Agent skill

Customer Win Back Sequencer

by gooseworks-ai in gooseworks-ai/goose-skills

For churned accounts, research what has changed since they left — new funding, team growth, competitor dissatisfaction, product updates that address their pain — then assess re-engagement potential…

MITAuto-check passedMarketing & SEO

Install Customer Win Back Sequencer

skills CLI
$ npx skills add gooseworks-ai/goose-skills --skill customer-win-back-sequencer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install gooseworks-ai/goose-skills customer-win-back-sequencer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/gooseworks-ai/goose-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/outreach/composites/customer-win-back-sequencer .claude/skills/customer-win-back-sequencer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
customer-win-back-sequencer
GitHub stars
1.2k
Used in
1 other repo
Token cost
~2.8k tokens
SKILL.md length
719 words
Files
2
Skills in repo
273
Repo updated
First seen
Licence
MIT

At a glance

For churned accounts, research what has changed since they left — new funding, team growth, competitor dissatisfaction, product updates that address their pain — then assess re-engagement potential…

  • Works in 5 steps: Intake → Churned Account Research → Win-Back Scoring → …
  • Tasks that involve Referral and retention marketing
  • SKILL.md covers When to Use, Phase 0: Intake, Phase 1: Churned Account… and Phase 2: Win-Back Scoring, plus 5 more sections
  • Calls make

What it does

Customer Win Back Sequencer is an agent skill from gooseworks-ai/goose-skills. For churned accounts, research what has changed since they left — new funding, team growth, competitor dissatisfaction, product updates that address their pain — then assess re-engagement potential and generate a personalized win-back email sequence with timing recommendations. Chains web research and LinkedIn monitoring with email sequence generation.

Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `skill.meta.json`).

It sits in Marketing & SEO, covering Referral and retention marketing and Email marketing. It works with LinkedIn. The repository describes itself as: Library of Growth & GTM skills + data APIs for Claude Code, Codex, Cursor to run ads, social, content, lead gen, seo and data scraping. The licence is MIT.

When your agent uses it

  • Tasks that involve Referral and retention marketing
  • Tasks that involve Email marketing

Example prompts

  • “/customer-win-back-sequencer”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Intake
  2. Churned Account Research
  3. Win-Back Scoring
  4. Sequence Generation
  5. Output Format

What it can do on your machine

Read from SKILL.md and the folder at commit c650c6d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • make

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Customer Win Back Sequencer loads about 2.8k tokens when it runs. Until then it costs about 96 tokens; SKILL.md has 719 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~96
When it runs · the whole SKILL.md, loaded when a task matches
~2.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from gooseworks-ai/goose-skills at commit c650c6d, republished under its MIT licence (© gooseworks-ai). 719 words, ~2,801 tokens.

Download SKILL.mdSave it as .claude/skills/customer-win-back-sequencer/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
customer-win-back-sequencer
description
For churned accounts, research what has changed since they left — new funding, team growth, competitor dissatisfaction, product updates that address their pain — then assess re-engagement potential and generate a personalized win-back email sequence with timing recommendations. Chains web research and LinkedIn monitoring with email sequence generation.
tags
outreach

Customer Win-Back Sequencer

Not every churned customer is gone forever. This skill identifies which ones to pursue, finds the right re-engagement angle, and generates a personalized win-back sequence. Timing and relevance are everything — no generic "we miss you" emails.

Built for: Startups that have churned customers sitting in a spreadsheet with no plan to re-engage them. The best win-back campaigns are triggered by change — this skill monitors for those changes and strikes when the timing is right.

When to Use

  • "Which churned customers should we try to win back?"
  • "Build a win-back campaign for [customer]"
  • "Research our churned accounts for re-engagement opportunities"
  • "Generate win-back emails for customers who left because of [reason]"
  • "Run the win-back scan on our churn list"

