Live Segments

Live segments query data in real-time every time they're accessed, ensuring you always work with the most current audience. Perfect for behavior-based campaigns, ongoing nurture sequences, and situations where real-time accuracy matters more than speed.

What Are Live Segments?

Live Segment = Real-Time Query

When you use a live segment, Expedify:

1. Runs your filter criteria against current database
2. Finds all contacts/companies/deals matching right now
3. Doesn't store the member list (queries on demand)
4. Always shows latest data

Key Characteristics:

• ✅ Always up-to-date (queries current data)
• ✅ No manual refresh needed (auto-updating)
• ✅ Behavior-based targeting (catches new matches immediately)
• ✅ Real-time accuracy
• ❌ Slower performance (queries each time)
• ❌ No historical snapshots
• ❌ Not ideal for very large segments

When to Use Live Segments

Best Use Cases

1. Behavior-Based Campaigns

• Abandoned cart recovery
• Re-engagement campaigns
• Lead nurture workflows
• Activity-triggered messages

Example:

Segment: "Abandoned Cart - Last 24 Hours"
Filter: Added to cart in last 24 hours AND checkout not completed
Use: Automated cart recovery email
Live segment: Catches new cart abandoners automatically

2. Welcome & Onboarding

• New subscriber sequences
• First-time customer onboarding
• Trial user activation
• Post-purchase follow-up

Example:

Segment: "New Subscribers - Last 7 Days"
Filter: Subscribed in last 7 days AND welcome series not completed
Use: Automated welcome email series
Live segment: New signups automatically enter sequence

3. Always-Current Lists

• Active customers
• High-value leads
• Inactive users needing re-engagement
• VIP status updates

Example:

Segment: "High-Intent Leads - Active"
Filter: Lead score > 80 OR viewed pricing 2+ times in last 7 days
Use: Sales alert automation
Live segment: Sales team sees current hot leads

4. Small to Medium Segments

• < 10,000 members
• Simple filter criteria
• Frequently changing membership
• Real-time accuracy critical

Example:

Segment: "Cart Value > $500 - Today"
Filter: Current cart value > $500 AND cart created today
Use: VIP sales alert
Live segment: Small, high-value group, needs real-time tracking

When NOT to Use Live Segments

❌ Avoid Live Segments For:

• One-time campaigns (use static segments)
• Very large audiences (100,000+ members)
• Complex filter criteria (performance issues)
• Historical analysis (need snapshots)
• A/B testing (need fixed groups)
• When you need consistent member lists

Use Static Segments Instead:

• Event invitations (fixed guest list)
• Quarterly reports (snapshot in time)
• Large newsletter lists (better performance)
• Multi-email sequences (consistent audience)

Creating a Live Segment

Step 1: Navigate to Segments

1. Go to Channel → Segments
2. Click + Create Segment
3. You'll see the segment builder interface

Step 2: Configure Basic Settings

Segment Type:

• Select Live Segment from the dropdown
• This tells Expedify to query data in real-time

Entity Type:

• Choose Contacts, Companies, or Deals
• This determines what kind of records you're segmenting
• Cannot be changed after creation

Example:

Segment Type: Live Segment
Entity Type: Contacts

Step 3: Build Filter Criteria

Add filter conditions to define who belongs in your segment:

Time-Based Filters (Perfect for Live Segments):

Contact created date: in last 7 days
Last email open: in last 30 days
Last purchase date: more than 90 days ago
Page view date: in last 24 hours

Behavior-Based Filters:

Event: Viewed page "/pricing" in last 7 days at least 2 times
Form: Submitted "Demo Request" in last 3 days
Campaign: Opened "Summer Sale" in last 14 days
Activity: Clicked email link in last 30 days

Dynamic Property Filters:

Lead score: greater than 80
Cart value: greater than $100
Subscription status: equals "active"
Tags: contains "vip"

Cross-Entity Filters:

Company Properties:
- Company industry: equals "Technology"
- Company size: greater than 100

