January 20265 min read

Email Segmentation

Behavioral and dynamic list segmentation for targeted campaigns.

Segmentation Overview

Segmented emails drive 30% higher opens and 50% higher clicks than non-segmented campaigns. In 2025, subscribers expect relevant, personalized content—not mass blasts.

Why Segment

code

Without Segmentation:
├── Same message to everyone
├── Lower engagement rates
├── Higher unsubscribes
├── Wasted potential

With Segmentation:
├── Relevant content to each group
├── Higher engagement
├── Better deliverability
├── Increased revenue

Impact on Metrics

| Metric | Mass Email | Segmented | |--------|------------|-----------| | Open Rate | 20% | 26-30% | | Click Rate | 2.5% | 4-5% | | Unsubscribe | 0.5% | 0.2% | | Revenue/Email | $0.10 | $0.25+ |

Segmentation Types

Demographic Segmentation

code

Basic Demographics:
├── Location (country, state, city)
├── Age range
├── Gender
├── Language
├── Job title (B2B)
├── Industry (B2B)
├── Company size (B2B)

Behavioral Segmentation

code

Website Behavior:
├── Pages viewed
├── Products browsed
├── Content downloaded
├── Time on site

Email Behavior:
├── Opens in last 30/60/90 days
├── Click activity
├── Email preferences
├── Response frequency

Purchase Behavior:
├── Past purchases
├── Purchase frequency
├── Average order value
├── Product categories bought
├── Days since last purchase

Engagement-Based Segments

code

Engagement Levels:
├── VIP: Opens 80%+ emails
├── Active: Opens regularly (last 30 days)
├── Engaged: Opens occasionally (last 60 days)
├── At-Risk: No opens in 60-90 days
├── Inactive: No opens in 90+ days
├── Churned: No opens in 180+ days

Lifecycle Stages

code

E-commerce:
├── New subscribers (never purchased)
├── First-time buyers
├── Repeat customers (2-3 purchases)
├── Loyal customers (4+ purchases)
├── VIP/High-value
├── Lapsed (previously active)

B2B/SaaS:
├── Subscriber
├── Lead
├── Marketing Qualified Lead (MQL)
├── Sales Qualified Lead (SQL)
├── Opportunity
├── Customer
├── Churned

Behavioral Segmentation

RFM Analysis

code

Recency: How recently they purchased
├── Recent (0-30 days)
├── Active (31-90 days)
├── Lapsed (91-180 days)
├── Dormant (180+ days)

Frequency: How often they purchase
├── One-time
├── Occasional (2-3)
├── Regular (4-10)
├── Frequent (10+)

Monetary: How much they spend
├── Low (<$50 average)
├── Medium ($50-200)
├── High ($200-500)
├── VIP ($500+)

Engagement Scoring

code

Point System Example:
+10 points: Email open
+20 points: Email click
+30 points: Website visit
+50 points: Content download
+100 points: Purchase

Segments:
├── Hot (100+ points/month)
├── Warm (50-99 points)
├── Cool (20-49 points)
├── Cold (0-19 points)

Purchase History

code

Segment by:
├── Product category buyers
├── Price point preference
├── Seasonal vs year-round
├── Discount vs full-price
├── Single vs multi-category

Dynamic Segments

What Are Dynamic Segments

code

Static Segment:
├── Fixed list of contacts
├── Manually updated
├── Point-in-time snapshot

Dynamic Segment:
├── Rule-based criteria
├── Automatically updates
├── Always current
├── Contacts move in/out based on behavior

Example Dynamic Segments

code

High-Value At-Risk:
Rules:
├── Total purchases > $500
├── Last purchase > 60 days ago
├── No email clicks in 30 days

Action: Trigger win-back with VIP offer

code

Cart Abandoners (Product):
Rules:
├── Added [specific product] to cart
├── Did not purchase in 24 hours
├── Not in existing cart flow

Action: Send product-specific recovery email

code

Newsletter Only (Not Buying):
Rules:
├── Subscribed 30+ days ago
├── Opens emails (engaged)
├── Zero purchases

Action: Educational content → product introduction

Segmentation Strategy

Segmentation Framework

code

Start Simple:
1. Engagement level (active vs inactive)
2. Customer vs non-customer
3. Purchase recency