Phase 0: Intake

Churned Account Data
  1. Churn list — CSV/sheet with: company name, domain, contact email, contact LinkedIn URL (if available), churn date, MRR at churn, churn reason (if known)
  2. Time since churn filter — Min/max months since churn to consider (default: 3-18 months. Too recent = too soon. Too old = too stale.)
  3. Minimum value — Only pursue accounts above $X MRR? (Focus effort on worthwhile wins)
Product Context
  1. Major product updates since churn — What's new? (Features, pricing changes, integrations, performance improvements)
  2. Churn reasons addressed — Which past churn reasons have you actually fixed?
  3. Current offer — Any win-back incentive? (Discount, extended trial, concierge onboarding, free migration)
Sequence Preferences
  1. Sender — Who should the emails come from? (Founder, CSM, account exec)
  2. Channel — Email only, or email + LinkedIn?
  3. Sequence length — How many touches? (Default: 3-4 over 3-4 weeks)

Phase 1: Churned Account Research

For each account in the churn list, research what's changed:

1A: Company Changes
Search: "[company name]" funding OR raised OR "series" OR acquisition 2025 2026
Search: "[company name]" hiring OR "we're hiring" OR "growing team"
Search: "[company name]" launch OR "new product" OR expansion OR pivot

Extract:

  • Funding: New round raised? (More budget available)
  • Growth: Headcount increasing? New hires in relevant roles?
  • Product changes: Launched something new that would benefit from your product?
  • Market moves: Entered a new market, new partnerships?
1B: Contact Changes
Search: "[contact name]" "[company name]" OR linkedin.com
Search: "[company name]" "[relevant title]" new OR hired OR promoted

Determine:

  • Same contact still there? If yes, continuity helps. If no, find the new person.
  • Contact promoted? More authority = bigger potential deal.
  • New decision-maker? Fresh eyes, no baggage from the old experience.
1C: Competitor Dissatisfaction Signals

If you know which competitor they switched to:

Search: "[competitor name]" complaints OR issues OR "looking for alternative"
Search: "[competitor name]" site:g2.com negative reviews
Search: "[company name]" "[competitor name]" OR "switched from"

Look for:

  • Public complaints about the competitor they switched to
  • Reviews mentioning problems that your product solves
  • Signs of "buyer's remorse" in the market
1D: Product-Churn Fit Analysis

Match what's changed in your product against their churn reason:

Churn ReasonProduct UpdateWin-Back Angle
"Too expensive"New pricing tier / startup discountPrice-based re-engagement
"Missing [feature]"[Feature] shippedFeature announcement
"Too complex"Simplified onboarding / UX overhaul"We listened" narrative
"Switched to [competitor]"Competitive advantage developedCompetitive displacement
"Didn't see ROI"New ROI dashboard / case studiesProof-based approach
"Champion left"N/A — find new championFresh start narrative
"Company downsized"Company now growing again (from research)Timing-based re-engagement
Show full SKILL.md (255 more words)Show less

Phase 2: Win-Back Scoring

Score each churned account's re-engagement potential:

Win-Back Score = (Change Signal × Churn Reason Addressability × Account Value) / Time Decay

Change Signal (1-5):
  5 = Multiple strong signals (funding + growth + competitor issues)
  4 = One strong signal (funding or significant growth)
  3 = Moderate signal (hiring, product launch)
  2 = Minor signal (still operating, no major changes)
  1 = No detectable change

Churn Reason Addressability (1-3):
  3 = You've directly fixed the reason they left
  2 = Partially addressed or different angle available
  1 = Same issues exist / unknown churn reason

Account Value (multiplier):
  2.0x = Was top 20% by MRR
  1.5x = Mid-tier MRR
  1.0x = Lower MRR

Time Decay (divisor):
  1.0 = Churned 3-6 months ago (sweet spot)
  1.2 = Churned 6-12 months ago
  1.5 = Churned 12-18 months ago
  2.0 = Churned 18+ months ago
Priority Tiers
TierScoreAction
High Priority8+Full personalized sequence + founder outreach
Medium Priority4-7Personalized sequence
Low Priority1-3Batch campaign or skip

Phase 3: Sequence Generation

Win-Back Sequence — High Priority (4 emails over 4 weeks)

Email 1: The Relevant Update (Day 0)

Subject options:
A: "[First name], [specific thing] changed since we last spoke"
B: "We fixed the thing that made you leave"
C: "[Company] + [Your Product] — worth another look?"

