Real-time segmentation for marketing automation
Create dynamic audiences that update instantly based on behavior. Trigger campaigns at the exact moment customers take action, not hours or days later.
What real-time segmentation delivers
Instant audience updates
Segments refresh in real-time as user behavior changes. No batch processing, no delays. Users enter and exit audiences the moment they take action.
Behavioral triggers
Launch campaigns automatically when users enter segments. Abandoned cart, high-intent browsing, churn risk, and VIP status changes trigger instantly.
No manual list management
Segments build themselves from events and behavior. No CSV uploads, no manual tagging, no outdated lists. Always current, always accurate.
Maximize conversion windows
Reach customers during micro-moments of high intent. Real-time segmentation ensures you message users when they are most likely to convert.
How real-time segmentation works
Segments that react to every action
Build audiences based on any event: purchases, app opens, page views, feature usage, cart additions. Segments update instantly when events fire.
- Custom events
Track any user interaction your app records - Compound filters
Combine events with AND/OR logic for precise targeting - Instant enrollment
Users enter segments the moment they match your criteria
Example: create segment “viewed product 3+ times in 48 hours without purchase” and users enter automatically as they browse.
RFM analysis in real-time
Automatic recency, frequency, and monetary segmentation. Users move between segments (champions, at-risk, hibernating) as their behavior changes.
- Recency
Days since last purchase, app open, or key action - Frequency
How often users complete target actions in a given period - Monetary value
Total spend, average order value, lifetime revenue - Auto-movement
Customers shift between RFM tiers with every transaction
Example: customer who has not purchased in 60 days automatically moves to at-risk segment and receives a retention offer.
Identify intent from behavior patterns
Combine multiple events to detect high-intent moments. Segment by activity patterns, not just single actions.
- Multi-condition logic
Chain events: viewed product 3+ times AND compared options AND no purchase in 30 days - Time-window filters
Scope conditions to specific periods (last 24h, last 7 days) - Cross-channel signals
Combine app, web, and email behavior in one segment
Example: users who viewed a loan calculator 3+ times, compared rates, and browsed competitor sites enter a high-intent loan segment.
See segment sizes update live
Watch your segments grow and shrink in real-time. Know exactly how many users match your criteria right now, not yesterday.
- Live counters
Segment size updates as users enter and exit - Estimate reach before sending
See your audience size before launching a campaign - Trend tracking
Monitor segment growth over time
Example: Black Friday segment tracking “users who added items to cart in the last hour” updates every second.
Why real-time segmentation matters
Static segmentation
- Daily batch processing
Audiences update once per day or slower. - Missed intent windows
Users convert before your campaign reaches them. - Manual list management
CSV exports, tagging, and cleanup required. - Yesterday’s behavior
Messages based on stale data, not current actions. - Irrelevant timing
Campaigns arrive hours after the triggering moment.
Real-time segmentation
- Instant updates
Audiences refresh the moment behavior changes. - Peak intent targeting
Reach users at their highest conversion likelihood. - Fully automated
Segments build and maintain themselves. - Current behavior
Always based on what users are doing right now. - Timely delivery
Campaigns trigger in seconds, not hours.
Segment by anything, update in real-time
Behavioral events
Any custom event from your app: page views, feature usage, purchases. Segment on 'viewed pricing page 3+ times' or any tracked action.
RFM scoring
Automatic customer value scoring. Champions, loyal customers, at-risk, and hibernating segments update with every transaction.
User properties
Demographics, location, device, subscription status, and plan type. Segment by 'premium users in New York' or any stored attribute.
Engagement level
Daily and monthly active users, session frequency, and activity patterns. Identify lapsed users the moment activity drops.
Purchase behavior
Order value, product categories, purchase frequency, and cart size. Segment by 'average order value above $100' automatically.
Geo-location
Real-time location-based segments. Delivery zones, store proximity, and regional offers for users within a defined radius.
Time-based
Lifecycle stage, days since signup, subscription renewal date. Catch users with 'trial ending in 3 days' without any manual work.
Predictive (AI-powered)
Churn risk, conversion likelihood, and high-intent moment detection. Surface users with 75% likelihood to convert in the next 24 hours.
Start segmenting in real-time
Build dynamic audiences that update instantly, trigger campaigns automatically, and reach customers at the exact moment they are most likely to convert.