--- title: "Default Segments" description: "Categorizing users based on their behaviors and characteristics is pivotal for effective audience targeting and personalization strategies. Lytics…" url: "https://www.contentstack.com/docs/lytics/developer-segments" product: "Contentstack" doc_type: "guide" audience: - developers - admins version: "current" last_updated: "2026-11-05" --- # Default Segments Categorizing users based on their behaviors and characteristics is pivotal for effective audience targeting and personalization strategies. Lytics audience segmentation offers a powerful tool for organizing users into meaningful groups based on shared attributes or behaviors. This section provides a comprehensive overview of all audience segments that are provided out-of-the-box. ## Available Segments (Audiences) Lytics audience segments apply predefined rules to each user profile as they update. Membership in these segments is maintained in real-time and can trigger subsequent actions when users enter or exit the segment. The following audience segments are all available out of the box, with no customization necessary in all Lytics pricing tiers. Name Slug Description Definition All all Your entire user base, both anonymous and known. FILTER \* Anonymous Profiles - 30 days anonymous\_profiles\_30\_days Anonymous profiles older than 30 days FILTER AND ( \_modified <= "now-30d", \_num\_aliases = 1, EXISTS '\_uids' ) FROM user ALIAS anonymous\_profiles\_30\_days Anonymous Profiles - 60 days anonymous\_profiles\_60\_days Anonymous profiles older than 60 days FILTER AND ( \_modified <= "now-60d", \_num\_aliases = 1, EXISTS '\_uids' ) FROM user ALIAS anonymous\_profiles\_60\_days Anonymous Profiles - 90 days anonymous\_profiles\_90\_days Anonymous profiles older than 90 days FILTER AND ( \_modified <= "now-90d", \_num\_aliases = 1, EXISTS '\_uids' ) FROM user ALIAS anonymous\_profiles\_90\_days Anonymous Profiles anonymous\_profiles Anonymous Profiles FILTER AND ( \_num\_aliases = 1, EXISTS '\_uids' ) FROM user ALIAS default\_anon\_seg Connected Customers connected\_customer\_segment Connected Customer Segment: Users who are active on 2 or more channels FILTER \_forceinvalidsegmentfield = 1 FROM user ALIAS connected\_customer\_segment Unhealthy Profiles default\_unhealthy\_profiles Any user profile that is in an unhealthy state. Commonly caused by merge conflicts such as rules which conflict. FILTER \_profile\_processing\_failure = true FROM user ALIAS default\_unhealthy\_profiles Behavior: At Risk Users ly\_at\_risk People who's interaction behavior is changing for the worse. FILTER AND (score\_momentum >= 10, score\_momentum <= 30) Behavior: Binge Users ly\_binge\_user People who show a lot of activity when they do interact with your brand. FILTER AND (score\_frequency <= 20, score\_intensity >= 50) Engagement: Casual Visitors ly\_casual\_visitor People who show little activity when they do interact with your brand. FILTER score\_intensity < 25 Engagement: Deeply Engaged Users ly\_deeply\_engaged\_users People who show a lot of activity when they do interact with your brand. FILTER score\_intensity > 75 Engagement: First-time Visitors ly\_first\_time\_visitor People who are visited from the first time. FILTER visitct = 1 Behavior: Frequent Users ly\_frequent\_user People consistently interacting with your brand. FILTER score\_frequency > 65 Campaign Referral Interactions: Email ly\_from\_email People referred from email. FILTER utm\_mediums INTERSECTS ( "email" ) Campaign Referral Interactions: Paid ly\_from\_paid People referred from paid media. FILTER utm\_mediums INTERSECTS ( "cpc", "ppc" ) Campaign Referral Interactions: Social ly\_from\_social People referred from social media. FILTER utm\_mediums INTERSECTS ( "social", "twitter", "facebook", "pinterest", "instagram" ) Web Activity: Has Visited Mobile Web ly\_has\_visited\_mobile\_web People who have visited on mobile web. FILTER EXISTS is\_mobile Web Activity: Has Visited Web ly\_has\_visited\_web People who have visited on web. FILTER channels INTERSECTS ( "web" ) Behavior: Infrequent Users ly\_infrequent\_user People not interacting with your brand. FILTER score\_frequency < 35 Location: International Visitors ly\_international\_visitor People who have visited outside the US. FILTER AND ( EXISTS visit\_country, visit\_country NOT IN ("US") ) Email Capture Status: Known Email ly\_known\_email People who have a known email address. FILTER EXISTS email Engagement: Moderately Engaged Visitors ly\_moderately\_engaged\_visitor People who show average activity when they do interact with your brand. FILTER AND (score\_intensity > 24, score\_intensity < 76) Behavior: Moderately Frequent Users ly\_moderately\_frequent\_user People occasionally interacting with your brand. FILTER AND (score\_frequency > 34, score\_frequency < 76) Web Activity: Multi Session Visitor ly\_multi\_session\_visitor People who have visited multiple times. FILTER visitct > 1 Behavior: Perusers ly\_peruser People who visit often but rarely interact deeply with your brand. FILTER