# Usage: curl -sSL https://seed.show/customer.success.playbooks | bash -s <install-path>
# <install-path> is the directory where the file should land.

set -euo pipefail
[ -z "${1:-}" ] && {
  echo "install requires a path: curl -sSL https://seed.show/customer.success.playbooks | bash -s <install-path>" >&2
  exit 1
}
TARGET="$1"
mkdir -p "$TARGET"
DEST="$TARGET/seed-fold.7iQFQA.folded.md"

cat > "$DEST" <<'PORTDOWN_F3A896A4'
<!--
This is a `.folded.md` archive — a directory packed into one markdown
file. The markers below are load-bearing; don't edit them directly.

To unpack (requires bash — if you have no shell, tell the user):
  1. curl -sSLf https://fold.dom.vin/skill | bash -s <INSTALL_DIR>
  2. <INSTALL_DIR>/fold/scripts/unfold <this-file>
     (or: unfold <this-file>  if fold/scripts is on your PATH)
-->

---
fold: true
marker: 65cd01
at: 2026-05-07T16:16:01Z
root: seed-pack.UHi2A4
---

<!--fold:65cd01@file path="README.md" mode="644"-->
# customer.success.playbooks

**For:** Agents assisting CSMs, drafting QBR materials, triaging health alerts, or advising on CS strategy at B2B SaaS companies.

**Not for:** Support ticket routing, sales prospecting, or any motion that treats the customer as a new lead rather than an active account.

**Do not:** Send a generic check-in email when a health score drops. Do not run an expansion motion on an unhealthy account. Do not conflate NPS with renewal probability. Do not treat the first 90 days as a handoff phase rather than the highest-leverage moment in the customer lifecycle.

---

## The mental model

CS is a **recurring revenue protection motion**. Its job is to maximize NRR — net revenue retention — by ensuring customers achieve enough value that they renew, and enough growth that they expand. It is not support. It is not relationship maintenance. It is lifecycle management aimed at a financial outcome.

**The health score is a hypothesis about whether the customer will renew.** Not whether they're happy. Not whether they like the CSM. Whether they will renew. It aggregates behavioral and relationship signals into a prediction: given everything we know about this account, how likely is it that they sign again? A health score is a model. Like all models, it's wrong — but it's wrong in knowable ways, and understanding its failure modes is what separates a CS org that catches risk early from one that is perpetually surprised by churn.

The metric that anchors CS is **NRR**: the percentage of last period's ARR that remains this period, including expansion and contraction, excluding new logos. NRR > 100% means the installed base is growing on its own. NRR < 100% means churn is eating new bookings. Elite SaaS runs 120%+ NRR. A CS org that doesn't track NRR is running a support org with a different name. Benchmarks vary significantly by ARR tier, go-to-market motion, and industry — see sources.md for current benchmarks.

---

## What CS actually is

Customer success is the post-sale function responsible for net revenue retention — keeping customers, expanding them, and ensuring the combination exceeds churn. The CS org does not exist to make customers happy. It exists to make customers successful enough that they renew and expand. These correlate but are not the same.

A customer can be satisfied and still churn: the product solved their problem, the problem went away, they don't need renewal. A customer can be frustrated and still renew: switching cost is too high, the product is embedded, they've already bought the vision. CS must understand why customers actually stay — and that understanding comes from behavioral signal, not survey data.

## Reactive vs. proactive CS

**Reactive CS** responds to problems after they surface — tickets, complaints, escalations, explicit non-renewal signals. This is the default in understaffed or early-stage CS orgs. It is not a strategy; it is managed decline.

**Proactive CS** intervenes before problems surface. Monitors health signals, executes against playbooks tied to lifecycle stages, gets ahead of at-risk situations before customers know they're at risk. This is the form that generates strong NRR.

The shift from reactive to proactive requires:
1. A health scoring model that surfaces risk before the customer says anything
2. Playbooks that trigger off health signals, not off inbound requests
3. Sufficient CSM capacity to act on the triggers — proactive CS that generates alerts no one acts on is worse than nothing (it creates the illusion of process while the org stays reactive)

---

## How health scores work and what they actually predict

A health score predicts renewal probability. It aggregates behavioral and relationship signals into a composite that answers: **"How likely is this customer to renew?"**

Common input signals, roughly in order of predictive value:

**Product adoption** — the single most predictive category. Are users using the features that correlate with long-term retention in your cohort data? Feature breadth, login frequency, power-user ratio, and activation of sticky features are higher-signal than raw login counts. An account where one user logs in daily but no one else has activated in six months is not highly adopted. The specific features that predict retention vary by product — cohort analysis, not intuition, identifies them.

