Customer Attributes and Types

Blueshift creates unified, comprehensive profiles of each customer by aggregating data from across all customer touchpoints. The customer profile contains explicit attributes that are based on the data sent to Blueshift by you, attributes that are derived from the customer data collected, and predictive attributes that are computed using Blueshift’s AI-powered predictive models.

You can use these customer attributes to build precise segments to target a particular audience, in campaign filters, and to personalize your messages using Liquid.

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Customer attributes are also referred to as User attributes in Blueshift.

Note: All of these user fields are case-sensitive and space-sensitive.

Standard (Blueshift Attributes)

Blueshift has a standard set of attributes you can map your data to.

Attribute Definition
email Email address of the user, identifies a user uniquely.
customer_id Customer id for this user in your database, identifies a user uniquely.
firstname User first name (optional)
lastname User last name (optional)
gender User's gender (optional): male, female or unknown.
joined_at Date user joined (optional) in ISO-8601 format
unsubscribed User’s subscription status (optional) boolean. Set to true - if the user has unsubscribed from mailing list.
unsubscribed_at Date when user unsubscribed in ISO-8601 format.
email_hard_bounced Automatically updated when a hard bounce occurs (true or false).
email_spam_reported Automatically updated when a user marks your email as spam via the ISP (true or false).
phone_number User's phone number, including ISD code.  Used for SMS messaging.  (optional)

Standard device attributes

Blueshift also has the following standard device attributes that you can use to track different mobile devices used by a customer. With these attributes you can track user and device level push and in-app message subscription status for each mobile device a user owns. You can see the app installation status for each mobile device a user owns.

Blueshift also derives some device attributes.

Attribute Definition
device_id Mobile device identifiers (mandatory).
device_token Mobile device tokens used for Push messaging.
device_type The type of device. For example, Android.
enable_inapp User’s status for receiving inapp messages. Set to false if the user opts out of receiving inapp messages.
enable_push User’s status for receiving push notifications. Set to false if the user opts out of receiving push notifications.
os_name Mobile device OS. For example, Android or iOS.
os_version Mobile device OS version. For example, iOS 15.
app_name The app on the mobile device.
app_version The version of the app used.
app_status Whether the app is installed or uninstalled.
device_manufacturer The device manufacturer. For example, Apple or Samsung.
ios_idfa The Identifier for Advertisers (IDFA) is a random device identifier assigned by Apple to a user's device. The IDFA is used for tracking and identifying a user (without revealing personal information). You can use this identifier to track data for customized advertising.
ios_idfv The Identifier for Vendors (IDFV) is a code assigned to all apps by one developer and is shared across all apps by that developer on your device. The value of the IDFV is the same for apps from the same developer running on the same device.
advertising_id Device ID provided by Google Play Services. It gives users better controls and provides developers with a simple, standard system to continue to monetize their apps. It enables users to reset their identifier or opt out of personalized ads (formerly known as interest-based ads) within Google Play apps.
firebase_instance_id Firebase Instance ID provides a unique identifier for each app instance and a mechanism to authenticate and authorize actions.
last_activity Most recent time the device was used.
updated_at Most recent time 

Custom Attributes

Non-standard or other custom attributes.

Custom Attribute (create your own) You may pass any other attribute, and it would get saved on the user. Ex: membership_level, loyalty_points, etc.

Derived Attributes

Blueshift can compute certain attributes based on all the data (event, campaign) from a user. At the time of building a segment, you can select these in the segment builder. 

Device attributes

Attribute Definition
last_browser_platform Most recent browser platform used by user (for example, webkit or blink).
last_browser_type Most recent browser used by user (for example, chrome or safari).
last_browser_version Version of browser Most recently used by user.
last_device_id Most recent known device ID from user's mobile app.
last_device_token Most recent device token sent from user's mobile app.
last_device_token_updated_at Time when the device token was last updated.
last_utm_medium The medium the link was used on such as, email, CPC, and so on.
last_utm_source The source of your traffic. For example, Blueshift.
last_visit_at Last known page load event.
session_last_activity_at Last known session date.
unsubscribed_at The time when a user unsubscribed from an email campaign.

Location attributes

Attribute Definition
last_location_city Most recent city for user based on latitude/longitude data.
last_location_country Most recent country for user based on latitude/longitude data.
last_location_country_code Most recent country code (ie +44 or +1) for user.
last_location_geo_delta_updated_at Most recent time the geo delta was updated.
last_location_geo_latitude Last known geo latitude of the user.
last_location_geo_longitude Last known geo longitude of the user.
last_location_geo_updated_at Most recent time the geo was updated.
last_location_state Most recent state for user based on latitude/longitude data.
last_location_timezone Last known timezone for the user.

 Campaign attributes

Attribute Definition
last_campaign_uuid UUID of campaign Most recently received by user.
last_click_at Most recent time a user clicked on a campaign.
last_click_campaign_uuid UUID of campaign on which user Most recently clicked.
last_click_creative_uuid Most recent creative UUID where click occurred.
last_click_experiment_uuid Most recent experiment UUID where click occurred.
last_click_trigger_type Type of trigger where last click occurred (for example, email, sms, and so on).
last_click_trigger_uuid UUID of Most recent trigger where click occurred.
last_creative_uuid Most recent creative a user received.
last_experiment_uuid Most recent experiment sent to a user.
last_open_at Most recent campaign open time.
last_open_campaign_uuid Most recent campaign UUID tied to open.
last_open_creative_uuid Most recent creative UUID tied to open.
last_open_experiment_uuid Most recent experiment UUID tied to open.
last_open_message_uuid Most recent message UUID tied to open.
last_open_trigger_type Most recent trigger type tied to open (for example, email, sms, and so on).
last_open_trigger_uuid Most recent trigger UUID tied to open.
last_purchase_at Date when a user last purchased.  Derived from purchase event
last_trigger_uuid UUID of most recent trigger sent to user.
last_utm_campaign The campaign name. For example, Abandoned Browse.
last_utm_content Optional parameter for additional details for A/B testing and content-targeted ads.
last_utm_medium The medium the link was used on such as, email, CPC, and so on.
last_utm_source The source of your traffic. For example, Blueshift.
last_utm_term Optional parameter suggested for paid search to identify keywords for your ad.
unsubscribed_at The time when a user unsubscribed from an email campaign.

 Lifetime attributes

Attribute Definition
last_purchase_at Date when a user last purchased.  Derived from purchase event
lifetime_revenue Computed and aggregated from purchase event. Requires revenue as an event attribute.
lifetime_orders Computed and aggregated from purchase event. 
lifetime_visits Computed from session data. Each session lasts 30 minutes.
lifetime_(custom goal) Computed from custom event goals.

Predictive attributes

Blueshift also computes Predictive Scores and affinities that can then be used in segments and campaign filters.

Attribute Definition
Predictive Scores Derived from predictive models (engagement, purchase intent/conversion, and retention)
Category Affinity Based on user interactions with your content/catalog in the last 28 days, computed daily.  May contain category affinities
Top Hour Optimal engagement time based on session data (events and campaign engagement) in the last 28 days, computed daily
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