CRM and Lifecycle skill 03 of 13

Lifecycle Segmentation and Engagement Tiers SKILL.md

The Lifecycle Segmentation skill makes Claude, Codex or another AI agent build segments that drive action: lifecycle stages, engagement tiers based on clicks, purchases and logins instead of inflated opens, RFM and value groups, intent and preference segments and B2B fit. Every segment gets an action matrix for journeys, frequency, offers and channels, and a sunset policy protects deliverability.

lifecycle-segmentation/SKILL.md, version 1.0.0, 1,651 words.

Segmentation decides who gets which message. Done well, it means new customers hear about getting started, loyal customers hear about what's new, at-risk customers get help and lapsed subscribers stop receiving mail they ignore. Done badly, everyone gets everything, engagement falls, complaints rise and inbox placement suffers.

This skill builds segments that are simple enough to maintain, based on behaviour rather than opens, and tied to actions: who to message, how often, with what, and who to suppress.

Operating principles

  1. Behaviour beats demographics. What people did recently predicts what they'll do next better than who they are.
  2. Clicks, purchases and logins over opens. Apple Mail Privacy Protection pre-loads images for many Apple Mail users, so opens are inflated and unreliable for engagement.
  3. Every segment needs an action. If no message, offer or suppression changes for a segment, it doesn't need to exist.
  4. Fewer, durable segments. A handful of well-defined segments used everywhere beats dozens of one-off lists.
  5. Suppression is a segment too. Deciding who not to mail protects deliverability and goodwill.

Core segment families

FamilyExamplesTypical use
Lifecycle stageNew, activated, repeat, loyal, at risk, lapsedWhich journey someone is in
Engagement tierEngaged (clicked or bought in 30 days), warm (90 days), cold (180 days), inactive (over 180 days)Frequency and sunset rules
ValueRFM (recency, frequency, monetary), predicted lifetime value, plan tierOffers, service level, VIP treatment
IntentBrowsed category, abandoned cart, viewed pricing, used feature XTriggered messages
PreferenceTopics chosen, channel preference, frequency choiceRespecting what people asked for
B2B fitIndustry, company size, role, account stageContent relevance and sales handoff

RFM in practice

Score each customer 1 to 5 on recency (days since last purchase), frequency (number of purchases) and monetary value (total spend), using quintiles from your own data. Then group:

GroupRFM patternAction
ChampionsHigh R, high F, high MEarly access, referrals, reviews; avoid discounts
LoyalMedium to high R and FCross-sell, loyalty perks
Promising newHigh R, low FSecond-purchase journey
At riskLow R, high F or MWin-back with service first, offer second
HibernatingLow R, low FLow-frequency reactivation, then sunset

When to use, and when not to

Use it when everyone receives the same campaigns, when engagement and deliverability are falling, before personalisation projects, and when moving platforms.

Don't use it to map stages from scratch (customer-journey-mapping) or to clean the underlying data (crm-data-hygiene).

Inputs to ask for, in one message

  1. Platform and available data: events, purchases, product usage, preferences.
  2. List size and engagement distribution (last click, last purchase, last login).
  3. Current segments and how they're used.
  4. Revenue by customer group, if available.
  5. Any regional or consent rules that limit targeting.

Raw SKILL.md file

.md

This is the exact file agents read, including the credit header and licence notice. Save it as lifecycle-segmentation/SKILL.md.

---
name: lifecycle-segmentation
description: "Build segments that drive action: lifecycle stages, engagement tiers based on clicks, purchases and logins rather than Apple-inflated opens, RFM and value groups, intent and preference segments, B2B fit, an action matrix for journeys, frequency, offers and channels, and a sunset policy that protects deliverability. Use whenever someone asks about email segmentation, customer segments, RFM analysis, engagement tiers, sunset policies, who to send to, list cleaning by engagement, or why every subscriber gets every campaign."
license: CC-BY-4.0
metadata:
  author: Afeez Adebayo
  author_url: https://afeezadebayo.com
  author_linkedin: https://www.linkedin.com/in/afeez-adebayo/
  author_x: https://x.com/za_icon
  source: https://afeezadebayo.com/skills-md/marketing/crm-lifecycle/lifecycle-segmentation/
  category: marketing
  subcategory: crm-lifecycle
  version: "1.0.0"
  created: "2026-10-10"
  updated: "2026-10-10"
---

# Lifecycle Segmentation and Engagement Tiers

Segmentation decides who gets which message. Done well, it means new customers hear about getting started, loyal customers hear about what's new, at-risk customers get help and lapsed subscribers stop receiving mail they ignore. Done badly, everyone gets everything, engagement falls, complaints rise and inbox placement suffers.

