Adobe Experience Platform consente di acquisire dati da Adobe Target utilizzando i campi Experience Data Model (XDM) per creare set di dati da utilizzare con Query Service. Poiché Adobe Target è progettato per personalizzare i contenuti e personalizzare le esperienze utente, le query eseguite su questi set di dati consentono di ottenere informazioni altamente personalizzate e mirate analizzando le attività utente tramite SQL.
Questo documento fornisce una serie di query SQL di esempio che illustrano casi d’uso comuni in base ai comportamenti e alle caratteristiche dei clienti.
Per ciascuno dei seguenti casi d’uso, come modello da personalizzare viene fornito un esempio di query SQL con parametri. Fornisci i parametri ovunque ti trovi { }
negli esempi SQL che si desidera valutare.
Nella tabella seguente sono elencati i campi di Target comuni e i campi XDM corrispondenti a cui vengono mappati.
L'uso di [ ]
all’interno del campo XDM indica un array.
Nome campo di destinazione | Nome campo XDM | Note |
---|---|---|
mboxName |
_experience.target.mboxname |
N/D |
Attività ID | _experience.target.activities.activityID |
N/D |
ID esperienza | _experience.target.activities[].activityEvents[]._experience.target.activity.activityevent.context.experienceID |
N/D |
ID segmento | _experience.target.activities[].activityEvents[].segmentEvents[].segmentID._id |
N/D |
Ambito evento | _experience.target.activities[].activityEvents[].eventScope |
Questo campo tiene traccia dei nuovi visitatori e delle nuove visite. |
ID passaggio | _experience.target.activities[].activityEvents[]._experience.target.activity.activityevent.context.stepID |
Questo campo è un ID passaggio personalizzato per Adobe Campaign. |
Totale prezzo | commerce.order.priceTotal | N/D |
Il nome di un set di dati creato automaticamente utilizzando i dati di Target è "Adobe Target Experience Events". Quando utilizzi questo set di dati con le query, utilizza il nome adobe_target_experience_events
.
Analizzando le attività degli utenti, puoi personalizzare il contenuto per un pubblico specifico e testarne diverse versioni per una singola entità. Inoltre, analizzando una specifica attività in un determinato periodo di tempo o per singoli utenti, le prestazioni di ciascuna attività possono essere comprese più chiaramente. I risultati di questa analisi combinata possono essere utilizzati per comprendere le prestazioni di ogni singola attività.
I seguenti casi di utilizzo di personalizzazione vengono creati utilizzando i dati di Adobe Target e si concentrano sulle attività degli utenti per ottenere informazioni preziose sul comportamento dei clienti rispetto alle applicazioni aziendali.
Questa guida illustra i seguenti concetti chiave attraverso gli esempi di casi d’uso:
SELECT
Hour,
ActivityID,
COUNT(ActivityID) AS Instances
FROM
(
SELECT
date_format(from_utc_timestamp(timestamp, 'America/New_York'), 'yyyy-MM-dd HH') AS Hour,
EXPLODE(_experience.target.activities.activityID) AS ActivityID
FROM adobe_target_experience_events
WHERE TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}') AND
_experience.target.activities IS NOT NULL
)
GROUP BY Hour, ActivityID
ORDER BY Hour DESC, Instances DESC
LIMIT 24
SELECT
date_format(from_utc_timestamp(timestamp, 'America/New_York'), 'yyyy-MM-dd HH') AS Hour,
_experience.target.activities.activityID AS ActivityID,
COUNT(ActivityID) AS Instances
FROM adobe_target_experience_events
WHERE
array_contains( _experience.target.activities.activityID, {Activity ID} ) AND
TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}') AND
_experience.target.activities IS NOT NULL
GROUP BY Hour, ActivityID
ORDER BY Hour DESC
LIMIT 24
SELECT
Day,
Activities.activityID,
ExperienceID,
COUNT(ExperienceID) AS Instances
FROM
(
SELECT
Day,
Activities,
EXPLODE(Activities.activityEvents._experience.target.activity.activityevent.context.experienceID) AS ExperienceID
FROM
(
SELECT
date_format(from_utc_timestamp(timestamp, 'America/New_York'), 'yyyy-MM-dd') AS Day,
EXPLODE(_experience.target.activities) AS Activities
FROM adobe_target_experience_events
WHERE
TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}') AND
_experience.target.activities IS NOT NULL
)
WHERE Activities.activityID = {activity_id}
)
GROUP BY Day, Activities.activityID, ExperienceID
ORDER BY Day DESC, Instances DESC
LIMIT 20
SELECT
Day,
Activities.activityID,
ExperienceID,
COUNT(ExperienceID) AS Instances
FROM
(
SELECT
Day,
Activities,
EXPLODE(Activities.activityEvents._experience.target.activity.activityevent.context.experienceID) AS ExperienceID
FROM
(
SELECT
date_format(from_utc_timestamp(timestamp, 'America/New_York'), 'yyyy-MM-dd') AS Day,
EXPLODE(_experience.target.activities) AS Activities
FROM adobe_target_experience_events
WHERE
TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}') AND
_experience.target.activities IS NOT NULL
)
WHERE Activities.activityID = {activity_id}
)
GROUP BY Day, Activities.activityID, ExperienceID
ORDER BY Day DESC, Instances DESC
LIMIT 20
SELECT
Day,
Activities.activityID,
ExperienceID,
COUNT(ExperienceID) AS Instances
FROM
(
SELECT
Day,
Activities,
EXPLODE(Activities.activityEvents._experience.target.activity.activityevent.context.experienceID) AS ExperienceID
FROM
(
SELECT
date_format(from_utc_timestamp(timestamp, 'America/New_York'), 'yyyy-MM-dd') AS Day,
EXPLODE(_experience.target.activities) AS Activities
FROM adobe_target_experience_events
WHERE
TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}') AND
_experience.target.activities IS NOT NULL
)
WHERE Activities.activityID = {activity_id}
)
GROUP BY Day, Activities.activityID, ExperienceID
ORDER BY Day DESC, Instances DESC
LIMIT 20
SELECT
Day,
Activities.activityID,
ExperienceID,
SegmentID._id,
SUM(CASE WHEN ActivityEvent.eventScope = 'visitor' THEN 1 END) as Visitors,
SUM(CASE WHEN ActivityEvent.eventScope = 'visit' THEN 1 END) as Visits,
SUM(CASE WHEN ActivityEvent.eventScope = 'impression' THEN 1 END) as Impressions
FROM
(
SELECT
Day,
Activities,
ActivityEvent,
ActivityEvent._experience.target.activity.activityevent.context.experienceID AS ExperienceID,
EXPLODE(ActivityEvent.segmentEvents.segmentID) AS SegmentID
FROM
(
SELECT
Day,
Activities,
EXPLODE(Activities.activityEvents) AS ActivityEvent
FROM
(
SELECT
date_format(from_utc_timestamp(timestamp, 'America/New_York'), 'yyyy-MM-dd') AS Day,
EXPLODE(_experience.target.activities) AS Activities
FROM adobe_target_experience_events
WHERE
TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}') AND
_experience.target.activities IS NOT NULL
LIMIT 1000000
)
LIMIT 1000000
)
LIMIT 1000000
)
GROUP BY Day, Activities.activityID, ExperienceID, SegmentID._id
ORDER BY Day DESC, Activities.activityID, ExperienceID ASC, SegmentID._id ASC, Visitors DESC
LIMIT 20
SELECT
_experience.target.mboxname,
COUNT(timestamp) AS records
FROM
adobe_target_experience_events
WHERE
TIMESTAMP = to_timestamp('{TARGET_YEAR}-{TARGET_MONTH}-{TARGET_DAY}')
GROUP BY _experience.target.mboxname ORDER BY records DESC
LIMIT 100