Customer properties
Customer properties (often referred to as customer attributes, profile attributes, or user properties) are distinct pieces of data or characteristics associated with an individual customer or user profile. These properties collectively build a comprehensive digital fingerprint for each person, describing who they are, what they've done, and what their preferences might be.
Customer properties can represent a wide array of information, categorized broadly as:
Demographic Properties:
Definition: Basic personal details that describes the customer.
Examples: Age, Gender, Income Level, Education, Occupation, Marital Status, Family Size, Geographic Location (City, State, Country).
Contact Information Properties:
Definition: Details needed to communicate with the customer.
Examples: Email Address, Phone Number, Mailing Address, Social Media Handles.
Firmographic Properties (for B2B):
Definition: Characteristics describing the company a B2B customer works for.
Examples: Company Name, Industry, Company Size (employees, revenue), Job Title, Department.
Psychographic & Preference Properties:
Definition: Insights into a customer's lifestyle, interests, values, and expressed preferences.
Examples: Hobbies, Interests (e.g., "outdoor activities," "tech gadgets"), Communication Preferences (e.g., "email only," "SMS opt-in"), Brand Loyalty Status, Product Preferences (e.g., "vegan products," "organic only").
Derived/Calculated Properties:
Definition: Attributes that are not directly collected but are calculated or inferred from other raw data.
Examples: Customer Lifetime Value (CLTV), Lead Score, Churn Risk Score, Predicted Next Best Action, Segment Membership (e.g., "High-Value Customer," "At-Risk Customer").
Usage
Customer properties are the backbone of modern, personalized marketing strategies and can be used in the following:
Segmentation: They are the primary criteria used to create distinct customer segments, allowing marketers to group individuals with similar characteristics or behaviours.
Personalisation: They enable hyper-personalization of marketing messages, content, product recommendations, and website experiences. Knowing a customer's past purchases or interests allows for highly relevant dynamic content.
Customer Journey Orchestration: They provide the necessary context to guide customers through tailored, automated journeys, triggering specific actions or communications based on changes in their properties (e.g., "if CLTV drops below X, send win-back email").
Targeted Advertising: They inform audience targeting for paid advertising campaigns, ensuring ads are served to the most relevant prospects or existing customers.
Analytics & Insights: Aggregating and analysing customer properties provides deep insights into customer cohorts, behavioural trends, and overall customer base health.
Lead Scoring & Qualification: Assigning scores to leads based on their properties (e.g., company size, job title, website activity) helps sales teams prioritize efforts.
Steps to create customer properties
Perform the following steps to create customer properties.
Navigate to > Data pipeline > Customer Properties
Name of the property: Enter the name for your customer property. This name will be used in payload.
Display name of the property: Enter the display name for your property. This name is to identify your property.
Data type: Declare the data type for your customer property. Check data types available in the CDP here.
User Identifier: Select YES if you want to make this property as user identifier.
Edit Customer Properties
In the existing customer properties you can only edit the display name of your customer property by navigating to Data pipeline > Customer property
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