📊
248
Total Segments
🟢
186
Published
⏸️
62
Draft
👥
125K
Avg Audience
⚡
18
This Week
🎯
42
Active Now
Recently Viewed
| # | Segment Name | Data Space | Type | Status | Size | Last Modified | Modified By | Actions |
|---|---|---|---|---|---|---|---|---|
| 1 | High Value Outdoor Enthusiasts | Default | Standard | Active | 45.7K | 2 hours ago | sking | |
| 2 | Churn Risk Segment | Default | Standard | Active | 12.3K | 1 day ago | mileb | |
| 3 | Email Engagement Outreach | Default | Standard | Active | 89.2K | 2 days ago | sking | |
| 4 | Draft Win-back Segment | Default | Standard | Draft | 0 | 3 days ago | BWrig | |
| 5 | Top Spenders Q4 | Default | Standard | Active | 5.4K | 5 days ago | mileb | |
| 6 | Loyalty Tier Gold Members | Default | Standard | Active | 28.9K | 1 week ago | sking |
Create New Segment
What's your goal for today?
Select a common goal or describe your own
OR SELECT A COMMON GOAL
Win-back
Win back recently churned customers
Growth & Monetization
Increase share of wallet from existing customers
Acquisition
Find prospects similar to my best customers
Service Led Marketing
Proactively engage customers frustrated with recent cases
Churn Prevention
Target at-risk customers with retention offers
Cross-sell & Upsell
Drive additional revenue with product recommendations
AI-Recommended Segments
Based on your data, insights from past segments, and performance trends
High Impact
High-Value At-Risk Customers
LTV >$2,500 but declining engagement by 40% in last 30 days
Estimated Size
1,847
Potential Value
$4.6M
Trending
Winter Campaign - Cold Climate
Outdoor enthusiasts in regions with winter sports activity + recent browsing
Estimated Size
12,453
Conv. Rate
18.4%
High ROI
Loyalty Upgrade Opportunity
3+ purchases, $500+ spent, not in loyalty program yet
Estimated Size
5,329
Avg LTV Lift
+45%
Similar +22% open
Email Re-Engagement
Previously engaged, no opens/clicks in 90 days, high past conversion
Estimated Size
8,942
Win-back Rate
12.8%
These segments are generated based on your data patterns, historical segment performance, and current business trends
OR BUILD MANUALLY
Skip AI assistance and build your segment with custom rules and filters
3.2M
Profiles
12
Sources
847
Segments
400
Activations
High Value Outdoor Enthusiasts
Our most engaged outdoor enthusiasts who have a high history of premium purchases but haven't geared up recently
Validate Your Segment
Quick checks to refine your rules before proceeding
Includes
Criteria to match
These are our biggest spenders who've hit the $7k spend milestone
Click for formula
Lifetime Value
is equal to or greater than
USD 7,000
Click to flip back
Group
3 conditions
Outdoor trekking enthusiasts with active interest in adventure gear
Click for formula
Grouped Filter
Match ALL conditions
1.
Past Purchases
includes any
Camping Gear, Skiing Equipment
AND
2.
Magazine Subscription
is equal to
Outdoor Adventure Magazine
AND
3.