---

Hi [First name],

[1 sentence acknowledging they left — no guilt, no desperation]

Since then, we've [specific improvement that addresses their churn reason]:

- [Change 1 — most relevant to their pain]
- [Change 2]
- [Change 3]

[If you have a relevant customer proof point]:
"[Company in their space] switched back and saw [result]."

Would it be worth a 15-minute look at what's different?

[Soft CTA — no pressure]

[Signature]

Email 2: The Proof Point (Day 7)

Subject: "How [similar company] is using [product] now"

Hi [First name],

Quick follow-up — wanted to share something relevant.

[Case study or proof point from a company similar to theirs]:
- [What they achieved]
- [Metric that matters]

[1 sentence connecting this to their specific situation]

[CTA — slightly stronger: "Want me to show you the new [feature] in 10 minutes?"]

[Signature]

Email 3: The Offer (Day 14)

Subject: "[Specific offer — e.g., 'Free migration + 30 days on us']"

Hi [First name],

I know switching tools is a pain — that's usually what keeps people from
coming back even when the product has improved.

So we're making it easy:
- [Offer detail 1 — e.g., "We'll handle the full migration"]
- [Offer detail 2 — e.g., "30 days free to test everything"]
- [Offer detail 3 — e.g., "Dedicated onboarding session"]

[If applicable: "This offer is available through [date]"]

Worth a conversation?

[Signature]

Email 4: The Breakup (Day 28)

Subject: "Closing the loop"

Hi [First name],

Totally understand if the timing isn't right — just wanted to
make sure this didn't slip through the cracks.

Quick summary of what's new:
→ [Key improvement 1]
→ [Key improvement 2]
→ [Standing offer, if applicable]

If anything changes on your end, my inbox is always open.

[Signature]

P.S. [Genuinely helpful resource — e.g., "We just published [relevant content].
Worth a read regardless of which tool you're using."]
Win-Back Sequence — Medium Priority (3 emails over 3 weeks)

Shorter, less personalized but still relevant:

Email 1: Product update announcement + relevance to their use case Email 2: Customer proof point + specific offer Email 3: Soft breakup with resource share

Win-Back Sequence — Competitor-Specific

If they switched to a known competitor:

Email 1: "How [product] compares to [competitor] today" — honest, non-aggressive comparison focused on what changed Email 2: Customer story of someone who switched back from that specific competitor Email 3: Offer + easy migration path

Phase 4: Output Format

markdown
# Win-Back Opportunity Report — [DATE]
Churned accounts analyzed: [N]
Time window: [Churned between X and Y months ago]

---

## Summary

| Priority | Accounts | Total MRR Opportunity |
|----------|----------|----------------------|
| High Priority | [N] | $[X]/mo |
| Medium Priority | [N] | $[X]/mo |
| Low Priority / Skip | [N] | $[X]/mo |

**Total recoverable MRR:** $[X]/mo (estimated, assuming [Y%] win-back rate)

---

## High Priority Accounts

### [Company 1] — Churned: [date] | Former MRR: $[X]
**Churn reason:** [Reason]
**What's changed (them):** [Research findings]
**What's changed (us):** [Product updates that address their pain]
**Win-back angle:** [The core pitch]
**Contact:** [Name, title, email]
**Sequence:** [Attached — 4 emails, personalized]

### [Company 2] — ...

---

## Medium Priority Accounts

| Account | Churned | MRR | Churn Reason | Win-Back Angle | Score |
|---------|---------|-----|-------------|---------------|-------|
| [Name] | [Date] | $[X] | [Reason] | [Angle] | [N] |

---

## Email Sequences

### [Company 1] — Full Personalized Sequence
[Email 1: Subject + body]
[Email 2: Subject + body]
[Email 3: Subject + body]
[Email 4: Subject + body]

### [Company 2] — ...

---

## Accounts to Skip (and Why)

| Account | Reason to Skip |
|---------|---------------|
| [Name] | [Still in same situation / company shut down / too recent] |

---

## Win-Back Campaign Setup

If using Smartlead:
- Campaign name: "Win-Back — [Month] [Year]"
- Sequences: [Use generated sequences above]
- Timing: [Recommended send schedule]
- Sender: [Recommended — founder for high priority, CSM for medium]

Save to clients/<client-name>/customer-success/win-back/win-back-report-[YYYY-MM-DD].md.