This skill builds segments that are simple enough to maintain, based on behaviour rather than opens, and tied to actions: who to message, how often, with what, and who to suppress.

## Operating principles
1. **Behaviour beats demographics.** What people did recently predicts what they'll do next better than who they are.
2. **Clicks, purchases and logins over opens.** Apple Mail Privacy Protection pre-loads images for many Apple Mail users, so opens are inflated and unreliable for engagement.
3. **Every segment needs an action.** If no message, offer or suppression changes for a segment, it doesn't need to exist.
4. **Fewer, durable segments.** A handful of well-defined segments used everywhere beats dozens of one-off lists.
5. **Suppression is a segment too.** Deciding who not to mail protects deliverability and goodwill.

## Core segment families
| Family | Examples | Typical use |
|---|---|---|
| Lifecycle stage | New, activated, repeat, loyal, at risk, lapsed | Which journey someone is in |
| Engagement tier | Engaged (clicked or bought in 30 days), warm (90 days), cold (180 days), inactive (over 180 days) | Frequency and sunset rules |
| Value | RFM (recency, frequency, monetary), predicted lifetime value, plan tier | Offers, service level, VIP treatment |
| Intent | Browsed category, abandoned cart, viewed pricing, used feature X | Triggered messages |
| Preference | Topics chosen, channel preference, frequency choice | Respecting what people asked for |
| B2B fit | Industry, company size, role, account stage | Content relevance and sales handoff |

## RFM in practice
Score each customer 1 to 5 on recency (days since last purchase), frequency (number of purchases) and monetary value (total spend), using quintiles from your own data. Then group:

| Group | RFM pattern | Action |
|---|---|---|
| Champions | High R, high F, high M | Early access, referrals, reviews; avoid discounts |
| Loyal | Medium to high R and F | Cross-sell, loyalty perks |
| Promising new | High R, low F | Second-purchase journey |
| At risk | Low R, high F or M | Win-back with service first, offer second |
| Hibernating | Low R, low F | Low-frequency reactivation, then sunset |

## When to use, and when not to
Use it when everyone receives the same campaigns, when engagement and deliverability are falling, before personalisation projects, and when moving platforms.

Don't use it to map stages from scratch (`customer-journey-mapping`) or to clean the underlying data (`crm-data-hygiene`).

## Inputs to ask for, in one message
1. Platform and available data: events, purchases, product usage, preferences.
2. List size and engagement distribution (last click, last purchase, last login).
3. Current segments and how they're used.
4. Revenue by customer group, if available.
5. Any regional or consent rules that limit targeting.

## Workflow

### Step 1. Audit current segments
List every saved segment, its definition, size, last use and owner. Archive anything unused for 90 days.

### Step 2. Define engagement tiers on reliable signals
Use clicks, purchases, logins, replies and site visits. If you must use opens, combine them with another signal and exclude machine opens where your platform flags them.

### Step 3. Define lifecycle stages
Reuse the journey map's entry and exit events so segments and journeys agree.

### Step 4. Add value and intent
Calculate RFM or predicted value; add intent segments for triggered flows.

### Step 5. Attach actions
For each segment: journeys it enters, campaign frequency, offer policy, channel mix and suppression rules.

### Step 6. Set a sunset policy
For subscribers with no clicks, purchases or visits for a set period (often 90 to 180 days, depending on purchase cycle), send a short re-permission sequence, then suppress those who don't respond.

### Step 7. Monitor
Track segment sizes and movement monthly: how many move from new to repeat, from engaged to cold, from at risk to won back.

