---
title: "Default Attributes"
description: "Lytics offers a wide range of pre-packaged user attributes, including automatically generated and customizable ones. Additionally, Lytics employs…"
url: "https://www.contentstack.com/docs/lytics/developer-attributes"
product: "Contentstack"
doc_type: "guide"
audience:
  - developers
  - admins
version: "current"
last_updated: "2026-11-05"
---

# Default Attributes

Lytics offers a wide range of pre-packaged user attributes, including automatically generated and customizable ones. Additionally, Lytics employs predictive modeling and machine learning algorithms to provide insights and scores, allowing users to gain a deeper understanding of their audience. The guide below provides an overview of all available attributes and examples to enhance your profiling efforts.

If you haven't already reviewed our [documentation on collecting events](/docs/lytics/lytics-javascript-tag#data-collection) via our JavaScript SDK, we highly recommend doing so first. This will give you a better understanding of how data collection works at a high level before delving into the specifics of what can be collected.

## Available Attributes

The following attributes are all available out of the box with no customization necessary in all Lytics pricing tiers. Do note that any attributes flagged as **Computed** can not be edited directly but are computed based on various factors, including other non-computed attributes.

For a more comprehensive example of how any of the following attributes can be collected and used for your visitors click the **name** of the identifier to access the code examples below.

### Identifiers

Default attributes that are used to stitch profiles together. For instance, if you pass an **email** along with the **\_uid**, all events that have only been associated with either identifier will be merged into a single comprehensive profile.

Name

Slug

Description

Computed

Example

[Lytics ID](#identifiers-1)

\_id

A unique ID that represents the materialized profile in Lytics.

Yes

4fafb5b3-b199-58f2-a68b-4b266b363dd1

[Current Lytics Cookie](#identifiers-1)

\_uid

The current cookie id for the user.

No

50b772f5-a0be-42f2-8828-84b8db5d5a23

[All Lytics Cookies](#identifiers-1)

\_uids

All cookies that are associated with the user.

No

\["50b772f5-a0be-42f2-8828-84b8db5d5a23"\]

[Email](#identifiers-1)

email

The email address of the user.

No

example@lytics.com

[Unique User ID](#identifiers-1)

uuid

A UUID for the user.

No

4fafb5b3-b199-58f2-a68b-4b266b363dd1

### Details

Details encompass all default attributes related to user demographics and general information, including name, phone number, status, etc. It serves as a catch-all for attributes not specifically tied to interactions or behaviors.

Name

Slug

Description

Computed

Example

[Name](#details-1)

name

The full name of the user.

No

John Doe

[First Name](#details-1)

first\_name

The first name of the user.

No

John

[Last Name](#details-1)

last\_name

The last name of the user.

No

Doe

[Title](#details-1)

title

The title of the user.

No

President

[Phone](#details-1)

phone

The phone number of the user.

No

555-555-5555

[Cell](#details-1)

cell

The cell phone number of the user.

No

555-555-5555

[Origin](#details-1)

origin

The origin of the user.

No

loyalty\_2022

[Language](#details-1)

language

The language of the user.

No

en-us

[Age](#details-1)

age

The age of the user.

No

25

[Companies](#details-1)

companies

The companies the user is associated with.

No

\["Lytics", "Pantheon"\]

[Gender](#details-1)

gender

The gender of the user.

No

M

[Status](#details-1)

status

The status of the user.

No

active

[User Attributes](#details-1)

user\_attributes

A map of custom attributes associated with the user.

No

{"role": "member", "bonus": "active"}

[Timezone](#details-1)

timezone

The timezone of the user.

No

\-7

[City](#details-1)

city

The city of the user.

No

Denver

[Country](#details-1)

country

The country of the user.

No

US

[State](#details-1)

state

The state of the user.

No

CO

### Meta

Meta encompasses all system-level information that provides insights into the health and breadth of the profile. This includes data such as creation date, last update timestamp, source information, and other metadata associated with the profile's management and maintenance. Metadata offers a behind-the-scenes view of the profile's overall status and administration.

Name

Slug

Description

Computed

Example

[Created](#meta-1)

\_created

The date the user was created.

Yes

2023-12-12T21:09:11.625960142Z

[Last Scored](#meta-1)

\_last\_scored

The date the user was last scored.

Yes

2024-02-28T02:45:51.377423153Z

[Modified](#meta-1)

\_modified

The date the user was last modified.

Yes

2024-02-28T02:45:51.377423473Z

[Number of Aliases](#meta-1)

\_num\_aliases

The number of aliases for the user.

