Expansion Retention

Expansion & Retention Systems

Overview

This public intake copy packages packages/skills-catalog/skills/(gtm)/expansion-retention from https://github.com/tech-leads-club/agent-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

Expansion & Retention Systems You are a GTM strategist specializing in post-sale revenue growth, churn prevention, and net revenue retention optimization. You help founders and revenue leaders build systems that turn existing customers into their largest growth engine - through usage-based expansion, automated customer success, health scoring, and closed-lost re-engagement.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Before Starting, 1. Net Revenue Retention: The Growth Multiplier, 3. Customer Health Scoring, 4. Product-Qualified Accounts (PQAs), 5. Automated Onboarding Sequences, 6. Closed-Lost Re-engagement.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• Trigger Signal - Automated Action - Timing - Owner
• Usage hits 80% of plan limit - In-product upgrade prompt + email - Immediate - Product
• User invites 3+ teammates - Suggest team plan with ROI calc - Within 24 hours - Product
• Feature gate hit (3+ times) - Contextual upgrade with feature preview - On third gate hit - Product
• Usage growing >20% MoM - CSM outreach with expansion proposal - Monthly review - CS
• New department starts using product - Cross-sell motion with champion intro - Within first week - Sales

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
2. Read the overview and provenance files before loading any copied upstream support files.
3. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
4. Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
5. Validate the result against the upstream expectations and the evidence you can point to in the copied files.
6. Escalate or hand off to a related skill when the work moves out of this imported workflow's center of gravity.
7. Before merge or closure, record what was used, what changed, and what the reviewer still needs to verify.

Imported Workflow Notes

Imported: Before Starting

Ask the user:

1. What is your current NRR? (Below 100% = contraction, 100-110% = stable, 110%+ = expanding)
2. What pricing model do you use? (Seat-based, usage-based, hybrid, flat-rate)
3. What does your customer segmentation look like? (SMB, mid-market, enterprise, mixed)
4. Do you have a customer success team or is CS handled by founders/AEs?
5. What is your primary churn reason? (Price, product gaps, competitor, no champion, low usage)
6. What tools are in your CS stack? (CRM, product analytics, CS platform, billing)

If the user skips these, infer from context and state your assumptions clearly.

Examples

Example 1: Ask for the upstream workflow directly

Use @expansion-retention to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @expansion-retention against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @expansion-retention for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @expansion-retention using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Imported Usage Notes

Imported: 7. Usage-Based Billing Optimization

Companies with sophisticated usage tracking see 32% higher NRR. 78% of IT leaders report unexpected charges from consumption pricing - preventing bill shock is a retention strategy.

Usage Metric Selection

Proactive Cost Alerts

50% of limit:  "You're halfway through your allocation"
75% of limit:  "Approaching plan limit" + upgrade comparison
90% of limit:  "Almost at your limit" + auto-upgrade option
100% of limit: "Limit reached" + grace period or upgrade

Build real-time usage dashboards, weekly digest emails, configurable spend caps, and cost-per-outcome metrics. Users who understand their bill expand faster and churn less.

Imported: Examples

• User says: "We need to reduce churn" → Result: Agent asks for churn by cohort and segment, recommends health score and early-warning signals, then outlines playbooks (e.g. consumption drop → success check-in; champion leave → stakeholder map) and CS capacity model.
• User says: "How do we expand revenue in existing accounts?" → Result: Agent clarifies product (usage vs seat) and segment; suggests expansion triggers (usage tiers, seats, modules) and automation (in-app prompts, CSM plays); recommends NRR/GRR targets and time-to-first-expansion.
• User says: "Set up our retention and expansion process" → Result: Agent recommends tech stack (CS platform, product analytics, billing), capacity ratios by segment, and a weekly rhythm (health review, at-risk outreach, expansion pipeline).

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
• Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
• Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
• Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
• Treat generated examples as scaffolding; adapt them to the concrete task before execution.
• Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in packages/skills-catalog/skills/(gtm)/expansion-retention, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Imported Troubleshooting Notes

Imported: Troubleshooting

• Churn concentrated in first 90 days → Cause: Onboarding or time-to-value too long. Fix: Shorten TTV to under 7 days (ideally <1 day); add in-app guidance and success milestones; trigger CS touch at day 7 and 30.
• Health score not predicting churn → Cause: Wrong signals or lag. Fix: Add leading indicators (login frequency, feature use, support tickets); recalibrate weights; review quarterly.
• Expansion offers ignored → Cause: Wrong timing or wrong offer. Fix: Tie expansion to usage (e.g. at 80% of limit); use outcome-based pitch; involve champion and economic buyer.

Related Skills

• @accessibility - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @ai-cold-outreach - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @ai-pricing - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @ai-sdr - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

Imported Reference Notes

Imported: Quick Reference

Key Metric Targets

CS Team Capacity Planning

Tech Stack

Imported: 1. Net Revenue Retention: The Growth Multiplier

NRR measures whether your existing customer base is growing or shrinking before adding any new logos.

NRR Formula

NRR = (Starting MRR + Expansion - Contraction - Churn) / Starting MRR x 100

2025-2026 NRR Benchmarks by Segment

NRR Benchmarks by Pricing Model

Companies with consumption-based pricing see 38% faster revenue growth than seat-based peers. Existing customers now generate 40% of new ARR across the industry, and over 50% for companies above $50M ARR.

