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[B2B Edition]{class="badge informative"}

Setup for B2B Edition use cases

AVAILABILITY
The functionality described in this article, and any other article or functionality badged with [B2B Edition]{class="badge informative"}, is in the Limited Testing phase of release and might not be available yet in your environment.
Also, [B2B Edition]{class="badge informative"} functionalities and documentation of [B2B Edition]{class="badge informative"} functionalities are subject to change and no legal obligations can be derived from it.
This note will be removed when the functionality is generally available. For information about the Customer Journey Analytics release process, see Customer Journey Analytics feature releases.

This article covers a typical setup of the Customer Journey Analytics B2B Edition to support the following uses cases:

NOTE
The demo data and screenshots that are used in these use cases are for illustration purposes only and do not reflect real world data.

Solution design reference

Before you set up Customer Journey Analytics B2B Edition, ensure you have a proper solution design reference in place that documents each of the fields you collect.

An example solution design reference could look like:

Event dimensions
table 0-row-1 1-row-1 2-row-1 3-row-1 4-row-1 5-row-1 6-row-1 7-row-1 8-row-1 9-row-1 10-row-1 11-row-1 12-row-1 13-row-1 14-row-1 15-row-1 16-row-1 17-row-1 18-row-1 19-row-1 20-row-1 21-row-1 22-row-1 23-row-1 24-row-1 25-row-1 26-row-1 27-row-1 28-row-1 29-row-1 30-row-1 31-row-1 32-row-1 33-row-1
Dimension name
Account ID
Account Name
Buying Group ID
Call Center
Call Center Representative ID
Call ID
Campaign Tracking Code
Content ID
Content Type
Data Source
Device Type
Event Details
Event Name
Funnel
Interaction Channel
Lead ID
Marketing Channel
Marketing Event ID
Marketing Event Type
Opportunity ID
Page
Page Details
Referring Domain
Sales Representative ID
Sales Stage Name
Sales Stage Number
Site Section
SKU
Subsidiary Account ID
Survey ID
Survey Satisfaction Score
Survey Type
User ID
Event metrics
table 0-row-2 1-row-2 2-row-2 3-row-2 4-row-2 5-row-2 6-row-2 7-row-2 8-row-2 9-row-2 10-row-2 11-row-2 12-row-2 13-row-2 14-row-2 15-row-2 16-row-2 17-row-2 18-row-2 19-row-2 20-row-2 21-row-2 22-row-2 23-row-2 24-row-2 25-row-2 26-row-2 27-row-2 28-row-2 29-row-2 30-row-2 31-row-2 32-row-2 33-row-2 34-row-2 35-row-2 36-row-2 37-row-2 38-row-2 39-row-2 40-row-2 41-row-2 42-row-2 43-row-2 44-row-2 45-row-2 46-row-2 47-row-2 48-row-2 49-row-2 50-row-2 51-row-2 52-row-2 53-row-2 54-row-2
Metric name Event type
Account Creation: Complete Counter
Account Creation: Start Counter
Call Cost Currency
Call Length Counter
Call Satisfaction Score Numeric
Call Surveys Completed Counter
Calls Counter
Closed-Lost Counter
Closed-Won Counter
Content Views Counter
Deal Size Currency Display Click-throughs Counter
Display Impressions Counter
Email Bounced Counter
Email Clicked Counter
Email Delivered Counter
Email Opened Counter
Email Sent Counter
Event Attendance Counter
Event Registration: Complete Counter
Event Registration: Step 1 Counter
Event Registration: Step 2 Counter
Event Registration: Step 3 Counter
Global Satisfaction Score Numeric Inbound Call Counter
Lead Form: Complete Counter
Lead Form: Step 1 Counter
Lead Form: Step 2 Counter
Lead Generated Counter
Lead Qualification Counter
Meetings Counter
MQL Disqualified Counter
MQL Qualified Counter
Needs Assessment Counter
Negotiation Counter
Objection Handling Counter
Opportunities Counter
Opportunity Creation Counter
Orders Counter
Outbound Call Counter
Post-Sales Follow-Up Counter
Proposal Submission Counter
Revenue Closed-Lost Currency
Revenue Closed-Won Currency
Sales Contact Calls Counter
Sales Stage Started Counter
SMS Click-throughs Counter
SMS Sent Counter
Social Click-throughs Counter
Social Impressions Counter
Solution Presentation Counter
SQL Disqualified Counter
SQL Qualified Counter
Units (do not expose) Counter
VoC Survey Satisfaction Score Numeric
VoC Surveys Completed Counter
Person records