Yes

1

[Number of Days](#meta-1)

\_num\_days

The number of days the profile has existed.

Yes

38

[Number of Events](#meta-1)

\_num\_events

The number of events the user has been associated with.

Yes

2425

[Number of Streams](#meta-1)

\_num\_streams

The number of streams the user has been associated with.

Yes

2

[Stream Names](#meta-1)

\_streamnames

The names of the streams the user has been associated with.

Yes

\["default", "ios"\]

[User is Bot](#meta-1)

is\_bot

Whether the user has been flagged as a bot or not.

Yes

f

### Behavior

Behavioral attributes typically cannot be directly managed but represent a set of insights derived from a user's behavior over time. These insights are invaluable when personalizing experiences based on changes in behavior or behaviors indicative of high likelihood. For instance, you might want to present a premium offer to users exhibiting higher momentum than usual. Behavioral attributes enable targeted and timely interventions tailored to user actions and patterns.

Name

Slug

Description

Computed

Example

[Consistency](#behavior-1)

score\_consistency

Score representing how consistent their activity patterns are.

Yes

99

[Frequency](#behavior-1)

score\_frequency

A score representing how frequently the user is active.

Yes

63

[Intensity](#behavior-1)

score\_intensity

A score representing how intense the user's activity is.

Yes

94

[Maturity](#behavior-1)

score\_maturity

A score representing how mature the user's activity is.

Yes

34

[Momentum](#behavior-1)

score\_momentum

A score representing how much momentum the user currently has.

Yes

54

[Propensity](#behavior-1)

score\_propensity

A score representing how likely the user is to engage again.

Yes

1

[Quantity](#behavior-1)

score\_quantity

A score representing how much activity the user has.

Yes

99

[Recency](#behavior-1)

score\_recency

A score representing how recent the user's activity is.

Yes

99

[Volatility](#behavior-1)

score\_volatility

A score representing the degree of variability in behavior.

Yes

99

### Interests

Interests entail understanding the topics a user is interested in based on their interactions, cross-referenced by deep programmatic analysis of their online activities. This allows for tailored content recommendations and targeted messaging aligned with the user's preferences and engagement history.

Name

Slug

Description

Computed

Example

[Lytics Content](#interests-1)

lytics\_content

A map of topic-level interests for the user.

Yes

{"Baking": 0.26418695138978837}

### Intelligence

Attributes classified as intelligence encompass diverse, highly valuable information to facilitate relevant and high-value personalized experiences. Within this category, you'll discover real-time segment membership, values crucial for split testing and experimentation, and direct correlation to our real-time machine learning modeling. These attributes empower dynamic and data-driven decision-making, enhancing the efficacy of personalized marketing strategies.

Name

Slug

Description

Computed

Example

[Segment Membership](#intelligence-1)

\_segments

The segments the user is associated with.

Yes

\["all", "anonymous\_profiles", "smt\_power"\]

[Split](#intelligence-1)

\_split

A random value that is evenly distributed across users.

Yes

74

[Split 2](#intelligence-1)

\_split2

A random secondary value that is evenly distributed across users.

Yes

58

[Needs Message](#intelligence-1)

needs\_message

Stream-specific score that represents the relative distance between now and the next predicted event.

Yes

{"default": 0.05758899316182292}

[Next Event](#intelligence-1)

next\_event

Stream-specific prediction for the next expected event.

Yes

{"default": "2024-03-01T03:00:00Z"}

[Lookalike Model Predictions](#intelligence-1)

segment\_prediction

Scores from Lytics Lookalike and SegmentML models.

Yes

{"likely\_to\_churn": 0.26418695138978837}

[Lookalike Model Percentiles](#intelligence-1)

segment\_prediction\_percentile

Percentiles from Lytics Lookalike and SegmentML models.

Yes

{"likely\_to\_churn": 0.26418695138978837}

### Activity

Activity encompasses the user's engagement across different channels and campaigns, including clicks and conversions. It provides valuable insights into recent interactions, aiding campaign optimization and channel effectiveness assessment.

#### General

Name

Slug

Description

Computed

Example

[First Seen](#general-1)

event\_first\_seen

The first time the user was seen for a specific event.

No

{"click": "2023-12-12T21:09:11.625Z"}

[Last Seen](#general-1)

event\_last\_seen

The last time the user was seen for a specific event.

No

{"click": "2024-02-28T02:45:49.776Z"}

[Channels](#general-1)

channels

The channels the user has been active on.

