Dataset queries
Find ready-to-use SQL query examples for analyzing the account, person, buying group, and journey data that Adobe Journey Optimizer B2B Edition exports to Adobe Experience Platform. To report on accounts, buying groups, email engagement, and journey activity, run the queries in Query Service.
For descriptions of the datasets and fields used in these queries, see Exported datasets.
Prerequisites prerequisites
Before you run any query on this page, make sure that you have the following:
- Access to Query Service: You must have access to Query Service in your Experience Platform sandbox.
- Available datasets: The queries target the exported Journey Optimizer B2B Edition datasets. In your sandbox, go to Datasets and verify that the datasets exist and contain data.
- Schema field values: Make sure that the fields in your queries have values in the corresponding schema. Empty fields return no results and do not produce errors.
account_table and person_activity_table. Replace each table name with the name of the corresponding dataset in your sandbox. If a dataset name contains hyphens, enclose it in double quotes. Replace placeholder values, such as Example Company and PASTE_COMPLETE_JOURNEY_ID_HERE, with values from your environment.Run a query run
To run any example on this page:
- In Experience Platform, select Query Service > Queries.
- Paste the example into the query editor, then replace the table names and placeholder values.
- Select Run.
The examples that filter by date use the last 30 days. To change the time range, edit the INTERVAL '30' DAY value.
Choose a query
Use the following table to choose a query for your reporting task.
Account and buying group queries
Use these queries to review the accounts, buying groups, and people available for reporting.
Review account details account-details
Review account names, industries, locations, and company sizes to understand the accounts available for reporting.
SELECT
a._id AS accountID,
a.accountName,
a.industry,
a.country,
a.numberOfEmployees
FROM account_table a
WHERE a.isDeleted = FALSE
ORDER BY a.accountName
LIMIT 100;
Compare buying group engagement buying-group-engagement
Compare buying groups by recorded engagement score, alongside completeness and solution interest.
SELECT
bg._id AS buyingGroupID,
bg.buyingGroupName,
bg.engagementScore,
bg.completenessScore,
bg.solutionInterest,
bg.buyingGroupStatus
FROM buying_group_table bg
WHERE bg.isDeleted = FALSE
ORDER BY bg.engagementScore DESC NULLS LAST, bg.buyingGroupName
LIMIT 100;
Find people in an account account-people
Find the people and job titles associated with an account to understand its contacts. Replace Example Company with an account name from your sandbox.
SELECT DISTINCT
a._id AS accountID,
a.accountName,
p._id AS personID,
p.firstName,
p.lastName,
p.email,
p.jobTitle
FROM account_member_table m
JOIN account_table a ON m.accountID = a._id
JOIN person_table p ON m.personID = p._id
WHERE m.isDeleted = FALSE
AND a.isDeleted = FALSE
AND p.isDeleted = FALSE
AND a.accountName = 'Example Company'
ORDER BY p.lastName, p.firstName
LIMIT 100;
Review buying group status changes buying-group-status-changes
Review buying group status changes in the last 30 days to understand how groups change over time.
SELECT
bg._id AS buyingGroupID,
bg.buyingGroupName,
e.timestamp AS changedAt,
e.newStatus
FROM buying_group_event_table e
JOIN buying_group_table bg ON e.buyingGroupID = bg._id
WHERE bg.isDeleted = FALSE
AND e.eventType = 'buyingGroup.changeStatus'
AND e.timestamp >= CURRENT_TIMESTAMP - INTERVAL '30' DAY
AND e.timestamp < CURRENT_TIMESTAMP
ORDER BY e.timestamp DESC
LIMIT 100;
Person engagement queries
Use these queries to review email engagement and other recorded person activity.
Find people who clicked an email email-clicks
To review recent email engagement, identify people with recorded email clicks in the last 30 days.
SELECT DISTINCT
p._id AS personID,
p.firstName,
p.lastName,
p.email
FROM person_activity_table e
JOIN person_table p ON e.personID = p._id
WHERE e.isDeleted = FALSE
AND p.isDeleted = FALSE
AND e.eventType = 'directMarketing.emailClicked'
AND e.timestamp >= CURRENT_TIMESTAMP - INTERVAL '30' DAY
AND e.timestamp < CURRENT_TIMESTAMP
ORDER BY p.lastName, p.firstName
LIMIT 100;
Compare recent person activity person-activity
Compare recorded activity types and the number of people involved to understand recent engagement.