## Segment definition template
```
Name: Engaged subscribers
Definition: clicked an email OR purchased OR logged in within the last 30 days, AND marketing consent = true
Refresh: daily
Used for: weekly campaigns at full frequency; product launches
Excludes: suppressed, bounced, complained
Owner: lifecycle lead
```

## Frequency rules by tier
| Tier | Campaign frequency | Triggered flows | Notes |
|---|---|---|---|
| Engaged (30 days) | Full schedule | All | Best audience for launches and tests |
| Warm (31 to 90 days) | Reduced (for example half) | All | Lead with best-performing content |
| Cold (91 to 180 days) | Monthly digest or highlights | Purchase-triggered only | Watch complaint rates closely |
| Inactive (over 180 days) | None until re-permission | Transactional only | Re-permission, then suppress |
Adjust the windows to your purchase cycle: a grocery brand might use 14, 45 and 90 days; a furniture brand 60, 180 and 365.

## Re-permission sequence
1. **Email 1:** "Do you still want to hear from us?" with a clear keep-me button and a preference link to choose topics or lower frequency.
2. **Email 2 (5 to 7 days later):** a short reminder showing what they get, with the same button.
3. **Email 3 (5 to 7 days later):** "We'll stop emailing you on [date] unless you click."
4. **Suppress** non-responders from marketing; keep transactional mail. Allow easy re-subscription on site.

## RFM calculation example (SQL)
```sql
WITH c AS (
  SELECT customer_id,
         DATE_DIFF(CURRENT_DATE(), MAX(order_date), DAY) AS recency_days,
         COUNT(*) AS frequency,
         SUM(order_value) AS monetary
  FROM orders
  WHERE order_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 24 MONTH)
  GROUP BY customer_id
)
SELECT customer_id,
       6 - NTILE(5) OVER (ORDER BY recency_days) AS r_score,
       NTILE(5) OVER (ORDER BY frequency) AS f_score,
       NTILE(5) OVER (ORDER BY monetary) AS m_score
FROM c;
```
Recalculate weekly or monthly and sync scores to the messaging platform as profile properties.

## Preference centre essentials
- Topic choices that map to real content streams.
- Frequency options (for example weekly or monthly digest).
- Channel choices (email, SMS, WhatsApp, push) with separate consent.
- A pause option for a set period.
- Unsubscribe from all marketing, clearly visible.
Preferences only build trust if campaigns actually respect them, so wire every preference to a segment rule.

## Edge cases and judgement calls
| Situation | What to do |
|---|---|
| Long purchase cycles (furniture, cars) | Use content engagement and site visits for tiers; lengthen the sunset window |
| B2B accounts with many contacts | Segment at account and contact level; don't sunset a champion because colleagues ignore mail |
| Very small list | Use three or four segments at most |
| Strong privacy rules in a market | Limit profiling to what consent covers; document the basis |
| Predicted LTV from a vendor model | Check it against actual outcomes before using it for offers |

## Handoffs to related skills
- Stage definitions: `customer-journey-mapping`
- Data quality: `crm-data-hygiene`
- Sunset and inbox placement: `email-deliverability`
- At-risk and lapsed programmes: `retention-churn-prevention`, `win-back-reactivation`
- Testing segment-based changes: `lifecycle-experimentation`

## Worked example
An online bookshop sent every campaign to 240,000 subscribers. Defining engagement on clicks and purchases showed only 52,000 had engaged in 90 days, while 110,000 had not clicked or bought in over a year. The new model used four engagement tiers, RFM groups and genre preferences. Campaigns went to engaged and warm tiers at full frequency, cold subscribers received a monthly digest, and inactive subscribers got a three-email re-permission sequence before suppression. Complaint rates fell, Gmail inbox placement improved and revenue per send rose because messages matched interests.

## Output format
```
# Segmentation plan: <business>, <date>
## Current segment audit (keep, merge, archive)
## Segment definitions (name, logic, refresh, owner)
## Action matrix
| Segment | Journeys | Campaign frequency | Offer policy | Channels | Suppression |
## Sunset policy
## Monitoring metrics
```

## Common mistakes
- Engagement based on opens alone.
- Dozens of segments nobody maintains.
- Segments with no change in treatment.
- No sunset policy, so inactive addresses damage deliverability.
- Discounting champions who would buy anyway.

## Questions to ask before you segment
- Which signals are reliable on your platform?
- How long is a normal gap between purchases or visits?
- Who will maintain segment definitions?