table 0-row-2 1-row-2 2-row-2 3-row-2 4-row-2 5-row-2 6-row-2 7-row-2 8-row-2 9-row-2 10-row-2 11-row-2 12-row-2 13-row-2 14-row-2 15-row-2 16-row-2 17-row-2 18-row-2 19-row-2 20-row-2 21-row-2 22-row-2 23-row-2 24-row-2 25-row-2 26-row-2 27-row-2 28-row-2 29-row-2 30-row-2 31-row-2 32-row-2 33-row-2 34-row-2 35-row-2 36-row-2 37-row-2 38-row-2 39-row-2 40-row-2 41-row-2 42-row-2
Data view field name Field type
Age Metric
Age Group Dimension
Category 1 Affinity Level Dimension
Category 1 Affinity Score Metric
Category 2 Affinity Level Dimension
Category 2 Affinity Score Metric
Category 3 Affinity Level Dimension
Category 3 Affinity Score Metric
Category 4 Affinity Level Dimension
Category 4 Affinity Score Metric
Category 5 Affinity Level Dimension
Category 5 Affinity Score Metric
Consent Advertising Dimension
Consent All Communications Dimension
Consent Direct Mail Dimension
Consent Email Dimension
Consent Mobile Phone Dimension
Consent Personalization Dimension
Consent Share Data Dimension
Consent SMS Dimension
Email Dimension
First Name Dimension
Gender Dimension
Individual City Dimension
Individual CLTV Level Dimension
Individual CLTV Score Metric
Individual Country Dimension
Individual Phone Dimension
Individual Postal Code Dimension
Individual Propensity to Buy Level Dimension
Individual Propensity to Buy Score Metric
Individual Propensity to Churn Level Dimension
Individual Propensity to Churn Score Metric
Individual Propensity to Upgrade Level Dimension
Individual Propensity to Upgrade Score Metric
Individual State Dimension
Individual Street Address Dimension
Job Title Dimension
Last Name Dimension
Net Promoter Score Metric
Net Promoter Status Dimension
Role Type Dimension
Account records
table 0-row-2 1-row-2 2-row-2 3-row-2 4-row-2 5-row-2 6-row-2 7-row-2 8-row-2 9-row-2 10-row-2 11-row-2 12-row-2 13-row-2 14-row-2 15-row-2 16-row-2 17-row-2 18-row-2 19-row-2 20-row-2 21-row-2 22-row-2 23-row-2 24-row-2 25-row-2
Data view field name Field type
Annual Revenue Metric
Company City Dimension
Company CLTV Level Dimension
Company CLTV Score Metric
Company Country Dimension
Company Name Dimension
Company Phone Dimension
Company Postal Code Dimension
Company Propensity to Buy Level Dimension
Company Propensity to Buy Score Metric
Company Propensity to Churn Level Dimension
Company Propensity to Churn Score Metric
Company Propensity to Upgrade Level Dimension
Company Propensity to Upgrade Score Metric
Company Size Dimension
Company State Dimension
Company Street Address Dimension
Industry Dimension
Number of Employees Metric
Partner Audience - Hardware Shoppers Dimension
Partner Audience - Rapid Growth Dimension
Partner Audience - Services Needed Dimension
Partner Audience - Software Shoppers Dimension
Revenue Range Dimension
Website Dimension
SKU records
table 0-row-2 1-row-2 2-row-2 3-row-2 4-row-2 5-row-2 6-row-2
Data view field name Field type
Hardware Product Category Dimension
Hardware Product Name Dimension
Service Category Dimension
Service Name Dimension
Software Product Category Dimension
Software Product Name Dimension

Schemas and datasets

The data that supports the solution design reference is structured using the following schemas and datasets.

Event data

The event dimensions and metrics are supported through a time-series (event) based schema and one or more datasets that contain event data.

Person data

The person records are supported through a record (profile) based schema and one or more datasets that contain person data. See below for an example of person data (based on the example solution design reference) typically available in such a dataset.

B2B person schema and datasets

Account data

The account records are supported through a record (lookup) record based schema and one or more datasets that contain account data. See below for an example of account data (based on the example solution design reference) typically available in such a dataset.

B2B account schema and datasets

SKU data

The SKU records are supported through a record (lookup) based schema and one or more datasets that contain SKU data. See below for an example of SKU data (based on the example solution design reference) typically available in such a dataset.