SELECT
e.eventType,
COUNT(*) AS recordedRows,
COUNT(DISTINCT e.personID) AS distinctPeople
FROM person_activity_table e
WHERE e.isDeleted = FALSE
AND e.personID IS NOT NULL
AND e.personID <> ''
AND e.timestamp >= CURRENT_TIMESTAMP - INTERVAL '30' DAY
AND e.timestamp < CURRENT_TIMESTAMP
GROUP BY e.eventType
ORDER BY recordedRows DESC
LIMIT 100;
Account journey queries
Use these queries to analyze account journeys. Replace PASTE_COMPLETE_JOURNEY_ID_HERE with the _id value of the account journey, and PASTE_COMPLETE_ACCOUNT_ID_HERE with the _id value of the account.
Compare account counts by journey account-journey-counts
Compare account journeys by status and recorded membership count to see which journeys have the largest account populations.
SELECT
j._id AS journeyID,
j.accountJourneyName,
j.accountJourneyStatus,
COUNT(DISTINCT m.accountID) AS accountsWithRecordedMembership
FROM account_journey_table j
LEFT JOIN account_journey_member_table m
ON m.journeyID = j._id
AND m.isDeleted = FALSE
AND m.accountID <> ''
WHERE j.isDeleted = FALSE
GROUP BY j._id, j.accountJourneyName, j.accountJourneyStatus
ORDER BY accountsWithRecordedMembership DESC, j.accountJourneyName
LIMIT 100;
List accounts in a journey journey-accounts
Review the accounts associated with a particular journey, including their industries and countries.
SELECT DISTINCT
a._id AS accountID,
a.accountName,
a.industry,
a.country
FROM account_journey_member_table m
JOIN account_table a ON m.accountID = a._id
WHERE m.isDeleted = FALSE
AND a.isDeleted = FALSE
AND m.journeyID = 'PASTE_COMPLETE_JOURNEY_ID_HERE'
ORDER BY a.accountName, accountID
LIMIT 100;
Track daily account activity account-daily-activity
Track daily account additions, removals, and step changes to understand activity in a journey over the last 30 days.
SELECT
CAST(e.timestamp AS DATE) AS activityDate,
e.eventType,
COUNT(*) AS recordedRows,
COUNT(DISTINCT e.accountID) AS distinctAccounts
FROM account_activity_table e
WHERE e.journeyID = 'PASTE_COMPLETE_JOURNEY_ID_HERE'
AND e.accountID IS NOT NULL
AND e.accountID <> ''
AND e.eventType IN (
'account.addAccountToJourney',
'account.removeAccountFromJourney',
'account.changeAccountJourneyNode'
)
AND e.timestamp >= CURRENT_TIMESTAMP - INTERVAL '30' DAY
AND e.timestamp < CURRENT_TIMESTAMP
GROUP BY CAST(e.timestamp AS DATE), e.eventType
ORDER BY activityDate DESC, e.eventType
LIMIT 100;
Review an account journey timeline account-timeline
Investigate the recent journey history of an account by reviewing its recorded events and journey steps.
SELECT
e.timestamp AS activityAt,
e.eventType,
e.journeyNodeID,
n.nodeType,
e.previousJourneyNodeID,
e.buyingGroupID
FROM account_activity_table e
LEFT JOIN account_journey_node_table n
ON e.journeyNodeID = n._id
AND e.journeyID = n.accountJourneyID
AND n.isDeleted = FALSE
WHERE e.accountID = 'PASTE_COMPLETE_ACCOUNT_ID_HERE'
AND e.journeyID = 'PASTE_COMPLETE_JOURNEY_ID_HERE'
AND e.timestamp >= CURRENT_TIMESTAMP - INTERVAL '30' DAY
AND e.timestamp < CURRENT_TIMESTAMP
ORDER BY e.timestamp DESC
LIMIT 100;
Person journey queries
Use these queries to analyze person journeys. Replace PASTE_COMPLETE_JOURNEY_ID_HERE with the _id value of the person journey, and PASTE_COMPLETE_PERSON_ID_HERE with the _id value of the person.