Then Add:
4. Product interests
5. Purchase frequency/value
6. Lifecycle stage

Advanced:
7. Predictive segments
8. Lookalike segments
9. Micro-segments

Content by Segment

| Segment | Content Strategy | |---------|-----------------| | New Subscribers | Education, brand story, social proof | | Active Non-Buyers | Product education, reviews, offers | | One-Time Buyers | Cross-sell, reviews request, loyalty | | Repeat Buyers | New products, VIP perks, exclusives | | VIP | Early access, special offers, recognition | | At-Risk | Re-engagement, incentives, feedback |

Segment Size Guidelines

code

Minimum Sizes:
├── For meaningful analysis: 100+ contacts
├── For A/B testing: 500+ contacts
├── For reliable patterns: 1,000+ contacts

If segment too small:
├── Combine with related segment
├── Broaden criteria
├── Use for automation only

Implementation

Setting Up Segments

code

## Essential Segments to Create

### By Engagement
□ Engaged (opened in last 30 days)
□ At-Risk (no open in 30-60 days)
□ Inactive (no open in 60-90 days)
□ Churned (no open in 90+ days)

### By Customer Status
□ Never Purchased
□ One-Time Buyer
□ Repeat Customer (2+ purchases)
□ VIP (top 10% by revenue)

### By Behavior
□ Cart Abandoners (last 7 days)
□ Browse Abandoners (last 7 days)
□ Recent Purchasers (last 30 days)
□ Lapsed Customers (90+ days)

Segment Maintenance

code

Weekly:
├── Check segment sizes
├── Review segment overlaps
├── Monitor segment growth/decline

Monthly:
├── Analyze segment performance
├── Update segment criteria if needed
├── Create new segments for trends

Quarterly:
├── Full segment audit
├── Archive unused segments
├── Document segment logic

Avoiding Over-Segmentation

code

Signs of Over-Segmentation:
├── Segments too small to test
├── Too many campaigns to manage
├── Content differences are minor
├── Analysis becomes impossible

Keep it manageable:
├── Start with 5-10 segments
├── Each segment needs unique strategy
├── Consolidate similar segments

Pro Tip: The best first segment to create is "Engaged Subscribers" (opened or clicked in last 30-60 days). Send your important campaigns to this segment first—they're most likely to convert and will boost your deliverability.

January 20265 min read

Email Segmentation

Behavioral and dynamic list segmentation for targeted campaigns.

Segmentation Overview

Segmented emails drive 30% higher opens and 50% higher clicks than non-segmented campaigns. In 2025, subscribers expect relevant, personalized content—not mass blasts.

Why Segment

code

Without Segmentation:
├── Same message to everyone
├── Lower engagement rates
├── Higher unsubscribes
├── Wasted potential

With Segmentation:
├── Relevant content to each group
├── Higher engagement
├── Better deliverability
├── Increased revenue

Impact on Metrics

| Metric | Mass Email | Segmented | |--------|------------|-----------| | Open Rate | 20% | 26-30% | | Click Rate | 2.5% | 4-5% | | Unsubscribe | 0.5% | 0.2% | | Revenue/Email | $0.10 | $0.25+ |

Segmentation Types

Demographic Segmentation

code

Basic Demographics:
├── Location (country, state, city)
├── Age range
├── Gender
├── Language
├── Job title (B2B)
├── Industry (B2B)
├── Company size (B2B)

Behavioral Segmentation

code

Website Behavior:
├── Pages viewed
├── Products browsed
├── Content downloaded
├── Time on site

Email Behavior:
├── Opens in last 30/60/90 days
├── Click activity
├── Email preferences
├── Response frequency

Purchase Behavior:
├── Past purchases
├── Purchase frequency
├── Average order value
├── Product categories bought
├── Days since last purchase

Engagement-Based Segments

code

Engagement Levels:
├── VIP: Opens 80%+ emails
├── Active: Opens regularly (last 30 days)
├── Engaged: Opens occasionally (last 60 days)
├── At-Risk: No opens in 60-90 days
├── Inactive: No opens in 90+ days
├── Churned: No opens in 180+ days

Lifecycle Stages

code

E-commerce:
├── New subscribers (never purchased)
├── First-time buyers
├── Repeat customers (2-3 purchases)
├── Loyal customers (4+ purchases)
├── VIP/High-value
├── Lapsed (previously active)