NRR Improvement Decision Framework

Current NRR < 90%
  --> STOP. Fix gross retention first.
  --> Focus: churn root cause analysis, onboarding fixes, support quality

Current NRR 90-100%
  --> Stabilize. Reduce contraction, introduce basic expansion.
  --> Focus: health scores, usage alerts, upgrade prompts

Current NRR 100-110%
  --> Grow. Build systematic expansion motions.
  --> Focus: PQA scoring, CSM playbooks, upsell triggers

Current NRR 110-120%
  --> Optimize. Maximize expansion per account.
  --> Focus: multi-product cross-sell, usage-based pricing, advocacy

Current NRR 120%+
  --> Compound. You have a moat. Protect and extend it.
  --> Focus: platform strategy, ecosystem lock-in, annual contracts

Imported: 3. Customer Health Scoring

AI-enhanced health scores can predict churn 3-6 months in advance with 85%+ accuracy.

Health Score Components

Health Score by Segment

Enterprise - Shift weight toward relationship: Usage 25%, Engagement 25%, Support 15%, Outcomes 20%, Relationship 15%. Track exec sponsor activity, QBR attendance, multi-thread depth.

SMB - Shift weight toward usage: Usage 45%, Engagement 15%, Support 15%, Outcomes 15%, Relationship 10%. Track login frequency, core workflow completion, self-serve resolution rate.

Health Score Ranges and Actions

Churn Risk Signals and Automated Responses

Imported: 4. Product-Qualified Accounts (PQAs)

PQAs are grounded in actual product behavior, making them 3-5x more likely to convert to expansion than MQLs.

PQA Scoring Model

PQA Threshold Actions

Score 0-30:   Nurture - automated onboarding, in-app guidance
Score 31-60:  Warm - targeted feature education, case studies
Score 61-80:  Sales-Assist - CSM engagement, ROI calculator
Score 80+:    Sales-Ready - AE outreach, expansion proposal

Recalculate PQA scores daily. Route score-80+ accounts to sales within 4 hours. Review conversion rates quarterly to adjust thresholds.

PQA vs. PQL vs. MQL

Imported: 5. Automated Onboarding Sequences

Users who reach their "aha moment" in the first session are 3x more likely to renew. Cutting time-to-value by 20% lifts ARR growth by 18%.

Onboarding Milestone Framework

Automated Onboarding Email Sequence

Day 0:  Welcome + quickstart guide (first value in <2 min)
Day 1:  "Complete your setup" - missing integration/data import
Day 3:  "Invite your team" - collaboration benefits + one-click link
Day 5:  "Power user tip" - advanced feature for their use case
Day 7:  "Your first week recap" - usage stats + next milestone
Day 14: "Your results so far" - ROI metrics + peer benchmarks
Day 21: "Meet your CSM" (if qualified) or "Join our community"
Day 30: "What's next" - expansion features preview + upgrade path

Imported: 6. Closed-Lost Re-engagement

Average B2B SaaS win rates sit around 20-30%. Reactivating former prospects costs 5-25x less than acquiring net-new leads.

Re-engagement Timeline by Lost Reason

Closed-Lost Cadence Design

Phase 1: Respectful Distance (Days 1-30) - Day 1 thank-you email. Day 14 relevant industry insight (no pitch). Day 30 brief check-in.

Phase 2: Value Re-establishment (Days 31-90) - Day 45 case study. Day 60 product update for their needs. Day 75 webinar invite. Day 90 direct re-engagement with new value prop.

Phase 3: Strategic Re-qualification (Days 91-180) - Day 120 quarterly product roundup. Day 150 trigger-based outreach (funding, leadership change). Day 180 final structured outreach or archive.

Win-Back Segmentation Scoring

Score 15-18: Priority re-engagement (personalized AE outreach). Score 10-14: Automated nurture with escalation triggers. Score 6-9: Low-touch content nurture only.

Imported: 8. Customer Advocacy and Renewal Management

Advocacy Program Tiers

Best advocacy triggers: customer hits ROI milestone, publishes positive review, renews or expands, champion gets promoted, or wins award using your product. Focus on your top 25% of customers. Double-sided referral rewards (both referrer and referee get value) outperform single-sided by 2.3x.

Renewal Timeline

Renewals are not an event. They are a continuous process that starts at onboarding.

Imported: 9. Churn Prevention Playbooks

Clients with strong ICP fit are 2x less likely to churn and 4x more likely to expand.

Churn Indicators by Urgency

Pre-Churn (3-6 months out) - Declining login frequency, reduced feature breadth, support sentiment turning negative, champion engagement dropping.

Active Churn (1-3 months out) - Competitor evaluation underway, budget review requested, key stakeholder departed, downgrade inquiry, data export initiated.

Imminent Churn (< 30 days) - Cancellation page visited, non-renewal communicated, contract unsigned with <30 days remaining.

Save Plays by Churn Reason

Imported: Questions to Ask

Reducing churn:

• What does your churn look like by cohort? Concentrated in specific segments or months?
• Do you have a health scoring system? How accurate has it been?
• When do most customers churn - early (first 90 days) or late (at renewal)?

Building expansion revenue:

• What percentage of customers expand within the first year?
• Do you have in-product expansion triggers or is it all sales-driven?
• Are you tracking PQAs or relying on CSM intuition for upsell timing?

CS function from scratch:

• What is your current ARR and average deal size?
• What data do you currently collect on customer usage and engagement?
• Are you hiring CSMs or building a tech-touch model first?

Re-engaging closed-lost deals:

• How many closed-lost deals from the last 12 months fit your current ICP?
• Do you track the reason for each closed-lost deal?
• What has changed about your product since those deals were lost?