Web Activity
viewed categories
Outdoor Equipment (last 30 days)
Click to flip back
Customers we haven't seen in over six months
Click for formula
Last Activity
is more than
180 Days ago
Click to flip back
No filters added yet
Click "Add Rules & Filters" below to start building your segment
AND
Add Rules & Filters to Build Segment
Quick Attributes
Select data model attributes to create custom filter rules
🎂
Age
Numeric • Customer attribute
📍
Location
Text • Geographic attribute
👤
Gender
Select • Demographic attribute
✉️
Email Status
Select • Communication attribute
📅
Last Purchase Date
Date • Transaction attribute
📱
Device Type
Select • Behavior attribute
💵
Income Level
Numeric • Financial attribute
🌐
Language Preference
Select • Preference attribute
Quick Filters
Pre-configured filters with attribute values already set
👥
Millennials (Age 25-40)
Age between 25 and 40
🗺️
PNW Residents
WA, OR, ID states
💰
High Spenders
Total spend > $5,000
📱
Mobile Only Users
Primary device = Mobile
✉️
Email Engaged
Opened email in last 30 days
⭐
Loyalty Gold+
Gold or Platinum tier
🛍️
Recent Purchasers
Purchased in last 60 days
❄️
Winter Enthusiasts
Interest in winter sports
Metrics
Calculated metrics using multiple attributes with formulas
💎
High LTV Customers
Total Spend + Projected Value > $100
📊
Highly Engaged
(Email Opens + Clicks + Site Visits) / 3 > 75
🎯
High AOV Shoppers
Total Spend / Order Count > $150
⚠️
High Churn Risk
Predicted churn probability > 70%
🔄
Frequent Buyers
Order Count / Months Active > 3
💪
Healthy Customers
Composite score (LTV + Engagement + Recency) > 80
📈
High ROI Customers
Revenue / Marketing Cost > 5
❤️
Brand Loyalists
Repeat Purchase Rate + NPS / 2 > 0.8
Build Your Custom Metric
Common Marketing Metrics
Try these examples:
• average order value greater than 500
• average lifetime value above 1000
• total revenue divided by marketing cost greater than 5
• purchase frequency more than 3 per month
• engagement score at least 75
💡 Tip: Press Cmd/Ctrl + Enter to generate
AI Metric Builder
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Formula Preview
Manual Metric Builder
FORMULA PREVIEW
Select attributes and formula to see preview
Other Segments
Include or exclude existing segments as nested conditions
🌟
VIP Customers
45.2K members • Active
⚠️
Churn Risk
12.8K members • Active
🎄
Holiday Shoppers
89.5K members • Active
📧
Email Subscribers
156K members • Active
🆕
New Customers (30 days)
8.3K members • Active
🎯
Win-back Segment
22.1K members • Active
💎
Premium Tier
34.7K members • Active
📱
Mobile App Users
67.9K members • Active
📮
Recently Contacted (30 days)
24.3K members • Active • Common exclusion
All Attributes
Show:
Demographics
🎂Age
👤Gender
📍Location
Show more
Web engagement
📄Page Views (90d)
🖥️Sessions (30d)
📅Last Visit Date
Show more
Sales orders
🛒Order Count
📅Last Purchase Date
💰Total Revenue
Show more
Service history
📋Cases Opened
🎧Support Tier
📅Last Case Date
Show more
View more Data Model Objects
Attributes in selected Data Graph
Predictive Scores
AI-powered propensity and affinity scores from Model Builder
🎯
High Purchase Propensity
ML Score: Likelihood to purchase in next 30 days > 70%
⚠️
High Churn Risk
ML Score: Likelihood to churn in next 90 days > 60%
🏔️
Outdoor Gear Affinity
ML Score: Interest in outdoor products > 80%
💻
Electronics Affinity
ML Score: Interest in electronics > 75%
⬆️
High Upsell Potential
ML Score: Likelihood to upgrade/buy premium > 65%
🔀
High Cross-sell Potential
ML Score: Likelihood to buy complementary products > 70%
❤️
High Brand Loyalty
ML Score: Brand preference and loyalty > 85%
📧
Email Response Propensity
ML Score: Likelihood to engage with email > 60%
✨
High Conversion Likelihood
ML Score: Probability to convert from lead > 75%
🔄
Win-back Opportunity
ML Score: Likelihood lapsed customers will return > 55%
⭐
Premium Product Fit
ML Score: Fit for premium products > 80%
🎁
High Referral Likelihood
ML Score: Likelihood to refer friends > 70%
Excludes
Criteria to filter out
No exclusions added. Click "Add Exclusion" to filter out specific criteria.
Publish Schedule
at
Start
End
Lookback Window
Rank and Limit
Transform your broad segment into highly specific, actionable audiences
What is Group, Rank, and Limit (GRL)?
GRL allows you to organize records into meaningful groups, prioritize them based on defined business rules, and control segment sizes. This transforms broad segments into the best-of-the-best audiences for high-value targeting.
🪣
Group (The Bucket)
Gather members into buckets by City (London, Tokyo, etc.)
