User Attributes | Kevel Audience

User Attributes

User Attributes hold information about a specific user. These attributes can be derived from multiple data sources and can be used as Activated Parameters or to enable Segmentation.

Audience provides an expansive collection of Default Attributes that apply to a broad set of general use cases.

For more granular control, it is possible to create Custom Attributes that are derived from real-time events. In addition, it is also possible to import attributes from the Offline User Import and to automatically generate Predictive Attributes by configuring Predictions.

Customers can send any user attribute relevant to their business, using any value they choose. However, for Demographic Data, we recommend following a specific schema to ensure a better navigational experience in Audience.

Attribute Naming

While attribute values are unrestricted, attribute names must be valid identifiers: they have to start with a letter or an underscore and may otherwise contain only letters, numbers, underscores (_) and dots (.). See Attribute Name Requirements for details and examples.

Custom Attributes

Custom Attributes are generated by processing the user's events. Configuring a new attribute requires one filter rule to identify which event to consider, an extraction strategy to identify what data to extract from the events, and an aggregation strategy, to define how to make the information available in the user profile. Custom Attributes will typically be available in the Segment Builder UI within 4 hours after creation.

Definition

Custom User Attribute definition is done through the dashboard attribute builder which provides an easy way to create complex event filter rules and specify the attribute extraction strategy visually using information regarding existing events. For more advanced use cases, it is possible to write rules manually.

Aggregation

The aggregation strategy to use when combining the extracted value with existing information. Some of the aggregations allow specifying the value that is extracted from the event, in such cases a field selection helper is available.

Round Timestamp to the Start of the Day

When creating a User attribute, it is common to look for user activity patterns at a day granularity. For example, "List of days the user visited the website". Such an attribute does not care for how many times the user visited the website in a single day, but rather on which days the user visited the site. This can be achieved with a "Unique list concatenation" aggregation and extracting the Timestamp field while enabling the "Round timestamp to the start of the day" option. The result is a list of timestamps for the first moment of each day, hence, avoiding duplicate entries for the same day.

Default Value

The default value to return if the attribute does not exists for a given user.

Attributes with no default value require special care when creating segment rules, since they can be undefined. You can check for undefined values in segment rules using the isDefined function.

Period

The period (in days) of past events to consider for the creation of the attribute. For example, to create a segment of "users who purchased shampoo at least 3 times in the last 7 days," you should define the period as 7 days.

Considerations

Attributes should be viewed as data aggregators, containing the necessary information for later filtering by segmentation rules.

Once the attribute is created, incoming tracking events will immediately populate the attribute. At the same time, we start processing events for up to 100 days and the whole order history to populate the attribute with historical data.

More events and orders in the system result in a longer time to complete the historical processing. If the whole history is irrelevant for an attribute, e.g., "people who purchased shampoo in the last 7 days", we recommend defining a period in the attribute definition so that we can exclude older, irrelevant events.

Attributes begin processing a few minutes after they are defined. If a new one is created, this delay is reset, allowing you to define multiple attributes and allowing Audience to compute them together. Once processing begins, new attributes are put on hold until the previous ones are computed. Additional attributes will be processed after the previous ones are complete.

Predictive Attributes

Predictive User Attributes are automatically generated and continuously updated by Predictions and require no configuration after the Prediction is created. Note that for the Default Predictions the created attributes are readily available for usage and require no interaction with the Prediction itself.

Event Predictions

The Event Predictions generate user attributes with the name pattern predictions.<event-prediction-id>.<prediction-interval>. These attributes can be used to segment users with a certain likelihood of triggering an event which follows the event filter of the Event Prediction in the future. In the Segment Builder, these attributes are available under Predictions > Event Predictions.

Default Predictions

In this section, you can find an overview of all the predictive attributes that are generated by our Default Predictions.

Next Purchase

note

The category-specific attribute names go through a normalization process in order to become valid identifiers to use inside segmentation rules.

Churn Factor

The churn factor enables identifying the current state of a customer's predicted purchase cycle. It is used as a factor of the distance to the predicted purchase interval. It is calculated as (<current-timestamp> - <last-purchase-timestamp>) / <predicted-interval-between-purchases>. It can assume any number larger than or equal to 0.

Purchase Cycle

RFM

The RFM attributes classify users in 0-10 buckets based on their Recency, Frequency and Monetary Value 10-quantiles.

Lifetime Value

Likelihood to Buy

Likelihood to Buy a Category

These attributes are available along a dedicated model to predict the likelihood to buy a product from a single or a set of categories. These attributes are not generated by default, as the strategies adopted for training the models need to be configured on a per-customer basis. To create segments using this strategy, contact your Customer Success Manager, and we will work with you to set it up.

Default Attributes

In addition to the attributes you can import via Offline User Import, Kevel Audience automatically generates a series of attributes per event for a user.

Accumulators and Temporal Attributes per Event Type

Interaction Type

Orders

Email and Campaigns

Geo Location

Devices

Activations

Demographic Attributes

The Audience UI is prepared to receive a set of demographic user attributes. Note that Audience does not generate these attributes, they have to be explicitly sent.