Cost

ComponentCost
Web research per churned accountFree
LinkedIn research (optional)~$0.25-0.50 per account
Sequence generationFree (LLM reasoning)
TotalFree — $5 (for ~10 accounts with LinkedIn research)

Tools Required

  • web_search — for company and competitor research
  • fetch_webpage — for career pages, news, competitor reviews
  • Optional: linkedin-profile-post-scraper for contact monitoring
  • Optional: review-site-scraper for competitor dissatisfaction signals
  • Optional: cold-email-outreach for campaign creation

Trigger Phrases

  • "Which churned customers should we win back?"
  • "Build a win-back sequence for [customer]"
  • "Research our churn list for re-engagement"
  • "Run the win-back scan"
  • "Generate win-back emails for churned accounts"

© gooseworks-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/outreach/composites/customer-win-back-sequencer of gooseworks-ai/goose-skills.

  • SKILL.md
  • skill.meta.json

Open the folder on GitHubat commit c650c6d

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in gooseworks-ai/goose-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Customer Win Back Sequencer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Smscoreyhaines31/marketingskills54k1 repos~4.6kAutomated safety check: PassMIT
Email Sequence Designeraaron-he-zhu/aaron-marketing-skills2.9k2 repos~4.2kAutomated safety check: PassApache-2.0
Reactivation Specialistaaron-he-zhu/aaron-marketing-skills2.9k2 repos~4.1kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Customer Win Back Sequencer

What does Customer Win Back Sequencer do?

For churned accounts, research what has changed since they left — new funding, team growth, competitor dissatisfaction, product updates that address their pain — then assess re-engagement potential…. Customer Win Back Sequencer is an agent skill from gooseworks-ai/goose-skills. For churned accounts, research what has changed since they left — new funding, team growth, competitor dissatisfaction, product updates that address their pain — then assess re-engagement potential and generate a personalized win-back email sequence with timing recommendations.

When should I use Customer Win Back Sequencer?

Customer Win Back Sequencer fits situations like: tasks that involve Referral and retention marketing; tasks that involve Email marketing.

How do I install Customer Win Back Sequencer in Claude Code?

Run `npx skills add gooseworks-ai/goose-skills --skill customer-win-back-sequencer -a claude-code`. Or copy the skill folder (skills/outreach/composites/customer-win-back-sequencer in gooseworks-ai/goose-skills) into .claude/skills/customer-win-back-sequencer in your project. Claude Code loads it when a task matches its description.

How do I install Customer Win Back Sequencer in Codex?

Run `npx skills add gooseworks-ai/goose-skills --skill customer-win-back-sequencer -a codex`. Or copy the skill folder (skills/outreach/composites/customer-win-back-sequencer in gooseworks-ai/goose-skills) into .agents/skills/customer-win-back-sequencer in your project. Codex loads it when a task matches its description.

Can I use Customer Win Back Sequencer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add gooseworks-ai/goose-skills --skill customer-win-back-sequencer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/customer-win-back-sequencer, .gemini/skills/customer-win-back-sequencer, .github/skills/customer-win-back-sequencer and .opencode/skills/customer-win-back-sequencer in your project.

What does Customer Win Back Sequencer need to run?

Going by SKILL.md and its folder, Customer Win Back Sequencer needs the command-line tools its instructions call (make).

Does Customer Win Back Sequencer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Customer Win Back Sequencer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Customer Win Back Sequencer use?

Customer Win Back Sequencer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Customer Win Back Sequencer use?

About 2.8k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Customer Win Back Sequencer?

Skills that share tags, products or a category with Customer Win Back Sequencer: Marketing Os (Yuzzyuk/marketing-os, 540 stars), Churn Prevention (freekmurze/dotfiles, 1k stars), Sms (coreyhaines31/marketingskills, 54k stars) and Email Sequence Designer (aaron-he-zhu/aaron-marketing-skills, 2.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Customer Win Back Sequencer?

gooseworks-ai (a GitHub organization) maintains it in gooseworks-ai/goose-skills, which has 1,240 GitHub stars. The repository holds 273 skills in this directory. The repository was last updated on October 8, 2026.

Source: gooseworks-ai/goose-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.