📊
Rank (The Priority)
Sort members by Lifetime Points within each city
🎯
Limit (The Quantity)
Select only the Top 5 from each city
AI-Recommended Strategy
For your high-value outdoor segment (12,500 customers, 45% high LTV), here's the optimal approach:
1
🪣
Group
Geographic Region
Your segment spans multiple regions. Grouping ensures you reach customers in all key markets rather than concentrating only where your segment is largest.
2
📊
Rank
Lifetime Value (Descending)
With 45% high LTV customers in your segment, prioritizing by lifetime value ensures you target your most valuable customers first, maximizing campaign ROI.
3
🎯
Limit
Top 500 per Region
Based on your segment size (~12,500 customers) and typical outdoor gear campaign budgets, targeting top 500 from each region creates a focused audience.
Expected Result
Refines your 12,500 customers down to ~2,500-3,000 top-tier customers (500 × 5-6 regions) — the best-of-the-best for maximum campaign ROI.
Configure Your GRL Rules
Example: Group by Geographic Region to ensure fair distribution across all areas
Example: Rank by Lifetime Value in descending order to prioritize highest-value customers
records per group
Example: Limit to Top 500 customers per region for a focused, high-value activation
Result Preview: Your segment of 12,487 customers will be refined to approximately 2,500-3,000 top customers
(500 per region × 5-6 major regions). This ensures you target only the highest-value individuals while maintaining geographic balance.
Why Use Rank and Limit?
✓ Precision Targeting: Focus on best-fit customers instead of everyone who qualifies
✓ Resource Optimization: Control activation costs by limiting audience size
✓ Fair Distribution: Ensure representation across all groups (regions, accounts, etc.)
✓ No SQL Required: Simple point-and-click interface for complex logic
Segment Preview
Explore your segment population with detailed records and key insights
Total Audience
45,700
Avg LTV
$8,450
Top Tier
Gold (47%)
Avg Age
34.2
Gender Split
60% M / 40% F
Top Region
US (53%)
Sample Records
Showing 50 records from your segment
| Customer ID | Name | LTV | Age | Loyalty Tier | Region | Active Status | Gender | Annual Income | Last Purchase | Total Orders | Avg Order Value | Churn Risk | Channel Pref | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| CUST-10281 | Sarah Johnson | $8,240 | 32 | Gold | Pacific NW | Active | sarah.j@email.com | F | $95K | 245 days ago | 18 | $458 | High | Mobile Push | |
| CUST-10742 | Michael Chen | $12,100 | 28 | Platinum | West Coast | Active | m.chen@email.com | M | $115K | 198 days ago | 24 | $504 | Med | ||
| CUST-11029 | Emma Rodriguez | $7,520 | 41 | Gold | Southwest | Active | emma.r@email.com | F | $78K | 210 days ago | 16 | $470 | High | SMS | |
| CUST-11384 | David Park | $9,890 | 35 | Gold | Pacific NW | Active | d.park@email.com | M | $105K | 183 days ago | 21 | $471 | Med | Mobile Push | |
| CUST-11591 | Olivia Martinez | $15,420 | 29 | Platinum | Northeast | Active | olivia.m@email.com | F | $135K | 225 days ago | 32 | $482 | High | ||
| CUST-11847 | James Wilson | $6,780 | 38 | Gold | Midwest | Active | j.wilson@email.com | M | $72K | 267 days ago | 14 | $484 | High | In-App | |
| CUST-12003 | Sophia Lee | $11,200 | 26 | Platinum | Pacific NW | Active | sophia.lee@email.com | F | $122K | 192 days ago | 26 | $431 | Med | Mobile Push | |
| CUST-12289 | Daniel Kim | $8,650 | 33 | Gold | West Coast | Active | d.kim@email.com | M | $91K | 201 days ago | 19 | $455 | Med |
Showing 1-50 of 12,487 records
Sample overview
Contactability and value range in this sample — for full composition and strategy, see Insights.
Contact readiness
48 of 50
records have email + phone for activation
Valid for outreach
96%
consented and not suppressed
LTV in this sample
$2.1K – $18.5K
range across 50 records
Orders in this sample
3 – 42
orders per customer
Channel Affinity Analysis
These channels perform best with your target audience
Why Look at Channel Affinity?