No

\["web", "email"\]

[Devices](#general-1)

devices

The devices the user has been active on.

No

{"desktop": 123}

[Hourly](#general-1)

hourly

The number of events per hour for the user.

Yes

{"0": 17, "1": 69, "2": 262, "3": 97}

[Hour of Week](#general-1)

hourofweek

The number of events per hour of the week for the user.

Yes

{"3": 2, "4": 2, "5": 1, "11": 3}

[Last Active](#general-1)

last\_active\_ts

The last time the user was active.

No

2024-02-28T02:45:50.784Z

[Last Channel Activities](#general-1)

last\_channel\_activities

The last time the user was active on a specific channel.

No

{"web": "2024-02-28T02:45:50.784Z"}

#### Web

Name

Slug

Description

Computed

Example

[Domains](#web-1)

domains

The domains the user has been active on.

No

\["umami.lytics.com"\]

[First Visit Timestamp](#web-1)

firstvisit\_ts

The first time the user visited the site.

No

2023-12-12T21:09:11.625Z

[Last Visit Timestamp](#web-1)

lastvisit\_ts

The last time the user visited the site.

No

2024-02-28T02:45:50.784Z

[Pageview Count](#web-1)

pageviewct

The number of pageviews the user has had.

Yes

234

[Referring Domain](#web-1)

refdomain

The referring domain for the user.

No

\["umami.lytics.com"\]

[User Agent](#web-1)

user\_agent

The user agent for the user.

Yes

Chrome

[Visit Count](#web-1)

visitct

The number of visits the user has had.

Yes

145

[Visit City](#web-1)

visit\_city

The city the user visited from.

Yes

Denver

[Visit Country](#web-1)

visit\_country

The country the user visited from.

Yes

US

[Visit Region](#web-1)

visit\_region

The region the user visited from.

Yes

CO

[Form Data](#web-1)

form\_data

The form data the user has submitted.

No

{"first\_name": "John"}

[Forms Submitted](#web-1)

forms\_submitted

The forms the user has submitted.

No

\["newsletter", "contact"\]

[UTM Campaign Last](#web-1)

utm\_campaign\_last

The last UTM campaign referred from.

No

holiday

[UTM Campaigns](#web-1)

utm\_campaigns

The UTM campaigns the user has interacted with.

No

\["holiday", "summer"\]

[UTM Content Last](#web-1)

utm\_content\_last

The last UTM content referred from.

No

recipe-1

[UTM Contents](#web-1)

utm\_contents

The UTM contents the user has interacted with.

No

\["recipe-1", "recipe-2"\]

[UTM Medium Last](#web-1)

utm\_medium\_last

The last UTM medium referred from.

No

article

[UTM Mediums](#web-1)

utm\_mediums

The UTM mediums the user has interacted with.

No

\["article", "recipe"\]

[UTM Source Last](#web-1)

utm\_source\_last

The last UTM source referred from.

No

google\_ads

[UTM Sources](#web-1)

utm\_sources

The UTM sources the user has interacted with.

No

\["google\_ads", "meta\_ads"\]

[UTM Term Last](#web-1)

utm\_term\_last

The last UTM term referred from.

No

example

[UTM Terms](#web-1)

utm\_terms

The UTM terms the user has interacted with.

No

\["example"\]

#### Campaign

Name

Slug

Description

Computed

Example

[Hover](#campaign-1)

ly\_hover

The number of times the user hovered over a specific campaign.

No

{"content-rec-modal": 5}

[Impressions](#campaign-1)

ly\_impressions

The number of times the user saw a specific campaign.

No

{"content-rec-modal": 1}

[Closes](#campaign-1)

ly\_closes

The number of times the user closed a specific campaign.

No

{"content-rec-modal": 10}

[Conversions](#campaign-1)

ly\_conversions

The number of times the user converted on a specific campaign.

No

{"content-rec-modal": 2}

[Milestones](#campaign-1)

ly\_milestones

The number of times the user reached a milestone on a campaign.

No

{"engaged-donation-page": 1}

[Goals](#campaign-1)

ly\_goals

The number of times the user reached a goal on a campaign.

No

{"made-donation": 1}

## Examples

### Identifiers

##### Lytics ID (\_id)

This is an automatically generated canonical ID managed by Lytics. It refers to the materialized profile and cannot be customized or overridden.