## Self-check before you answer
- Are engagement tiers based on reliable signals?
- Does every segment have a clear action?
- Is there a sunset policy matched to the purchase cycle?
- Are definitions documented with refresh and owner?

## Further reading
- Apple Mail Privacy Protection overview: https://support.apple.com/guide/mail/use-mail-privacy-protection-mlhl03be2866/mac
- Klaviyo, RFM analysis guide: https://help.klaviyo.com/

---
Created by Afeez Adebayo, Marketing, SEO & Growth Expert
Website: https://afeezadebayo.com
LinkedIn: https://www.linkedin.com/in/afeez-adebayo/
X: https://x.com/za_icon
Source: https://afeezadebayo.com/skills-md/marketing/crm-lifecycle/lifecycle-segmentation/

Licence: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). You may copy, share and adapt this skill, including for commercial use, as long as you credit Afeez Adebayo and link to the source URL above. Keep this notice in any copy or adapted version.

Workflow

Step 1. Audit current segments

List every saved segment, its definition, size, last use and owner. Archive anything unused for 90 days.

Step 2. Define engagement tiers on reliable signals

Use clicks, purchases, logins, replies and site visits. If you must use opens, combine them with another signal and exclude machine opens where your platform flags them.

Step 3. Define lifecycle stages

Reuse the journey map's entry and exit events so segments and journeys agree.

Step 4. Add value and intent

Calculate RFM or predicted value; add intent segments for triggered flows.

Step 5. Attach actions

For each segment: journeys it enters, campaign frequency, offer policy, channel mix and suppression rules.

Step 6. Set a sunset policy

For subscribers with no clicks, purchases or visits for a set period (often 90 to 180 days, depending on purchase cycle), send a short re-permission sequence, then suppress those who don't respond.

Step 7. Monitor

Track segment sizes and movement monthly: how many move from new to repeat, from engaged to cold, from at risk to won back.

Segment definition template

Name: Engaged subscribers
Definition: clicked an email OR purchased OR logged in within the last 30 days, AND marketing consent = true
Refresh: daily
Used for: weekly campaigns at full frequency; product launches
Excludes: suppressed, bounced, complained
Owner: lifecycle lead

Frequency rules by tier

TierCampaign frequencyTriggered flowsNotes
Engaged (30 days)Full scheduleAllBest audience for launches and tests
Warm (31 to 90 days)Reduced (for example half)AllLead with best-performing content
Cold (91 to 180 days)Monthly digest or highlightsPurchase-triggered onlyWatch complaint rates closely
Inactive (over 180 days)None until re-permissionTransactional onlyRe-permission, then suppress

Adjust the windows to your purchase cycle: a grocery brand might use 14, 45 and 90 days; a furniture brand 60, 180 and 365.

Re-permission sequence

  1. Email 1: "Do you still want to hear from us?" with a clear keep-me button and a preference link to choose topics or lower frequency.
  2. Email 2 (5 to 7 days later): a short reminder showing what they get, with the same button.
  3. Email 3 (5 to 7 days later): "We'll stop emailing you on [date] unless you click."
  4. Suppress non-responders from marketing; keep transactional mail. Allow easy re-subscription on site.

RFM calculation example (SQL)

WITH c AS (
  SELECT customer_id,
         DATE_DIFF(CURRENT_DATE(), MAX(order_date), DAY) AS recency_days,
         COUNT(*) AS frequency,
         SUM(order_value) AS monetary
  FROM orders
  WHERE order_date >= DATE_SUB(CURRENT_DATE(), INTERVAL 24 MONTH)
  GROUP BY customer_id
)
SELECT customer_id,
       6 - NTILE(5) OVER (ORDER BY recency_days) AS r_score,
       NTILE(5) OVER (ORDER BY frequency) AS f_score,
       NTILE(5) OVER (ORDER BY monetary) AS m_score
FROM c;

Recalculate weekly or monthly and sync scores to the messaging platform as profile properties.

Preference centre essentials

  • Topic choices that map to real content streams.
  • Frequency options (for example weekly or monthly digest).
  • Channel choices (email, SMS, WhatsApp, push) with separate consent.
  • A pause option for a set period.
  • Unsubscribe from all marketing, clearly visible.

