Identifiers & Traits

How Identifiers & Traits differ from each other in the Attuitive world.

The two core concepts of Attuitive are Identifiers & Traits. On the surface, these two properties share some similiarities but understanding their differences can allow you to drive the most value from the system.

Both properties relate to users and describing them in some form but have different purposes.

Identifiers

Identifiers are properties that can be used to identify your users. These are data points that are generally unique across your users such as an email address or phone number. Each property is an identifier.

The /identify endpoint leverages these properties, first when creating your users and at a later point for identifying them by these values. For example, you can take a known email address and use the /identify endpoint to retrieve the matching user.

Conflicts

There may be some scenarios in which a particular identifier, phoneNumber for example, is not unique across your users. Attuitive allows for this and will not return an error in the event of inserting a second, or greater user with the same phoneNumber value.

Important: individual identifiers do not have to be unique across users!

Whilst unique identifiers are preferential, when calling the /identify endpoint you can provide multiple filter properties. Doing so allows you use a combination of multiple identifier values to find an exact match. Failing this, multiple users may be returned which can be filtered by other means as suited to your purpose.

Traits

Traits are attributes of your users and describe certain things about them. They are often not unique across users and are likely domain specific, i.e. they relate to a data point relevant to the application or industry. For example, an e-commerce brand may hold many details around a customers purchase or browsing behaviours:

{
    "lastPurchaseDate": "13/04/2025",
    "lastOrderNumber": "ODR-123",
    "lastSiteVisit": "15/04/2025"
}

It is these properties that hold value and will derive insights into behaviours, analytics, and patterns that will allow for data-driven decision making.