**Engagement with CS** — are they showing up to QBRs, responding to check-ins, attending trainings, escalating issues (escalation is engagement, not churn signal). Ghosting is a serious at-risk signal. An account you haven't spoken to in 60 days is not healthy regardless of product usage.

**Support ticket volume and sentiment** — high volume with unresolved issues is a risk signal. High volume with fast resolution is often a positive (the product is being used; issues get fixed). Ticket sentiment and escalation patterns matter more than raw count.

**Stakeholder map completeness** — do you know the economic buyer, the champion, the admin, and the end-user sponsor? Champion departure is one of the highest-risk events a CS org faces; it's invisible without a stakeholder map. Missing stakeholders = unknown risk.

**Contract signals** — time to renewal, contract value trajectory (expanding vs. flat vs. declining), multi-year vs. annual.

**NPS/CSAT** — a lagging, incomplete signal. Better than nothing for accounts that respond; the non-response rate (~60–70% in most programs) is its own signal. Do not over-weight NPS in health scores.

Health scores are only as good as the signal coverage of the accounts they model. Accounts with sparse data produce unreliable health scores. Data completeness is itself a health metric.

---

## What agents get wrong

**Health score as vanity metric.** A health score that tracks "green" because the CSM manually overrode it, because no one updated the champion field after a departure, or because login data is stale is not a health score — it's theater. The score is only useful if the input signals are current and honest. An agent that accepts a green health score at face value without checking signal freshness will miss risk that a human CSM would catch in a five-minute account review.

**Confusing engagement with adoption.** A customer who attends every QBR and responds to every check-in but hasn't activated the core workflow is engaged but not adopted. Engagement without adoption is a retention risk wearing a green flag. The question is not "are they talking to us?" — it's "are they embedded in the product in ways that create switching cost?"

**Treating all at-risk signals the same.** A low health score driven by low product adoption requires a different intervention than one driven by champion departure, which requires a different intervention than one driven by unresolved support escalations. Agents that receive "at-risk account" as a trigger and produce a generic check-in template have collapsed three different playbooks into one. The root cause determines the response; skipping diagnosis guarantees the wrong play.

**Reactive intervention timing.** By the time a customer names the risk — a renewal conversation starting with "we're evaluating whether to continue" — they've usually already decided. Proactive CS catches the signals 60–90 days before that conversation happens: declining usage, missed QBRs, a champion who stopped responding, a new IT contact who wasn't on any prior calls. Agents working from inbound signals are always too late.

**QBRs that report instead of advance.** A quarterly business review that summarizes usage statistics and recaps what the product did is a reporting exercise, not a QBR. Its function is to re-anchor the relationship on business outcomes, surface the customer's evolving priorities, identify gaps between what was promised and what was delivered, and create mutual accountability for the next quarter. A QBR without at least one customer commitment — a next step, an expansion conversation, an escalation resolution, an introduction to a new stakeholder — is a missed opportunity.

**NPS as a churn predictor.** NPS measures a feeling at a point in time. An account can score 9 and churn six months later because the champion left, the use case was solved, or the company was acquired. An account can score 6 and renew because the product is embedded in critical workflows. Weight behavioral signals over sentiment signals. NPS is useful for identifying detractors to rescue, not for forecasting renewal.

**Running expansion on unhealthy accounts.** Upsell conversations require a healthy foundation: the customer is achieving value, has an advocate, and sees growth in their use case. Attempting expansion on an account with declining usage, an unresolved escalation, or a departing champion accelerates churn. Health scoring gates expansion; it doesn't just gate retention.

---

## What AI is changing

**What AI is improving:**

- **Automated health scoring at scale.** ML models trained on cohort data can weight adoption signals more accurately than hand-tuned scoring rubrics, surface accounts that a manual review would miss, and flag leading indicators (feature usage drop, login frequency decline) weeks before they compound. At high account volumes, AI health scoring catches patterns no human team could track manually.
- **Churn prediction.** Predictive models trained on historical churn patterns can score renewal probability at the account level — not just "yellow/red" but "73% renewal probability" — giving CS orgs a prioritization layer they didn't have before. The quality of prediction depends entirely on the quality and recency of training data.
- **Next best action.** AI can recommend which playbook to run, which contact to reach out to, and what the message should be anchored to — given the account's health signal, contract position, and historical engagement. This reduces the cognitive load on CSMs managing large account books.
- **Digital CS at scale for long-tail customers.** For SMB and self-serve segments where 1:1 CSM coverage isn't economically viable, AI-driven digital CS — automated playbooks, personalized in-app interventions, smart email sequences triggered by behavioral signals — can approximate proactive CS at a fraction of the cost. The ceiling is lower than human CS, but the floor is far higher than no CS at all.