🎯
Optimize Engagement
Reach your audience on channels where they're most active
💰
Reduce Waste
Avoid spending on channels with low engagement potential
📈
Data-Driven Strategy
Make informed decisions based on historical performance
⏰
Perfect Timing
Send messages when your audience is most likely to respond
📱
Mobile Push
Top Pick
High engagement potential
70%
Engagement Breakdown
Delivered: 94.2%
Opened: 68.5%
Clicked: 42.3%
Converted: 12.8%
Best window: 12:00 PM - 2:00 PM
💬
SMS
Medium engagement potential
55%
Engagement Breakdown
Delivered: 97.8%
Viewed: 52.1%
Clicked: 31.4%
Converted: 9.2%
Best window: 10:00 AM - 12:00 PM
✉️
Email
Lower engagement potential
35%
Engagement Breakdown
Delivered: 89.3%
Opened: 28.7%
Clicked: 8.4%
Converted: 2.1%
Best window: 6:00 PM - 8:00 PM
🔔
In-App
Medium engagement potential
48%
Engagement Breakdown
Displayed: 86.5%
Viewed: 45.2%
Clicked: 24.7%
Dismissed: 20.5%
Best window: 9:00 AM - 11:00 AM
Insight: 70% of this segment responds better to Mobile Push notifications. Consider prioritizing this channel for maximum engagement.
This data is based on performance analysis from 847 previous segment activations targeting similar audience segments.
Smart Splits
Create optimized test variants to maximize segment performance
Why Use Smart Splits?
🧪
A/B Testing
Test different offers and messaging to find what resonates best
🛡️
Risk Mitigation
Reduce activation risk by testing variants before full rollout
📊
Data-Driven Decisions
Make informed choices based on real performance data
💰
Maximize ROI
Identify the highest-performing variant to scale for better returns
Adjust Split Percentages
📱
50%
💬
50%
📱 Push Discount
Split 1 of 2
Split Size
50%
🎁
15% Discount
via Mobile Push
Audience
6,244
💬 SMS Free Ship
Split 2 of 2
Split Size
50%
🚚
Free Shipping
via SMS
Audience
6,243
Add Another Split
Create additional variants for multivariate testing
Segment Insights
Strategic understanding of your audience composition, behavior, and business impact
Audience Composition
LTV Tier Distribution
High 45%
Medium 35%
Low 20%
💡 45% High LTV → Premium positioning recommended
Loyalty Status
Gold 47%
Silver 28%
Bronze 25%
Lifecycle Stages
35%
New
40%
Growing
18%
Mature
7%
Veteran
Engagement Levels
28%
Highly
Engaged
Engaged
42%
Moderate
22%
At Risk
8%
Dormant
Behavioral Patterns
Purchase Behavior
Order Frequency
3.2x/yr
Favorite Category
Outdoor Gear
Cross-Buy Propensity
68%
Seasonal Pattern
Spring Peak
Engagement Patterns
Email Open Rate
42%
SMS Response Rate
35%
App Engagement
73%
⏰ Best Time: 6:00 PM - 8:00 PM weekdays
Revenue & Value Indicators
Total Addressable Value
$38.6M
Avg LTV per Customer
$8,450
Revenue at Risk
$2.94M
Projected Lifetime Value
$11.2K
Spending Patterns
Average Order Value (AOV)
$425
Purchase Frequency
3.2x/year
Basket Composition
2.8 items avg
Risk & Opportunity Scores
Churn Risk Distribution
High Risk
65%
Medium Risk
23%
Low Risk
12%
Opportunity Scores
Upsell Potential
High
78% likely to upgrade
Cross-Sell Readiness
68%
2+ category interest
Win-Back Opportunity
Medium
45% recoverable
Sentiment Indicators
Net Promoter Score (NPS)
72
Excellent
Satisfaction Trend
+8.5%
vs last quarter
Suggested Segment Refinements
Based on your insights, consider these high-impact adjustments to your segment
🏆
High Impact
Focus on Gold Tier Only
47% of your segment is already Gold loyalty members. Refine to create a premium VIP segment for exclusive treatment.