Deal Properties:
- Open deal count: greater than 1
- Total deal value: greater than $10,000

Step 4: Configure Filter Logic

AND Logic (all conditions must match):

Contact: Subscribed in last 7 days AND
Contact: Email is verified AND
Contact: Welcome email not sent

→ New verified subscribers who haven't received welcome email

OR Logic (any condition can match):

Contact: Lead score > 90 OR
Contact: Viewed pricing 3+ times in last week OR
Contact: Submitted demo request form

→ Any high-intent signal = qualify for segment

Time-Window Combinations:

(Contact: Added to cart in last 24 hours AND
 Contact: Checkout not completed)
OR
(Contact: Viewed product in last 48 hours AND
 Contact: Not purchased AND
 Contact: Email clicks > 2 in last week)

→ Cart abandoners OR highly engaged window shoppers

Step 5: Preview Members (Real-Time)

Live Preview:

1. Click Preview button
2. See contacts matching filters right now
3. Check current member count
4. Verify results make sense

What You'll See:

• Sample contacts (first 50 from current query)
• Current member count (may change minute-to-minute)
• Filter validation warnings
• Estimated query performance

Important Notes:

• Preview shows current data
• Member count may differ when you access segment later
• Query runs fresh each time you preview
• Performance indicator helps identify slow queries

Step 6: Save Segment

Segment Metadata:

• Name: Descriptive, include "Live" or "Current" (e.g., "Active Cart Abandoners - Live")
• Description: Explain purpose and expected membership
• Tags: Categorize (e.g., behavioral, automation, live)
• Visibility:
  • Private: Only you can see/use
  • Public: Available to entire team

Example:

Name: "New Subscribers - Welcome Series (Live)"
Description: "Contacts who subscribed in last 7 days. Auto-updates for welcome email workflow. Always shows current new subscribers."
Tags: ["onboarding", "automation", "live", "email-series"]
Visibility: Public

Click Save:

• Segment created instantly (no processing)
• No member list stored
• Ready to use immediately
• Queries run when accessed

How Live Segments Work

Real-Time Querying

Each time you access a live segment:

1. Campaign Send:

   User clicks "Send Campaign" →
   System queries live segment →
   Gets current member list →
   Sends to those members

2. Workflow Trigger:

   Every 15 minutes →
   System queries "New Subscribers" live segment →
   Finds contacts who entered segment since last check →
   Triggers workflow for new members

3. Analytics Dashboard:

   Open segment analytics →
   System queries current members →
   Shows real-time count and stats

Auto-Updating Behavior

Example Timeline:

Monday 9 AM:
  Segment "Cart Abandoners - Last 24 Hours"
  Members: John, Sarah, Mike (3 total)

Monday 11 AM:
  Same segment queried again
  Members: Sarah, Mike, Lisa, Tom (4 total)
  (John completed checkout, Lisa & Tom abandoned cart)

Monday 3 PM:
  Same segment queried again
  Members: Tom, Emma, David (3 total)
  (Sarah & Mike completed checkout or aged out, Emma & David abandoned cart)

No Refresh Needed:

• Members automatically added when they match
• Members automatically removed when they stop matching
• Always reflects current state

Performance Considerations

Query Performance Factors:

1. Filter Complexity:

   • Simple: 1-2 conditions → Fast (< 1 second)
   • Medium: 3-5 conditions → Moderate (1-3 seconds)
   • Complex: 6+ conditions, nested groups → Slow (3-10+ seconds)

2. Member Count:

   • Small (< 1,000): Fast
   • Medium (1,000-10,000): Moderate
   • Large (10,000-100,000): Slow
   • Very Large (100,000+): Very slow (use static instead)

3. Field Types:

   • Indexed fields: Fast (ID, email, created_at)
   • Regular fields: Moderate (name, city, tags)
   • Custom fields: Slower (depends on indexing)

4. Time-Based Filters:

   • "in last X days": Fast (indexed)
   • "between dates": Fast
   • Complex date calculations: Slower

Optimization Tips:

• Keep filter count reasonable (3-5 conditions)
• Use indexed fields when possible
• Avoid deep nesting (max 2 levels)
• Consider static segment if performance suffers

Best Practices

Naming Conventions

Include "Live" or Time Window:

• ✅ "Active Cart Abandoners - Live"
• ✅ "New Subscribers - Last 7 Days (Live)"
• ✅ "High-Intent Leads - Current"
• ✅ "Inactive Users - 90+ Days (Live)"

Avoid Dated Names:

• ❌ "Q1 2024 Customers" (implies snapshot)
• ❌ "March Webinar Attendees" (implies fixed list)
• ❌ "Last Week's Leads" (confusing for live segment)

Filter Design

Time-Based Best Practices:

Good:

Last activity: in last 30 days
Created date: in last 7 days
Purchase date: more than 90 days ago

Avoid:

Created date: equals 2024-03-15 (too specific, won't update)
Last activity: before January 1 (static cutoff, won't update)

Relative Time Windows:

✅ "in last X days" - Always relative to today
✅ "in next X days" - Always relative to today
✅ "more than X days ago" - Always relative to today
❌ "between 2024-01-01 and 2024-03-31" - Fixed dates

Use in Automation

Workflow Triggers:

Perfect for Live Segments:

Trigger: Contact enters segment "New Subscriber - Last 24 Hours"
Action: Send welcome email series
Runs: Every 15 minutes
Result: New subscribers automatically enter welcome series

Workflow Conditions:

IF contact in live segment "High-Intent Leads"
  THEN: Assign to sales rep
  ELSE: Continue nurture sequence

Recurring Campaigns:

Daily Newsletter:
  Audience: Live segment "Active Subscribers - Last 90 Days"
  Schedule: Every weekday at 8 AM
  Result: Always sends to currently active subscribers

Monitoring

Track Segment Growth:

Monday: "New Subscribers - Last 7 Days" = 234 members
Tuesday: Same segment = 312 members (78 new)
Wednesday: Same segment = 289 members (some aged out)

Set Alerts:

• Member count drops below threshold
• Segment grows unusually fast
• Query performance degrades

Review Regularly:

• Check filter criteria still makes sense
• Verify member count is reasonable
• Monitor query performance
• Update filters if needed

Common Live Segment Patterns

Welcome & Onboarding

New User Welcome:

Name: "New Users - Welcome Series (Live)"
Filters:
  - Created date: in last 7 days
  - Welcome email not sent: true
  - Email is verified: true
Use: Automated welcome email workflow

Trial Activation:

Name: "Trial Users - Day 1-7 (Live)"
Filters:
  - Trial started: in last 7 days
  - Trial status: active
  - Product usage: less than 5 events
Use: Trial activation sequence

Cart Abandonment

Recent Cart Abandoners:

Name: "Abandoned Cart - Last 24 Hours (Live)"
Filters:
  - Added to cart: in last 24 hours
  - Checkout completed: false
  - Cart value: greater than $50
Use: Automated cart recovery email

Multi-Stage Recovery:

Segment 1: "Abandoned Cart - 1-4 Hours (Live)"
  - Cart age: 1-4 hours
  - Send: Gentle reminder

Segment 2: "Abandoned Cart - 24 Hours (Live)"
  - Cart age: 20-28 hours
  - Send: Discount offer

Segment 3: "Abandoned Cart - 48 Hours (Live)"
  - Cart age: 44-52 hours
  - Send: Final urgency email

Re-engagement

Inactive Users:

Name: "Inactive Users - 90+ Days (Live)"
Filters:
  - Last login: more than 90 days ago
  - Account status: active
  - Re-engagement sent: false in last 90 days
Use: Win-back campaign

Email Inactive:

Name: "Email Inactive - No Open 60 Days (Live)"
Filters:
  - Last email open: more than 60 days ago
  - Email verified: true
  - Subscription status: active
Use: Re-engagement email series

Lead Nurture

High-Intent Signals:

Name: "High-Intent Leads - Current (Live)"
Filters:
  (Lead score: greater than 80) OR
  (Viewed pricing: in last 7 days, at least 2 times) OR
  (Submitted demo form: in last 3 days)
Use: Sales team alert, priority follow-up

Lead Scoring Threshold:

Name: "Hot Leads - Score 80+ (Live)"
Filters:
  - Lead score: greater than 80
  - Contact type: lead
  - Assigned to sales: false
Use: Auto-assign to sales rep

Behavioral Targeting

Product Interest:

Name: "Feature A Interest - Last 14 Days (Live)"
Filters:
  - Viewed feature A page: in last 14 days, at least once
  - Current plan: does not include feature A
  - Account status: active
Use: Upgrade campaign for Feature A

Content Engagement:

Name: "Blog Readers - Active (Live)"
Filters:
  - Viewed blog page: in last 30 days, at least 3 times
  - Subscribed to blog: false
  - Email verified: true
Use: Blog subscription campaign

Troubleshooting

Segment Member Count Changing

Problem: Member count keeps changing when you check

This is NORMAL for live segments!

• Members are added/removed as data changes
• Count reflects current state
• Expected behavior

When to Investigate:

• Dramatic unexpected changes (500 → 5,000 members)
• Count drops to zero unexpectedly
• Constant zero members (filter too restrictive)

Solutions:

1. Review filter logic
2. Check time window settings
3. Verify data quality
4. Consider using static segment if you need fixed count

Poor Performance

Problem: Segment queries are very slow (> 10 seconds)

Causes:

1. Too many members (> 100,000)
2. Complex filter criteria
3. Deep nested groups
4. Unindexed fields

Solutions:

1. Simplify filters: Remove unnecessary conditions
2. Split segment: Create multiple smaller segments
3. Use indexed fields: Filter on ID, email, created_at
4. Switch to static: For large, infrequently-changing segments
5. Optimize time windows: Use "in last X days" instead of complex date ranges

Workflow Not Triggering

Problem: Segment membership workflow trigger not firing

Common Issues:

1. Workflow checks too infrequently

   • Default: Every 15 minutes
   • Solution: Increase check frequency if needed

2. Contacts entering and exiting quickly

   • Example: "Last 1 hour" segment
   • Workflow checks every 15 min, might miss quick changes
   • Solution: Widen time window or use webhook trigger

3. Filter criteria too narrow

   • No contacts matching
   • Solution: Preview segment, broaden filters

4. Workflow paused or disabled

   • Check workflow status
   • Solution: Activate workflow

Unexpected Members

Problem: Segment includes contacts you didn't expect

Debug Steps:

1. Check OR logic: One condition matching includes contact
2. Verify field values: Confirm contact actually matches
3. Review time windows: "in last 30 days" includes full range
4. Examine nested groups: Complex logic can be misleading
5. Use preview: Sample individual member records

Example Debug:

Filter: (City = "Boston" OR Tags contains "vip") AND Email verified

Contact included: Mike
  - City: Chicago (doesn't match)
  - Tags: ["vip", "customer"] (MATCHES)
  - Email verified: true (matches)

Result: Mike included because Tags contains "vip" (OR logic)

Live vs. Static Segment Comparison

Feature	Live Segment	Static Segment
Member Storage	Not stored (queried)	Stored in database
Performance	Slower (query each time)	Fast (pre-computed)
Accuracy	Always current	Snapshot in time
Refresh	Automatic	Manual
Best For	Ongoing campaigns, behavior	One-time, large audiences
Processing	Instant (no processing)	Initial + each refresh
Member Count	Dynamic	Fixed until refresh
Historical Value	None (always current)	High (snapshots)
Query Time	1-10 seconds	< 1 second
Max Recommended Size	10,000 members	1,000,000+ members

Related Resources

• Segment Overview → - Introduction to segments
• Static Segments → - Snapshot-based segments
• Workflow Triggers → - Automate with segments
• Filter Builder → - Master filter logic
• Abandoned Cart Campaign → - Live segment use case