**What stays human:**

- **Strategic account relationships.** Enterprise accounts with complex buying committees, multi-product footprints, and high renewal stakes need a CSM who understands the account's internal politics, can read the room in an executive conversation, and can escalate credibly when something breaks. AI can brief the CSM; it can't replace the relationship.
- **Executive sponsorship conversations.** When an account is at risk at the C-level — the economic buyer is churning, an executive sponsor has left, or the account relationship needs to be reset at the top — the intervention is a human-to-human executive call. No automated sequence recovers an executive relationship.
- **Complex escalations.** Escalations that involve product failures, SLA breaches, or broken commitments require human judgment about what to offer, how to frame accountability, and when to involve leadership. AI can help draft the response; it can't own the accountability.
- **Champion development.** Identifying who inside a customer organization has the potential to become a champion — someone who will advocate internally, defend the budget, and expand the relationship — requires reading behavior and ambition over time. AI can surface engagement signals; the actual development work is relationship-driven.

Fetch playbook.md for the six canonical CS playbook frameworks. Fetch sources.md for current CS methodology resources.
<!--fold:65cd01@file path="playbook.md" mode="644"-->
# CS Playbook

Six canonical CS playbooks as decision frameworks. Not scripts — trigger logic, goals, agent actions, success metrics, and failure modes. The right playbook depends on where the account is in its lifecycle and what's driving the health signal, not on what the CSM has bandwidth for this week.

---

## 1. New customer onboarding

**Trigger conditions:** New logo signed. Contract executed. Handoff from sales to CS.

**Goals:** Activate the account (defined feature usage achieved), establish a success plan with measurable milestones, surface the right stakeholders, set the cadence for the relationship.

**Time window:** Days 0–90. The first 90 days determine long-term retention probability more than any other phase. Customers who don't activate and adopt in the first quarter almost never become long-term retainers, regardless of subsequent CS effort.

**Agent actions:**
- Send kickoff email within 24 hours of contract close — reference the specific outcomes the customer bought for, not generic onboarding language
- Schedule kickoff call within 5 business days — agenda: introductions, success plan review, technical setup, key contacts, next 30-day milestones
- Build a stakeholder map: economic buyer, day-to-day champion, admin/IT contact, end-user sponsor — missing any of these is a risk. Get this in writing in the first 30 days.
- Configure activation milestones in the CS platform (first login, first key workflow completed, first team member added, first integration connected) — these are leading indicators of renewal. The specific milestones that predict retention are product-specific; use cohort data, not intuition.
- Send weekly progress check-ins for the first month; transition to bi-weekly once activation milestones are hit
- Flag any account that hasn't hit day-30 milestones — escalate to CSM, not automated email

**Success metrics:** Time to first activation milestone, feature breadth at 60 days, stakeholder map completeness, day-90 health score.

**Common failure modes:**
- Treating onboarding as a project (finite, done when complete) rather than a lifecycle phase (foundation for everything that follows)
- Under-resourcing onboarding to free up CSM time — this is borrowing from future NRR
- Letting sales handoff go stale (>5 business days before CS contact) — intent peaks at signature
- Onboarding to features rather than outcomes — teaching the product instead of mapping the product to the customer's specific goals
- Not building the stakeholder map in the first 30 days — champion departure becomes invisible risk

---

## 2. Executive business review (EBR / QBR)

**Trigger conditions:** Quarterly for strategic accounts; semi-annual for commercial accounts. Also triggered on: contract renewal within 90 days, expansion conversation ready to open, significant product change that affects the account.

**Goals:** Re-anchor the relationship on business outcomes (not usage metrics). Surface the customer's evolving priorities. Create mutual accountability for the next quarter. Identify expansion readiness or risk.

**Agent actions:**
- Pull 4 data points before building the agenda: (1) stated goals from the last QBR or success plan, (2) product usage trends, (3) open escalations or unresolved support issues, (4) contract details (renewal date, expansion opportunity, prior upsells)
- Build the agenda around the customer's business goals, not around product usage slides — "how are you tracking against your Q2 targets?" not "here's how many logins you had"
- Draft 3 questions the CSM should ask in the call — at least one should be about the customer's priorities shifting, not about the product
- Every QBR should produce at least one customer commitment: a next step, an expansion conversation to schedule, an introduction to a new stakeholder, an escalation resolution plan. A QBR without a customer commitment is a missed opportunity.
- Send agenda 5 business days in advance; get confirmation. A QBR that isn't confirmed 48 hours out is likely to be cancelled — escalate, don't assume.
- Do not run a QBR on an account with an unresolved escalation — fix the escalation first. A QBR on a broken relationship is a liability.