B2B/SaaS:
├── Subscriber
├── Lead
├── Marketing Qualified Lead (MQL)
├── Sales Qualified Lead (SQL)
├── Opportunity
├── Customer
├── Churned

Behavioral Segmentation

RFM Analysis

code

Recency: How recently they purchased
├── Recent (0-30 days)
├── Active (31-90 days)
├── Lapsed (91-180 days)
├── Dormant (180+ days)

Frequency: How often they purchase
├── One-time
├── Occasional (2-3)
├── Regular (4-10)
├── Frequent (10+)

Monetary: How much they spend
├── Low (<$50 average)
├── Medium ($50-200)
├── High ($200-500)
├── VIP ($500+)

Engagement Scoring

code

Point System Example:
+10 points: Email open
+20 points: Email click
+30 points: Website visit
+50 points: Content download
+100 points: Purchase

Segments:
├── Hot (100+ points/month)
├── Warm (50-99 points)
├── Cool (20-49 points)
├── Cold (0-19 points)

Purchase History

code

Segment by:
├── Product category buyers
├── Price point preference
├── Seasonal vs year-round
├── Discount vs full-price
├── Single vs multi-category

Dynamic Segments

What Are Dynamic Segments

code

Static Segment:
├── Fixed list of contacts
├── Manually updated
├── Point-in-time snapshot

Dynamic Segment:
├── Rule-based criteria
├── Automatically updates
├── Always current
├── Contacts move in/out based on behavior

Example Dynamic Segments

code

High-Value At-Risk:
Rules:
├── Total purchases > $500
├── Last purchase > 60 days ago
├── No email clicks in 30 days

Action: Trigger win-back with VIP offer

code

Cart Abandoners (Product):
Rules:
├── Added [specific product] to cart
├── Did not purchase in 24 hours
├── Not in existing cart flow

Action: Send product-specific recovery email

code

Newsletter Only (Not Buying):
Rules:
├── Subscribed 30+ days ago
├── Opens emails (engaged)
├── Zero purchases

Action: Educational content → product introduction

Segmentation Strategy

Segmentation Framework

code

Start Simple:
1. Engagement level (active vs inactive)
2. Customer vs non-customer
3. Purchase recency

Then Add:
4. Product interests
5. Purchase frequency/value
6. Lifecycle stage

Advanced:
7. Predictive segments
8. Lookalike segments
9. Micro-segments

Content by Segment

Segment Size Guidelines

code

Minimum Sizes:
├── For meaningful analysis: 100+ contacts
├── For A/B testing: 500+ contacts
├── For reliable patterns: 1,000+ contacts

If segment too small:
├── Combine with related segment
├── Broaden criteria
├── Use for automation only

Implementation

Setting Up Segments

code

## Essential Segments to Create

### By Engagement
□ Engaged (opened in last 30 days)
□ At-Risk (no open in 30-60 days)
□ Inactive (no open in 60-90 days)
□ Churned (no open in 90+ days)

### By Customer Status
□ Never Purchased
□ One-Time Buyer
□ Repeat Customer (2+ purchases)
□ VIP (top 10% by revenue)

### By Behavior
□ Cart Abandoners (last 7 days)
□ Browse Abandoners (last 7 days)
□ Recent Purchasers (last 30 days)
□ Lapsed Customers (90+ days)

Segment Maintenance

code

Weekly:
├── Check segment sizes
├── Review segment overlaps
├── Monitor segment growth/decline

Monthly:
├── Analyze segment performance
├── Update segment criteria if needed
├── Create new segments for trends

Quarterly:
├── Full segment audit
├── Archive unused segments
├── Document segment logic

Avoiding Over-Segmentation

code

Signs of Over-Segmentation:
├── Segments too small to test
├── Too many campaigns to manage
├── Content differences are minor
├── Analysis becomes impossible

Keep it manageable:
├── Start with 5-10 segments
├── Each segment needs unique strategy
├── Consolidate similar segments

Pro Tip: The best first segment to create is "Engaged Subscribers" (opened or clicked in last 30-60 days). Send your important campaigns to this segment first—they're most likely to convert and will boost your deliverability.