AND (score\_frequency >= 70, score\_intensity <= 20) Engagement: Repeat Visitors ly\_repeat\_visitor People who have visited multiple times. FILTER visitct > 1 Casual Visitors ly\_reporting\_casual\_visitors People who show little activity when they do interact with your brand. FILTER score\_intensity < 25 Deeply Engaged Users ly\_reporting\_deeply\_engaged\_users People who show a lot of activity when they do interact with your brand. FILTER score\_intensity > 75 Frequent Users ly\_reporting\_frequent\_users People who interact with your brand a lot. FILTER score\_frequency > 65 Email ly\_reporting\_from\_email People referred from email. FILTER utm\_mediums intersects ( "email" ) Facebook ly\_reporting\_from\_facebook People referred from Facebook. FILTER utm\_sources intersects ("Facebook", "facebook") Google ly\_reporting\_from\_google People referred from Google search. FILTER utm\_sources intersects ("Google", "Google Search", "Google Ads", "gads", "google", "google-search") Paid ly\_reporting\_from\_paid People referred from paid media. FILTER utm\_mediums intersects ( "cpc", "ppc" ) Social ly\_reporting\_from\_social People referred from social media. FILTER utm\_mediums intersects ( "social", "twitter", "facebook", "pinterest", "instagram" ) Has Visited Mobile Web ly\_reporting\_has\_visited\_mobile\_web People who have visited on mobile web. FILTER EXISTS is\_mobile Has Visited Web ly\_reporting\_has\_visited\_web People who have visited on web. FILTER channels INTERSECTS ( "web" ) Infrequent Users ly\_reporting\_infrequent\_users People who interact with your brand occasionally. FILTER score\_frequency < 35 Last Visit Within 3 Months ly\_reporting\_last\_visit\_within\_3\_months People who have visited within the last 3 months. FILTER lastvisit\_ts > "now-3M" Last Visit Within A Day ly\_reporting\_last\_visit\_within\_day People who have visited within the last day. FILTER lastvisit\_ts > "now-1d" Last Visit Within A Month ly\_reporting\_last\_visit\_within\_month People who have visited within the last month. FILTER lastvisit\_ts > "now-1M" Last Visit Within A Week ly\_reporting\_last\_visit\_within\_week People who have visited within the last week. FILTER lastvisit\_ts > "now-1w" Multi Session Visitor ly\_reporting\_multi\_session\_visitor People who have visited multiple times. FILTER visitct > 1 Single Page Visitor ly\_reporting\_single\_page\_visitor People who have only visited one time. FILTER pageviewct = 1 Web Activity: Single Page Visitor ly\_single\_page\_visitor People who have only visited one time. FILTER pageviewct = 1 Email Capture Status: Unknown Email ly\_unknown\_email People who do not have a known email address. FILTER NOT EXISTS email Location: US Visitors ly\_us\_visitor People who have visited from the US. FILTER visit\_country IN ("US") Browser / OS: Android ly\_uses\_android People who have used Android. FILTER devices INTERSECTS ( "Android" ) Browser / OS: Desktop ly\_uses\_desktop People who used a desktop. FILTER devices INTERSECTS ( "desktop" ) Browser / OS: iOS ly\_uses\_ios People who have used iOS. FILTER devices INTERSECTS ( "IOS" ) Browser / OS: Mobile ly\_uses\_mobile People who have used a mobile device. FILTER devices INTERSECTS ( "Android", "Blackberry", "IOS", "WinMobile" ) Browser / OS: Other ly\_uses\_other People who have used other devices. FILTER devices INTERSECTS ( "Blackberry", "WinMobile", "other" ) Lytics Currently Engaged smt\_active Users who are currently engaging with your brand. FILTER AND ( score\_momentum > 10, EXISTS score\_momentum, \_created < "now-1w", NOT AND ( score\_frequency <= 5, score\_intensity == 0, score\_momentum == 0, score\_quantity <= 3 ), NOT AND ( score\_quantity >= 50, score\_frequency >= 50, score\_intensity >= 25, score\_momentum >= 40 ) ) FROM user Lytics Disengaged smt\_dormant Users who show minimal or no activity for a prolonged period of time. FILTER AND ( AND ( score\_frequency <= 5, score\_intensity == 0, score\_momentum == 0, score\_quantity <= 3 ), EXISTS score\_momentum, \_created < "now-1w" ) FROM user Lytics Previously Engaged smt\_inactive Users who are currently disengaged with your brand, but had been previously. FILTER AND ( score\_momentum <= 10, EXISTS score\_momentum, \_created < "now-1w", NOT AND ( score\_frequency <= 5, score\_intensity == 0, score\_momentum == 0, score\_quantity <= 3 ) ) FROM user Lytics New smt\_new Users who are new to your audience within the last week. FILTER \_created >= "now-1w" FROM user Lytics Highly Engaged smt\_power Users who engage most frequently and consistently of your users. FILTER AND ( AND ( score\_quantity >= 50, score\_frequency >= 50, score\_intensity >= 25, score\_momentum >= 40 ), EXISTS score\_momentum, \_created < "now-1w", NOT AND ( score\_frequency <= 5, score\_intensity == 0, score\_momentum == 0, score\_quantity <= 3 ), score\_momentum > 10 ) FROM user Lytics Unscored smt\_unscored Users who have not registered enough activity to be scored by our behavioral algorithms. FILTER AND ( NOT EXISTS score\_momentum, \_created < "now-1w" )