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. |
last_user_open_at | Timestamp of last open by user. This exclude open by prefetch or bots |
last_user_click_at | Timestamp of last click by user. This excludes any bot clicks |
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. |
Note
Blueshift automatically captures the first and last timestamp for all goal events in the customer profile.
For any goal event, such as a subscription or trial, corresponding attributes will appear in the format <goal_event_name>_first_occurred_at and <goal_event_name>_last_occurred_at.
Example: If the goal event is paid_subscription_started, the attributes paid_subscription_started_first_occurred_at and paid_subscription_started_last_occurred_at will reflect the initial subscription date and the most recent upgrade or renewal date.
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
Comments
0 comments