User Traits 

User segmentation is a powerful feature within the ReBid CDP that allows you to categorize and target users based on specific traits and conditions. With user segmentation, you can create tailored experiences, perform analyses, and execute targeted marketing strategies. The CDP enables you to define segments using various trait types, including Session traits, PII (Personally Identifiable Information) traits, and Public traits. You can also apply advanced conditions to refine your segments for precise targeting.

To create user segments in the CDP, follow these steps:

1. Select the appropriate Trait Type. You can select from these types: Stats, PII traits, Public traits, Private traits, and others. 

2. Once you've chosen the trait type, you can set specific conditions based on user attributes. These conditions allow you to filter users based on their traits. For example, you can filter users based on their first-seen date, last-seen date, total number of sessions, session duration, and more.

3.Specify the frequency and time duration for the event execution. This helps you target users who have performed specific actions within a certain time frame.

4. Optionally, you can add event attribute filters to further narrow down your segment. These filters allow you to focus on users who have performed specific actions with certain attributes.

5. Add aggregation to event attributes and set filters for aggregated values. You can also create nested conditions to refine your segment based on complex criteria.

6. Combine multiple filters using AND/OR logic to create sophisticated segment conditions that reflect various user behaviors.

8. Optionally, add global exclusion filters to exclude certain users from your segment based on specific criteria by using the NOT logic. 

9. As you build your segment conditions, they are transformed into statements. Each statement includes the conditions you've set, and you can easily edit them as needed.

Trait Types and Conditions

The CDP offers various trait types and conditions for user segmentation:

1. Stats: Auto-populated attributes related to user sessions, such as first seen date, last seen date, number of sessions, session duration, last page visited, etc.

2. Private Traits: User device-related attributes, including browser, language, and user agent.

3. PII Traits: Personally Identifiable Information attributes, such as first name, last name, email, phone number, social media accounts (Facebook, Twitter, WhatsApp), and birth date.

4. Public Traits: Attributes related to user location and IP, including IP address, user time zone, city, state, and country.

User Behavior

ReBid CDP enables you to create targeted audiences by leveraging user event actions and their associated properties. Events represent user activities, such as App Open or Product Purchase, and can include event attributes like platform name, product category, and product price. You can follow these steps to define your audience:

1. Choose whether you want to include users who have performed a specific action or those who haven't performed it.

2. Pick the event that you want to focus on. You can select one or multiple events. Note that when multiple events are selected, options for adding properties and aggregations become inactive.

3. Set Event Frequency. You can choose options like "At least," "At most," "Exactly," or "Between" (specifying two values).

4. Specify the Time Period  within which the event actions should have taken place. You can select options like "in the last (n) (days/weeks/months)," "Between" (using calendar widgets), specific dates, or relative time frames like "Today," "Yesterday," etc.

5. If the event has associated properties, you can add filters based on these properties using the "+property/+attribute" button. This allows you to narrow down your audience even further.

6. Utilize aggregation operations like SUM, AVG, MIN, MAX, and MEDIAN on numeric event property values. This is helpful when you want to segment users based on aggregated data.

7. In cases where the order of events matters, you can add successive action or inaction conditions. This helps you segment users based on sequences of events and inactivity timelines.

• Successive Action: Define conditions for users who performed a sequence of events.

• Inaction: Specify conditions for users who performed an initial event but didn't perform a subsequent event within a certain timeframe.

8. Refine your audience further by adding nested filters with the ‘+nested filter’ button. You can connect filters with AND/OR/NOT logic.

9. Add additional filters that connect to the previous parent filter with the ‘+filter’ button. These filters can further refine your audience based on various conditions.

10. Apply a global exclusion filter using the ‘Exclude users’ button. This helps you exclude specific users from your audience.

11. As you complete each segment condition, it will be transformed into a statement with an edit icon for further adjustments.

Dropdown Values Reference:

1. User Action:

• Performed

• Did not perform

2. Event:

• Multi-select dropdown with "Select All" option

3. Frequency:

• At least

• At most

• Exactly

• Between (2 values)

4. Time Period:

• Various options for specifying time frames

5. Value Operator (String):

• Various options for string-based comparisons

6. Value Operator (Numeric):

• Various options for numeric comparisons

7. Value Operator (Date):

• Various options for date-based comparisons

8. Aggregation Operations:

• SUM

• AVG

• MIN

• MAX

• MEDIAN

9. Aggregation Operators (Numeric):

• Various options for numeric comparisons

Predictive Segments offer a comprehensive approach to segmentation, incorporating both RFM (Recency, Frequency, Monetary) and VBS (Value, Behavior, Segmentation) segments. Users can effortlessly switch between Segmentation models by utilizing a dropdown selection (RFM/VBS). They can then assign a distinct segment name (e.g., Loyalists, Champions) and set a specific date range to refine their segmentation. The same rules apply for nested filters, outer filters, and exclusion criteria, ensuring a seamless experience across the board.

Custom Segments

Custom Segments are a powerful feature within the CDP platform that enable you to define specialized groups of data based on specific criteria. These criteria can encompass a variety of factors such as user behavior, demographics, interactions, and more. By creating custom segments, you can precisely tailor your analysis and actions, allowing for more targeted and effective decision-making.

Navigate to the Custom Segment section and then choose the specific custom segment you wish to establish a rule. Underneath the dropdown menu for custom segment selection, you will find the description corresponding to the custom segment you have chosen. Nested filters, outer filters, and exclusions operate in a similar manner.