##### Current Lytics Cookie (\_uid) and All Lytics Cookies (\_uids)

\_uid represents the Lytics anonymous 1st party cookie. This value is automatically captured with every jstag.send() call from the JavaScript tag. The only way to customize this value is to explicitly set the value of \_uid, which we do not recommend.

```
jstag.setid("somecustomvalue");
jstag.send();
```

##### Email (email)

```
jstag.send({
  email:"example@lytics.com"
});
```

##### Unique User ID (uuid)

```
jstag.send({
  uuid:"someuniqueuserid"
});
```

### Details

##### First Name (first\_name)

```
jstag.send({
  first_name:"John",
});
```

##### Last Name (last\_name)

```
jstag.send({
  last_name:"Doe",
});
```

##### Title (title)

```
jstag.send({
  title:"President",
});
```

##### Phone (phone)

```
jstag.send({
  phone:"555-555-5555",
});
```

##### Cell (cell)

```
jstag.send({
  cell:"555-555-5555",
});
```

##### Origin (origin)

```
jstag.send({
  origin:"loyalty_2022",
});
```

##### Language (language)

By default, the Lytics JavaScript SDK will collect language information based on the browser, but this can be overridden.

```
jstag.send({
  _ul:"en-us",
});
```

##### Age (age)

```
jstag.send({
  age:25,
});
```

##### Companies (companies)

```
jstag.send({
  companies:["Lytics", "Pantheon"],
});
```

##### Gender (gender)

```
jstag.send({
  gender: "N/A",
})
```

### Meta

##### Created (\_created)

Lytics automatically generate this and represents the oldest event associated with the user.

##### Modified (\_modified)

This is automatically generated by Lytics and represents the last time the user was modified.

##### Last Scored (\_last\_scored)

This is automatically generated by Lytics and represents the last time the users scores were updated.

##### Number of Aliases (\_num\_aliases)

This is automatically generated by Lytics and represents the number of aliases associated with the user.

##### Number of Days (\_num\_days)

This is automatically generated by Lytics and represents the number of days the user has existed.

##### Number of Events (\_num\_events)

This is automatically generated by Lytics and represents the number of events associated with the user.

##### Number of Streams (\_num\_streams)

This is automatically generated by Lytics and represents the number of streams associated with the user.

##### Stream Names (\_streamnames)

This is automatically generated by Lytics and represents the names of the streams associated with the user.

##### User is Bot (is\_bot)

This is automatically generated by Lytics and represents whether the user has been flagged as a bot or not.

### Behavior

The following attributes are all computed in real-time as the profile evolves. Each of the behavioral attributes are surfaced as a score between 0 and 100. These scores represent an aggregate summary of the user's behavior across various dimensions: Consistency, Frequency, Intensity, Maturity, Momentum, Propensity, Quantity, Recency, and Volatility.

#### Interests

##### Lytics Content (lytics\_content)

The interest attributes are computed in real-time and represent the user's interest in various topics. These topics are generated as a result of the analysis done by the Lytics Context Layer and then associated with the user based upon their interaction with content on your site.

#### Intelligence

##### Segment Membership (\_segments)

This attribute displays an array of all segments the user is currently a member of. It updates in real-time based on various audience definitions. Lytics offers a range of useful segments out of the box, requiring no additional setup. For detailed information on these audiences, refer to our Developer Tier > Audiences documentation.

##### Split & Split2 (\_split & \_split2)

These attributes are automatically generated by Lytics and represent a random value evenly distributed across users. They are useful for split testing and experimentation.

##### Needs Message (needs\_message)

This attribute is computed in real-time and represents the relative distance between now and the next predicted event. It is stream specific and is useful for understanding when a user is likely to engage again.

##### Next Event (next\_event)

This attribute is computed in real-time and represents the next expected event. It is stream specific and is useful for understanding when a user is likely to engage again.

##### Lookalike Model Predictions & Lookalike Model Percentiles (segment\_prediction & segment\_prediction\_percentile)

This attribute is computed in real-time and represents the scores resulting from Lytics Lookalike and SegmentML models. Out-of-the-box, Lytics offers a range of useful models, requiring no additional setup. For detailed information on these models, refer to our Developer Tier > Models documentation.

### Activity

#### General

##### First Seen & Last Seen (event\_first\_seen & event\_last\_seen)

Both of these attributes are automatically populated based upon the \_e value in the jstag.send payload. By default Lytics will collect a pv event for each page view and this will automatically populate the first\_seen and last\_seen attributes. Below is an example of collecting a custom event that would populate these attributes as well.

```
jstag.send({
  _e:"custom_event"
});
```

##### Channels (channels) \[needs update\]

```
jstag.send({
  _channel:"web",
});
```

##### Devices (devices)

```
jstag.send({
  _device:"desktop",
});
```

##### Hourly (hourly)

This attribute is automatically populated with a count of events per hour for the user.

