metrics, segments, and time granularities) to a project. Instantly create breakdowns and segments, create cohorts for analysis, create alerts, compare segments, do flow and fallout analysis, and curate and schedule reports for sharing with anyone in your business.

Customer Journey Analytics brings this solution on top of Platform data. We highly recommend watching this four-minute overview video:

If you haven't used Analysis Workspace before, we highly recommend watching this video:

Create Your Project

Now it's time to create your first CJA project. Go to the projects tab inside of CJA. Click Create new.

You'll then see this. Select Blank project and then click Create.

You'll then see an empty project.

First, make sure to select the correct Data View in the upper right corner of your screen. In this example, the Data View to select is vangeluwe - Omnichannel Data View.

Next, you'll save your project and give it a name. You can use the following command to save:

OS
Short cut

Windows

Control + S

Mac

Command + S

You'll see this popup:

Please use this naming convention:

Name
Description

--demoProfileLdap-- - Omnichannel Analysis

--demoProfileLdap-- - Omnichannel Analysis

Next, click Save.

11.4.2 Calculated Metrics

Although we have organized all the components in the Data View, you still need to adapt some of them, so that business users are ready to start their analysis. Also, during any analysis you can create calculated metric to go deeper on the insights finding.

As an example we will create a calculated Conversion Rate using the Purchases metric/event we defined on the Data View.

Conversion Rate

Let's start opening the calculated metric builder. Click on the + to create your first Calculated Metric in Analysis Workspace.

The Calculated Metric Builder will show up:

Find the Purchases in the list of Metrics in the left side menu. Under Metrics click Show all

Now drag an drop the Purchases metric in to the calculated metric definition.

Typically, conversion rate means Conversions / Sessions. So let's do the same calculation in the calculated Metric definition canvas. Find the Sessions metric and drag and drop it into the definition builder, under the Purchases event.

Notice that the division operator is automatically selected.

The conversion rate is commonly represented in percentage. So, let's change the format to be percentage and also select 2 decimals.

Finally, Change the name and description of the calculated metric:

Title
Description

Conversion Rate

Conversion Rate

You will have something like this on your screen:

Don't forget to Save the Calculated Metric.

11.4.3 Calculated Dimensions: Filters (segmentation) & Date Ranges

Filters: Calculated Dimensions

Calculations are not meant to be only for Metrics. Before starting any analysis it's also interesting to create some Calculated Dimensions. This basically meant segments back in Adobe Analytics. In Customer Journey Analytics, these segments are called Filters.

Creating filters will help business users to start the analysis with some valuable calculated dimensions. This will automate some tasks as well as helping on the adoption part. Here are some examples:

  1. Own Media, Paid Media,

  2. New vs Returning visits

  3. Customers with Abandoned Cart

These filters can be created before or during the analysis part (which you'll do in the next exercise).

Date Ranges: Calculated Time Dimensions

Time Dimensions are another type of calculated dimensions. Some are already create, but you also have the ability to create your own custom Time Dimensions at the data preparation phase.

These Calculated Time Dimensions we will help analysts and business users to remember important dates and use them to filter and change the reporting time. Typical questions and doubts that come to our minds when we do analysis:

  • When was Black Friday last year? 21th-29th?

  • When did we run that TV campaign in December?

  • From when to when did we do the 2018 Summer Sales? I want to compare it against 2019. By the way, do you know the exact days in 2019?

You've now finished the data preparation exercise using CJA Analysis Workspace.

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CJA OVERVIEW VIDEO
ANALYSIS WORKSPACE VIDEO