Preferences only build trust if campaigns actually respect them, so wire every preference to a segment rule.

Edge cases and judgement calls

SituationWhat to do
Long purchase cycles (furniture, cars)Use content engagement and site visits for tiers; lengthen the sunset window
B2B accounts with many contactsSegment at account and contact level; don't sunset a champion because colleagues ignore mail
Very small listUse three or four segments at most
Strong privacy rules in a marketLimit profiling to what consent covers; document the basis
Predicted LTV from a vendor modelCheck it against actual outcomes before using it for offers
  • Stage definitions: customer-journey-mapping
  • Data quality: crm-data-hygiene
  • Sunset and inbox placement: email-deliverability
  • At-risk and lapsed programmes: retention-churn-prevention, win-back-reactivation
  • Testing segment-based changes: lifecycle-experimentation

Worked example

An online bookshop sent every campaign to 240,000 subscribers. Defining engagement on clicks and purchases showed only 52,000 had engaged in 90 days, while 110,000 had not clicked or bought in over a year. The new model used four engagement tiers, RFM groups and genre preferences. Campaigns went to engaged and warm tiers at full frequency, cold subscribers received a monthly digest, and inactive subscribers got a three-email re-permission sequence before suppression. Complaint rates fell, Gmail inbox placement improved and revenue per send rose because messages matched interests.

Output format

# Segmentation plan: <business>, <date>
## Current segment audit (keep, merge, archive)
## Segment definitions (name, logic, refresh, owner)
## Action matrix
| Segment | Journeys | Campaign frequency | Offer policy | Channels | Suppression |
## Sunset policy
## Monitoring metrics

Common mistakes

  • Engagement based on opens alone.
  • Dozens of segments nobody maintains.
  • Segments with no change in treatment.
  • No sunset policy, so inactive addresses damage deliverability.
  • Discounting champions who would buy anyway.

Questions to ask before you segment

  • Which signals are reliable on your platform?
  • How long is a normal gap between purchases or visits?
  • Who will maintain segment definitions?

Self-check before you answer

  • Are engagement tiers based on reliable signals?
  • Does every segment have a clear action?
  • Is there a sunset policy matched to the purchase cycle?
  • Are definitions documented with refresh and owner?

Further reading

When to use this skill, and when not to

Use it when everyone receives every campaign, when engagement and inbox placement are falling, before personalisation projects and when moving platforms.

Segmentation decides who gets which message and how often. Good segments mean new customers hear about getting started, loyal customers hear what’s new, at-risk customers get help and long-inactive subscribers stop receiving mail they ignore, which is also what keeps complaint rates low.

Don’t use it to map stages from scratch (use Customer Journey Mapping) or to clean the data underneath (use CRM Data Hygiene).

Example prompts

  • “Build engagement tiers and a sunset policy for our 240,000 subscribers.”
  • “Calculate RFM groups from this order export and tell me what to send each.”
  • “Our Klaviyo has 140 segments. Which should we keep?”
  • “Design a preference centre that our campaigns will actually respect.”
  • “How should frequency differ between engaged and cold subscribers?”

Example output

The skill returns a fixed structure. A shortened example for an imaginary site:

# Segmentation plan: example bookshop, 10 October 2026

## Engagement tiers (clicks, purchases, visits)
| Tier | Definition | Size | Frequency |
| Engaged | Activity in 30 days | 52,000 | Full |
| Warm | 31-90 days | 41,000 | Half |
| Cold | 91-365 days | 37,000 | Monthly digest |
| Inactive | Over 365 days | 110,000 | Re-permission, then suppress |

## RFM groups
Champions: early access, no discounts. At risk: service-first win-back.

Every segment comes with the action that changes for it; segments that change nothing are archived.

What the agent needs from you

The skill asks for your platform and available data (events, purchases, usage, preferences), list size and the distribution of last click, purchase and login, current segments and how they are used, revenue by customer group and any regional or consent rules that limit targeting.

How this skill hands off to related skills

Segments connect to most of the set. Stages come from Customer Journey Mapping, data quality from CRM Data Hygiene, sunset and inbox placement from Email Deliverability, at-risk and lapsed treatments from Retention and Win-Back, and segment tests from Lifecycle Experimentation.