**Success metrics:** QBR held (not cancelled), at least one customer commitment documented, renewal probability updated, expansion opportunity identified or closed.

**Common failure modes:**
- Building a QBR deck that reviews usage statistics rather than business outcomes — reporting is not a review
- Letting the QBR run without a clear ask — "just wanted to check in" leaves with nothing
- Scheduling QBRs at renewal time only — by then, it's too late to change the trajectory
- No agenda sent in advance — unprepared executives cancel
- Confusing a status update call with a QBR — different cadence, different participants, different outcomes

---

## 3. Expansion / upsell trigger

**Trigger conditions:** All of the following must be true — health score green (or yellow with a documented explanation), product adoption of core tier strong (breadth + depth), an expansion signal present (power users hitting plan limits, new use case emerging, team growth, stakeholder map showing new department contact).

**Goals:** Identify the right expansion motion (seat expansion, tier upgrade, adjacent product, new department), qualify the conversation, advance to AE if deal size warrants.

**Agent actions:**
- Check health score gate before any expansion action — do not run this playbook on yellow or red accounts without explicit CSM override and documented rationale
- Identify the specific signal driving expansion readiness: seats, usage ceiling, new team, new use case — the conversation must be anchored to this signal, not to "we have more products"
- Identify who owns the buying conversation — is it the existing champion, or does it require reaching the economic buyer?
- Draft the expansion framing: "You've been doing X with the product; there's a natural next step that solves Y" — not "we have an upsell opportunity"
- Involve AE for deals over deal-size threshold (threshold should be set by CS/Sales alignment, not by the agent); CSM handles below threshold
- Set an explicit close timeline: expansion conversations that stretch past 60 days without a decision usually stall permanently

**Success metrics:** Expansion opportunity qualified, handoff to AE if applicable, expansion ARR added.

**Common failure modes:**
- Running expansion on accounts with declining usage or unresolved escalations — accelerates churn, damages trust
- Anchoring the conversation to the product ("we have a new module") rather than the customer's outcome ("you're hitting the ceiling on X")
- Not involving the economic buyer — champion enthusiasm without budget authority stalls
- Over-relying on automated upsell triggers without CSM qualification — the signal must be reviewed, not auto-actioned
- Conflating expansion readiness with satisfaction — a happy customer with no growth signal is not an expansion target

---

## 4. At-risk intervention

**Trigger conditions:** Health score drops to yellow or red. Specific risk signals: usage declining for 30+ days, QBR missed or cancelled, champion departure confirmed or suspected, unresolved escalation open >14 days, NPS response below threshold, no CS contact in 60+ days, renewal in <90 days with no active conversation.

**Goals:** Diagnose the root cause of risk (not all at-risk signals are the same), arrest the decline, re-establish contact and commitment, assess whether renewal is recoverable.

**Agent actions (diagnosis first):**
- Identify which signal is driving the at-risk status — the intervention depends entirely on the root cause:
  - Low adoption → onboarding gap or use-case shift; intervention is re-activation (bring back champion + hands-on session)
  - Champion departure → stakeholder map intervention; find the new champion before the old one leaves completely, map to economic buyer (see Playbook 6: Executive sponsor change)
  - Unresolved escalation → escalation resolution is the only priority; do not attempt a relationship conversation until the escalation is closed
  - Ghosting (no contact in 60+ days) → multi-channel outreach to re-establish contact; escalate to manager-to-manager if initial outreach fails within 10 days
  - Renewal-imminent with no conversation started → treat as urgent; immediate outreach, offer an EBR or executive sponsor call

- Draft outreach that names the specific concern — do not send a generic check-in. "I noticed usage has dropped significantly over the last 6 weeks — I'd like to understand what's changed and whether there's something we can do differently" is better than "just checking in to see how things are going."
- Escalate to executive sponsor if standard CSM outreach is not landing within 10 days
- Document the risk assessment: what's the recovery probability, what would it take to recover, and is this account worth the intervention cost?
- Keep at-risk intervention separate from renewal conversation — the customer interprets simultaneous pressure as transactional

**Success metrics:** Contact re-established, root cause identified, recovery plan in place with customer commitment, health score improvement within 30 days.

