Derived attributes are customer attributes that are generated or calculated by Blueshift based on other customer attributes and event data. These derived attributes are available on the Customer Profile and are refreshed at regular intervals. At the time of building a segment, you can select these in the segment builder. 

Standard derived attributes

Blueshift can compute certain attributes based on all the data (event, campaign) from a customer. 

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.
This attribute is updated when Blueshift receives an event for the customer and is updated once during a user session.
The attribute is updated for a click event only if the click generates a page load event or any other event.
last_click_at Last known click event.
last_open_at Last known open event.
Together with last_click_at, this attribute helps you to understand when a customer last engaged with your campaigns.
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.

Custom derived attributes

Using the custom derived attributes feature, you can compute complex attributes like counts, min and max values, averages, percentages, and so on.

For example, you can calculate the total number of orders for customers, find out the last time a person visited a physical store to purchase an item, the unique visitor count for a store and so on. You can also add conditions using event attributes and fine tune the derived attributes. For example, the number of shows watched using the app or the favorite brand of a customer with high lifetime value.

You can then use these derived attributes to create highly focused segments or as filters in campaigns.

 Note

Contact your CSM to explore and implement any use cases and to set up custom derived attributes.

Functions

You can use the following functions to calculate a derived attribute in Blueshift.

Count

The count for a particular event over a specific period of time.

For example, the number of comedy shows watched. This count is derived from the custom event playback_complete or playback_paused using the event attributes show_name and show_category. This count along with counts of other categories of shows can help you to determine which shows to promote to the customer.

Other examples:

  • Number of movies watched in the last year
  • Items purchased within past 90 days
  • Items returned within past 90 days
  • Page views for a particular item within past 7 days

Sum

The computed sum for a particular event over a specific period of time.

For example, the lifetime revenue for a customer. This sum is derived from the revenue attribute that is passed in the order event. You can use this to promote a loyalty program. We can also add conditions to identify favorite brands which will enable you to promote items from the same brand or promote a similar new brand.

Other examples:

  • The total revenue from orders in the past 7 days
  • The total viewing time in the past 30 days
  • Total visits in the past 7 days.
  • Total orders in the past 30 days.

Average

The average value for a particular event over a specific period of time.

For example, the average number of minutes watched for a particular show in the past 30 days. This average is derived from the custom event playback_complete or playback_paused using the event attribute minutes_watched. We can also add conditions to identify the channel so that only shows watched through the app will be considered.

Other examples:

  • Average order value (Revenue/No. of orders) in the past 90 days
  • Average playback time per session

Max/Min

The maximum or minimum value for an attribute over a specific period of time.

For example, the maximum order value for the last 30 days. This amount  is derived from the revenue attribute that is passed in the order event. You can use this value to offer a discount to customers who have spent more than a certain amount.

Other examples:

  • The maximum order quantity for a particular item
  • The minimum watch time for a show

First/Last

The first or the last occurrence of an event.

For example, Last time media viewed. This time is derived from the custom event playback_complete or playback_paused. You can use this to encourage or incentivize customers who have not visited the app in a while to come back. Another way this could be used is to add conditions to identify the channel so that you can encourage customers who are using the website to use the app instead.

Other examples:

  • First purchase date
  • Last purchase date
  • First time customer purchased In Store
  • Last time customer purchased In Store
  • First time customer purchased in eCommerce store
  • Last time customer purchased in eCommerce store
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