How to run Lifecycle Segmentation step by step

  1. Install the skill as lifecycle-segmentation/SKILL.md.
  2. Export current segments with definitions, sizes, last use and owners.
  3. Share engagement and purchase data so tiers use clicks, purchases and logins.
  4. Add order data for RFM scoring and any preference fields.
  5. Review definitions, the action matrix and the sunset policy.
  6. Implement and monitor segment sizes and movement monthly.

Situations this skill handles

Segmentation problems usually show up as falling engagement. The skill handles these situations:

SituationWhat the skill does
Everyone gets every campaignBuilds engagement tiers with different frequencies
Huge inactive shareRuns re-permission, then suppresses non-responders
Too many segmentsArchives unused ones and keeps a small durable set
Discounts sent to best customersUses RFM to give champions access and recognition instead
Long purchase cyclesUses visits and content engagement, with longer windows
B2B accountsSegments at account and contact level

What makes this skill different

Most segmentation advice starts with demographics and open rates. This skill starts with behaviour and reliable signals, and insists every segment has an action attached: which journeys it enters, how often it is mailed, what offers it gets and when it is suppressed.

It treats suppression as a segment in its own right. Deciding who not to mail is one of the most effective ways to protect inbox placement for everyone else.

Practical tips from real projects

  • Match windows to the purchase cycle: a grocery brand and a furniture brand need very different tiers.
  • Document every segment with logic, refresh and owner.
  • Don’t discount champions who would buy anyway.
  • Watch segment movement, not just sizes.

A worked example: an online bookshop sent every campaign to 240,000 subscribers. Defining engagement on clicks and purchases showed only 52,000 had engaged in 90 days, while 110,000 had not clicked or bought in over a year. Four engagement tiers, RFM groups and genre preferences replaced the single list. Engaged and warm tiers received full campaigns, cold subscribers a monthly digest and inactive subscribers a three-email re-permission sequence before suppression. Complaints fell, Gmail inbox placement improved and revenue per send rose.

The skill includes the SQL to calculate RFM scores, a frequency table by tier, a re-permission sequence and the essentials of a preference centre, so the plan can be implemented in Klaviyo, Braze, Customer.io or HubSpot without starting from a blank page.

Monthly monitoring closes the loop: how many people move from new to repeat, from engaged to cold and from at risk back to engaged. Those flows between segments are the clearest sign that lifecycle work is changing behaviour, not just sending more messages.

Segment families work together rather than alone. A customer is in one lifecycle stage, one engagement tier and one value group at any time, plus any intent and preference segments that apply. Journeys use the stage, campaign frequency uses the tier, offers use the value group, and triggered messages use intent. Keeping each family to a few clear groups makes the combinations manageable and easy to explain to the rest of the business.

Preference centres complete the picture. Topic choices, frequency options, channel choices with separate consent, a pause option and a clear unsubscribe give people control, and the skill wires every option to a segment rule so campaigns actually honour what people chose. Ignored preferences damage trust faster than having none.

For B2B, segmentation works at two levels. Account segments describe the company (industry, size, stage, health) and contact segments describe the person (role, engagement, preferences). A champion at a healthy account shouldn’t be sunset just because colleagues ignore email, and an inactive contact at an expanding account may need a different message, not suppression.

Frequently asked questions

Grouping customers by where they are in their relationship with you and how they behave, so each group gets messages, frequency and offers that fit.

Apple Mail Privacy Protection pre-loads images for many users, recording opens whether or not people read the email. Clicks, purchases, logins and replies are more reliable.

Recency, frequency and monetary value: scoring customers on how recently they bought, how often and how much, then treating groups such as champions, loyal, at risk and hibernating differently.

A rule for subscribers who haven’t engaged for a set period: send a short re-permission sequence, then stop marketing to those who don’t respond. It protects deliverability and goodwill.

Fewer than most teams think. A handful of durable segments used everywhere beats dozens of one-off lists nobody maintains.

Only if campaigns respect them. Every preference in the centre should map to a segment rule.

Changelog

  • 1.0.0, 10 October 2026: first release.

Use, adapt and share this skill under CC BY 4.0: credit Afeez Adebayo and link to this page.