B2B SKU schema and datasets

Connection

Define an account-based connection in Customer Journey Analytics to ingest and join records from the event, account, person and SKU datasets.

  1. Create a new connection in Customer Journey Analytics.

  2. Enter a descriptive name and description for the connection.

  3. Select Building Account as the Primary ID.

  4. Select all Optional containers.

  5. Select your preferred sandbox and estimate the average number of daily events.

    B2B account-based connection

  6. Select Add datasets and add the B2B datasets that contain the data for events, accounts, persons and SKUs.

    B2B connection - add datasets

  7. Select Next to configure the settings for each of the selected datasets.

  8. For the event dataset, ensure you select the appropriate fields that correspond to the identities for Account ID, Global Account ID, Opportunity ID, Buying Group ID and Person ID.

    B2B connection - add event dataset

  9. Scroll down to configure the account records dataset. Ensure you select the correct identifier (Account_ID) to match the account by the Global Account container. Select the correct identifier (Account_ID) as the Global Account field.

    B2B connection - add account dataset

  10. Scroll down to configure the person records dataset. Ensure you select the correct key (Person_ID) to match the person by the Person container. Select the appropriate identity (Profile_Account_ID_Individual) to match the Global Account field.

    B2B connection - add person dataset

  11. Scroll down to configure the SKU records dataset. Ensure you select the correct key (Sku). Select Match by field because no container is configured or available for this data. Select the SKU field in the event dataset(SKU (event datasets)) as the matching key.

    B2B connection - add SKU dataset

  12. Select Add datasets to save the datasets and their configured settings.

  13. Select Save to save the connection.

Data view

After data is ingested in Customer Journey Analytics, you want to create a data view that includes all the components you have defined in your solution design reference.

Configure

  1. Create a new data view in Customer Journey Analytics.

  2. Select the connection you previously created (for example: B2B Demo Connection (ExL)).

  3. Provide a name for the data view. For example: B2B Demo Data view (ExL) and optionally a description.

  4. Optionally, rename the containers. Or stick with the default container names.

    B2B data view - configure

  5. Select Save and continue.

Components

By default, all standard components are already included in your data view. These standard components include the B2B specific metrics for Accounts, Buying Groups, Global Accounts, and Opportunities.

  1. Add all event dimensions that you have defined in the solution design reference, to the dimension components in your data view. For example, the field Event Name, which represents the Event Name dimension. Ensure you configure the dimension component through the available Component settings.

    B2B data view - components - event dimensions

  2. Add all event metrics that you have defined in the solution design reference to the metrics components in your data view. For example, the field SQL Qualified, which represents the SQL Qualified metric. Ensure you configure the dimension component through the available Component settings.

    B2B data view - components - event metrics

  3. Add all account dimensions that you have defined in the solution design reference to the dimension components in your data view. For example, the field Industry, which represents the Industry dimension. Ensure you configure the dimension component through the available Component settings.

    B2B data view - components - account dimensions

  4. Add all account metrics that you have defined in the solution design reference to the metrics components in your data view. For example, the field Number_of_Employees, which represents the Number_of_Employees metric. Ensure you configure the dimension component through the available Component settings.

    B2B data view - components - account metrics

  5. Add all person dimensions that you have defined in the solution design reference to the dimension components in your data view. For example, the field Category_1_Affinity_Level, which represents the Category_1_Affinity_Level dimension. Ensure you configure the dimension component through the available Component settings.

    B2B data view - components - account dimensions

  6. Add all person metrics that you have defined in the solution design reference to the metrics components in your data view. For example, the field Category_1_Affinity_Score, which represents the Category_1_Affinity_Score metric. Ensure you configure the dimension component through the available Component settings.

    B2B data view - components - account metrics

  7. Add all SKU dimensions that you have defined in the solution design reference to the dimension components in your data view. For example, the field Service Category, which represents the Service Category dimension. Ensure you configure the dimension component through the available Component settings.

    B2B data view - components - account dimensions

  8. Select Save and Continue.

Settings

  1. You can optionally define specific settings for the data view:

    • Add segments to the data view.
    • Use a (calculated) metric to define session settings.
  2. Select Save and continue.

Segments

You can prepare one or more B2B specific container-based segments that you can use in your Workspace project.

For example:

  • Accounts with event registration segment.

    B2B use case - segment - accounts registered

  • US accounts with Buying Groups and stage 5 opportunities segment.

    B2B use case - segment - stage 5

Other

You can optionally define other components for your use cases, like calculated metrics, date ranges, or alerts.

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