Estimated Impact
Size: -53%
Quality: +High
⚡
Recommended
Focus on Highly Engaged Only
28% are highly engaged customers. Targeting this group aligns with your goal for maximum outdoor gear campaign response.
Estimated Impact
Size: -72%
Response: +High
📅
Optimize
Add Recency Filter
3.2x/year purchase frequency suggests quarterly buying patterns. Target customers due for next purchase within 90 days.
Estimated Impact
Size: -25%
Conversion: +High
📱
Add App Activity Filter
Leverage 73% app engagement - highest performing channel for outdoor enthusiasts.
🌸
Add Spring Buyer Filter
Target seasonal peak pattern detected - perfect for outdoor gear campaigns.
🔄
Add Cross-Buy Opportunity Filter
68% cross-buy propensity - expand to complementary outdoor categories.
🎯
Add Upsell Propensity Filter
78% upsell potential - target for premium outdoor equipment upgrades.
Overlap Analysis
Visualize overlap with other active and historical segments
👥
Total Reachable
12,487
+2.3% vs last activation
🎯
Expected Reach
87.2%
Based on channel affinity
⚥
Gender Ratio
60:40
Male : Female
📊
Average Age
34.2
years old
🎯
Top Age Group
25-34
4,620 customers (37%)
💰
Avg Lifetime Value
$3,240
+12% vs avg customer
📍
Top Region
Pacific NW
2,847 customers (23%)
⏰
Avg Days Since Purchase
210
~7 months inactive
🛍️
Past Purchase Rate
3.8x
Above average
⭐
Loyalty Status
Gold+
89% are Gold or Platinum
Segment Overlap Analysis
Visualize overlap with other active and historical segments
Outdoor Adventure Enthusiasts
Activation History: Ran last week and last month with strong engagement
Last Week (Winter Sports Promo):
35% responded
Last Month (Holiday Gift Guide):
52% responded
💡 Recommendation: Coordinate messaging timing to avoid message fatigue. Consider suppressing overlapping users for 2-3 weeks.
Quick Select
🏕️
Outdoor Adventures
Last Week + Last Month
42%
5,244 overlap
❄️
Winter Sports Promo
Last Week
35%
4,370 overlap
🎁
Holiday Gift Guide
Last Month
52%
6,493 overlap
⭐
Premium Buyers
Active
28%
3,496 overlap
💎
Gold Tier Loyalty
Active
38%
4,745 overlap
🛍️
Recent Buyers
Active (30 Days)
22%
2,747 overlap
Message Fatigue Indicators
📊 For This Segment Only (12,487 customers)
All metrics below show contact frequency and fatigue scores specifically for customers in this segment population
23%
Contacted in Last 7 Days
2,847 customers from this segment
19%
High Message Frequency
2,362 customers receiving 6+ msgs/month
6.8/10
Fatigue Risk Score
Moderate-High Risk for this segment
📊 Contact Frequency Breakdown
Of the 12,487 customers in this segment:
Last 7 days:
2,847 (23%)
Last 14 days:
4,120 (33%)
Last 30 days:
6,891 (55%)
Last 90 days:
9,234 (74%)
📬 Message Volume Distribution
Messages per month for this segment:
Light (1-2 msgs):
4,234 (34%)
Moderate (3-5 msgs):
5,891 (47%)
⚠️ High (6+ msgs):
2,362 (19%)
890 customers contacted 5+ times in last 30 days
⚡ Fatigue Risk Analysis
6.8
out of 10
Moderate-High Risk
⚠️ Warning: 19% of customers in this segment (2,362 people) have received high message frequency. Consider suppressing or reducing contact frequency to avoid fatigue.
