Blueshift can store various types of user data - explicit, derived and predictive. 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 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 |
| facebook_id | User’s Facebook id (optional) |
| 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) |
| device_ids | Mobile device identifiers (optional) |
| device_tokens | Mobile device tokens used for Push messaging (optional) |
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.
| Attribute | Definition |
| 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 |
| llifetime_(custom goal) | Computed from custom event goals |
| unsubscribed_at | The time when a user unsubscribed from an email campaign |
| session_last_activity_at | Last known session date |
| last_purchase_at | Date when a user last purchased. Derived from purchase event |
| last_visit_at | Last known pageload event |
| last_sent_at | Most recent sent campaign time |
| last_open_at | Most recent campaign open time |
| last_device_token | Most recent device token sent from your mobile app |
| last_location_geo_longitude | Last known geo longitude of the user |
| last_location_geo_latitude | Last known geo latitude of the user |
| last_location_timezone | Last known timezone for the user |
But you don't have to remember all these attributes when you create a segment. At the time of building a segment, you can select these in the segment builder.
Predictive Scores
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 |
Comments
0 comments