Compare person counts by journey person-journey-counts
Compare person journeys by recorded membership count, status, and dates to understand their size and lifecycle.
SELECT
j._id AS journeyID,
j.personJourneyName,
j.personJourneyStatus,
j.startDate,
j.endDate,
COUNT(DISTINCT m.personID) AS peopleWithRecordedMembership
FROM person_journey_table j
LEFT JOIN person_journey_member_table m
ON m.journeyID = j._id
AND m.isDeleted = FALSE
AND m.personID <> ''
WHERE j.isDeleted = FALSE
GROUP BY
j._id,
j.personJourneyName,
j.personJourneyStatus,
j.startDate,
j.endDate
ORDER BY peopleWithRecordedMembership DESC, j.personJourneyName
LIMIT 100;
List people in a journey journey-people
Review who is associated with a journey, when they last entered, and how often they have entered.
SELECT DISTINCT
m.personID,
p.firstName,
p.lastName,
p.email,
m.membershipDate,
m.lastEntryDate,
m.entryCount,
m.reentryOpensAt,
m.journeyNodeID
FROM person_journey_member_table m
LEFT JOIN person_table p
ON m.personID = p._id
AND p.isDeleted = FALSE
WHERE m.isDeleted = FALSE
AND m.personID IS NOT NULL
AND m.personID <> ''
AND m.journeyID = 'PASTE_COMPLETE_JOURNEY_ID_HERE'
ORDER BY m.lastEntryDate DESC NULLS LAST, m.personID
LIMIT 100;
Compare person counts by step person-step-counts
See how people are distributed across the steps recorded in their journey memberships.
SELECT
m.journeyNodeID,
n.nodeType,
COUNT(DISTINCT m.personID) AS peopleWithRecordedStep
FROM person_journey_member_table m
LEFT JOIN person_journey_node_table n
ON m.journeyNodeID = n._id
AND m.journeyID = n.personJourneyID
AND n.isDeleted = FALSE
WHERE m.isDeleted = FALSE
AND m.personID IS NOT NULL
AND m.personID <> ''
AND m.journeyID = 'PASTE_COMPLETE_JOURNEY_ID_HERE'
GROUP BY m.journeyNodeID, n.nodeType
ORDER BY peopleWithRecordedStep DESC, m.journeyNodeID
LIMIT 100;
Track recent journey activity person-journey-activity
Compare recorded journey starts, ends, and transitions to understand person activity in a journey over the last 30 days.
SELECT
e.eventType,
COUNT(*) AS recordedRows,
COUNT(DISTINCT e.personID) AS distinctPeople
FROM person_activity_table e
WHERE e.isDeleted = FALSE
AND e.journeyID = 'PASTE_COMPLETE_JOURNEY_ID_HERE'
AND e.personID IS NOT NULL
AND e.personID <> ''
AND e.eventType IN (
'person.journeyAdd',
'person.journeyRemove',
'person.journeyStart',
'person.journeyEnd',
'person.journeyNodeTransition',
'person.journeySplitNode'
)
AND e.timestamp >= CURRENT_TIMESTAMP - INTERVAL '30' DAY
AND e.timestamp < CURRENT_TIMESTAMP
GROUP BY e.eventType
ORDER BY recordedRows DESC, e.eventType
LIMIT 100;
Review a person journey timeline person-timeline
Investigate the recent journey history of a person, including step transitions, split choices, and journey attributed profile updates.
SELECT
e.timestamp AS activityAt,
e.eventType,
e.journeyNodeID,
e.previousJourneyNodeID,
e.newJourneyNodeID,
e.journeyChoiceNumber,
e.journeyEntryCount,
e.attributeName,
e.attributeOldValue,
e.attributeNewValue
FROM person_activity_table e
WHERE e.isDeleted = FALSE
AND e.personID = 'PASTE_COMPLETE_PERSON_ID_HERE'
AND e.journeyID = 'PASTE_COMPLETE_JOURNEY_ID_HERE'
AND e.timestamp >= CURRENT_TIMESTAMP - INTERVAL '30' DAY
AND e.timestamp < CURRENT_TIMESTAMP
ORDER BY e.timestamp DESC
LIMIT 100;