Smart Optimization Suggestions
AI-recommended actions to reduce overlap and optimize activation effectiveness
Exclusion Suggestions
Remove overlapping customers to prevent conflicts and over-messaging
Exclude active VIP segment customers
234 customers overlap with ongoing VIP outreach
Impact: -234 (1.9%)
Exclude high-frequency contacted
890 customers received 5+ messages in last 30 days
Impact: -890 (7.1%)
Exclude recent converters (14 days)
423 customers made recent purchases
Impact: -423 (3.4%)
Filter Addition Suggestions
Add criteria to reduce overlap and create more unique segments
Add Region = "West Coast"
Would reduce overlap with "Outdoor Adventures" by 28%
Impact: -1,470 customers (11.8%)
Add Age Range 35-45
Would reduce overlap with "Holiday Gift Guide" by 22%
Impact: -3,245 customers (26.0%)
Add Product Category = "Trail Running"
Creates more specific segment focused on trail runners
Impact: -4,680 customers (37.5%)
Activation
Choose an activation template and launch your segment
Segment Summary
Segment Name
High Value Outdoor Enthusiasts
Audience Size
12,487
Avg. LTV
$3,240
Smart Splits
2 Variants (50/50)
See how your audience engages by channel, or split the segment for testing. View channel affinity to optimize by channel; set up smart splits to run variants (e.g. A/B).
Select Activation Template
Recommended Template: Email Re-Engagement Campaign
Based on your goal to promote new outdoor gear, your segment of high-value customers with 47% Gold tier membership, 73% mobile app engagement, and strong email channel affinity (62% engagement rate), we recommend starting with a multi-touchpoint email campaign for maximum reach and personalization.
Choose from our curated activation templates optimized for specific use cases and platforms
Configure Custom Template
Build your activation template with channels and personalization
1
Channels & Contact Points
Select activation platform and choose which contact points to include
Activation Platform
Contact Point Selection
2
Activation Membership Filtering
Apply compliance and membership filters
Membership Filters
3
Add Personalization Attributes & Metrics
Select attributes to personalize your messages
Run a multi-step journey (e.g. email then SMS, or trigger-based flows) before sending to this activation. Add a journey to orchestrate steps and timing.
Journeys
Configure automated multi-step customer journeys
Recommended Journey: Multi-Channel Re-Engagement
Based on your segment's high mobile app engagement (73%) and strong email performance (62% engagement rate), we recommend a multi-channel approach starting with email, followed by intelligent fallback logic to SMS or paid ads based on customer response. This maximizes touchpoints while respecting engagement patterns.
📧
Multi-Channel Re-Engagement
Reach dormant customers across email, SMS, and paid ads with intelligent fallback logic
Channels
✉️ Email
📱 SMS
📘 Meta Ads
Journey Summary
- Initial email with personalized discount
- Wait 48 hours for engagement
- Engaged → SMS follow-up
- Not engaged → Meta Ads retargeting
1
Send Email
48h
?
Engaged?
YES
📱 SMS
NO
📘 Ads
👑
VIP Customer Nurture
Personalized journey based on customer tier (Gold/Platinum/Diamond) with exclusive offers
Channels
✉️ Email
📱 SMS
📞 Phone
Journey Summary
- Welcome email to all VIP tiers
- Wait 24 hours
- Gold → 10% email offer
- Platinum → 20% SMS + gift
- Diamond → Personal rep call
1
Welcome Email
24h
?
Tier?
GOLD
✉️
10%
PLAT
📱
20%
DIA
📞
Call
🛒
Cart Abandonment Recovery
Automated sequence with escalating incentives based on cart value and customer purchase history
Channels
✉️ Email
📱 SMS
Journey Summary
- Send cart reminder email
- Wait 2 hours
- High value (>$100) → SMS with 15% off
- Low value (<$100) → Email with free shipping
1
Reminder Email
2h
?
Cart Value?
>$100
📱 SMS
15% off
<$100
✉️ Email
Free ship
🚀
Product Launch Sequence
Multi-wave launch campaign with early access, waitlist, and general availability phases
Channels
✉️ Email
📱 SMS
📘 Social
📊 Paid Ads
Journey Summary
- Day 1: VIP early access (Email+SMS)
- Day 2: Waitlist opens (Email)
- Day 7: Public launch (All channels)
- Phased rollout for exclusivity
1
VIP Early Access
Day 2
2
Waitlist Opens
Day 7
3
Public Launch
Build Custom Journey
💡 Quick Add Suggested Steps
No steps added yet. Click a suggested step above or define your own.