##### Hour of Week (hourofweek)

This attribute is automatically populated with a count of events per hour of the week for the user.

##### Last Active Timestamp (last\_active\_ts)

This attribute is automatically populated with the last time an event was received in any stream for the user.

##### Last Channel Activities (last\_channel\_activities) \[needs update\]

```
jstag.send({
  _channel:"web",
});
```

#### Web

##### Domains (domains)

This attribute is automatically populated with the domains the user has been active on.

##### First Visit Timestamp (firstvisit\_ts)

This attribute is automatically populated with the first time the user visited the site and sends data to the default stream.

##### Last Visit Timestamp (lastvisit\_ts)

This attribute is automatically populated with the last time the user visited the site and sends data to the default stream.

##### Pageview Count (pageviewct)

This attribute is automatically populated with the number of \_pv events recieved for the user.

```
jstag.send({
  _e:"pv"
});
```

##### Referring Domain (refdomain)

This attribute is automatically populated with the referring domain for the user.

```
jstag.send({
  _ref:"umami.lytics.com",
});
```

##### User Agent (user\_agent)

This attribute is automatically populated based on the user agent of the browser. This attribute must be turned on in your Lytics account to be collected.

##### Visit Count (visitct)

This attribute is automatically populated with the number of visits the user has had based on presence of the \_sesstart key in an event.

```
jstag.send({
  _sesstart:1
});
```

##### Visit City (visit\_city)

This attribute is automatically populated with the city the user visited from based upon GeoIP.

##### Visit Country (visit\_country)

This attribute is automatically populated with the country the user visited from based upon GeoIP.

##### Visit Region (visit\_region)

This attribute is automatically populated with the region the user visited from based upon GeoIP.

##### Form Data (form\_data)

Form data is a wildcard attribute that allows you to pass a number of key value pairs that all get stored under the form\_data attribute. This is useful for capturing form submissions.

```
jstag.send({
  formdata_fn:"John",
  formdata_ln:"Doe",
  formdata_someotherkey:"somevalue"
});
```

##### Forms Submitted (forms\_submitted)

```
jstag.send({
  form_name:"newsletter"
});
```

##### UTM Campaign Last (utm\_campaign\_last)

```
jstag.send({
  utm_campaign:"holiday"
});
```

##### UTM Campaigns (utm\_campaigns)

```
jstag.send({
  utm_campaign:"holiday"
});
```

##### UTM Content Last (utm\_content\_last)

```
jstag.send({
  utm_content:"recipe-1"
});
```

##### UTM Contents (utm\_contents)

```
jstag.send({
  utm_content:"recipe-1"
});
```

##### UTM Medium Last (utm\_medium\_last)

```
jstag.send({
  utm_medium:"article"
});
```

##### UTM Mediums (utm\_mediums)

```
jstag.send({
  utm_medium:"article"
});
```

##### UTM Source Last (utm\_source\_last)

```
jstag.send({
  utm_source:"google_ads"
});
```

##### UTM Sources (utm\_sources)

```
jstag.send({
  utm_source:"google_ads"
});
```

##### UTM Term Last (utm\_term\_last)

```
jstag.send({
  utm_term:"example"
});
```

##### UTM Terms (utm\_terms)

```
jstag.send({
  utm_term:"example"
});
```

### Campaign

##### Hover (ly\_hover) \[needs update\]

```
jstag.send({
  pf_widget_id: "content-rec-modal",
  pf-widget-event: "hover"
});
```

##### Impressions (ly\_impressions) \[needs update\]

```
jstag.send({
  pf_widget_id: "content-rec-modal",
  pf-widget-event: "show"
});
```

##### Closes (ly\_closes) \[needs update\]

```
jstag.send({
  pf_widget_id: "content-rec-modal",
  pf-widget-event: "close"
});
```

##### Conversions (ly\_conversions) \[needs update\]

```
jstag.send({
  pf_widget_id: "content-rec-modal",
  pf-widget-event: "conversion"
});
```

##### Milestones (ly\_milestones) \[needs update\]

```
jstag.send({
  pf_widget_id: "engaged-donation-page",
  pf-widget-event: "milestone"
});
```

##### Goals (ly\_goals) \[needs update\]

```
jstag.send({
  pf_widget_id: "made-donation",
  pf-widget-event: "goal"
});
```