**Common failure modes:**
- Treating all at-risk signals as the same — sending adoption outreach to an account where the champion just left is the wrong play
- Waiting for the customer to say something — by the time they name the risk, they've usually already decided
- Running at-risk intervention and renewal conversation simultaneously — the customer interprets this as transactional; separate them
- Generic "how are you doing" outreach that doesn't name the specific signal — tells the customer you're not paying attention
- Not escalating when standard outreach isn't working — CSM-level contact has a ceiling; manager/executive involvement changes the dynamic

---

## 5. Renewal

**Trigger conditions:** 90 days before renewal date for strategic accounts; 60 days for commercial; 30 days for SMB/self-serve.

**Goals:** Secure the renewal (prevent churn), identify any contraction risk and counter it, set up the next contract term with expansion opportunity identified.

**Agent actions:**
- Run a pre-renewal health check before initiating the conversation: health score, open escalations, stakeholder map completeness, expansion signals. Do not start a renewal conversation on an account with an unresolved escalation.
- Confirm the economic buyer is still the right person — stakeholder changes happen silently; a renewal conversation with the wrong person fails
- Draft the renewal proposal anchored to documented outcomes: "In the past year, you achieved X. The next contract term sets you up for Y." — not a bill-of-materials quote
- Identify and address contraction risk early — if the customer's use case has shrunk (team layoffs, product pivot, budget cut), proposing the same contract value accelerates churn. A smaller renewal is better than a lost renewal.
- Set a renewal meeting at -90 days; get a decision target date. A renewal conversation without a target decision date will drift past the renewal date.
- At -30 days: if unsigned, escalate. Renewals that reach -7 days without a signature are high-risk even if the customer says "we're renewing."

**Success metrics:** Renewal signed on or before contract end date, NRR impact (contraction, flat, or expansion), time from renewal conversation start to signature.

**Common failure modes:**
- Starting the renewal conversation too late — at -90 days you have time to diagnose and address concerns; at -30 you're negotiating under pressure
- Proposing the same contract without confirming it still fits the customer's actual usage and use case
- Not addressing contraction risk proactively — customers who want to downsize will sign a smaller contract; customers who want to downsize but are offered a full renewal will churn instead
- Treating renewal as a finance/legal handoff — the CSM owns the renewal relationship; operations processes the paperwork
- Letting auto-renew mask churn — auto-renew delays the churn signal, it doesn't eliminate it

---

## 6. Executive sponsor change

**Trigger conditions:** Champion or economic buyer departure confirmed or suspected. New executive contact appears in the account that hasn't been mapped. LinkedIn activity suggesting job transition for a key stakeholder. Outreach to primary contact goes unanswered for 14+ days with no explanation.

**Goals:** Identify and map the new stakeholder before the relationship gap widens. Establish credibility with the new contact anchored to business outcomes, not product features. Prevent the renewal risk that follows every unchecked sponsor change.

**Why this is a separate playbook:** Champion departure is the single highest-risk event in CS that doesn't show up immediately in product usage data. A champion who's leaving often stops engaging 30–60 days before their last day — they're not going to escalate anything, they're not going to renew anything, they're just going to stop responding. By the time the new contact is in the role, the relationship narrative has been lost. This playbook exists to catch the gap before it becomes a churn.

**Agent actions:**
- On departure signal: immediately identify who the new economic buyer or champion is. Check LinkedIn, ask the outgoing contact directly ("Who should I connect with as you transition?"), check the CS platform's stakeholder map for any recently added contacts.
- If the departing stakeholder is reachable: schedule an explicit transition call — agenda is documentation of the relationship history, open items, and a warm introduction to the new contact. A CSM who manages the offboarding of a departing champion can use that person as an internal reference to the successor.
- First contact with the new stakeholder: anchor to their priorities, not to the product's history with the account. "I'd love to understand what success looks like for you in this role" is the opening. Do not lead with a usage summary. Do not lead with a renewal conversation.
- Build a success plan with the new stakeholder in the first 30 days — this is effectively an onboarding motion inside an existing account. Their context is different from the predecessor's; assume nothing carried over.
- Re-map the full stakeholder structure — champion departure often correlates with organizational change; other contacts may have shifted too.
- Update health score: a confirmed champion departure without a mapped successor moves the account to yellow regardless of usage data.

**Success metrics:** New stakeholder mapped and engaged within 30 days of departure signal. New success plan in place within 60 days. Health score restored to green or yellow with documented recovery path within 90 days.

**Common failure modes:**
- Waiting for the new contact to reach out — they have no context on the relationship, may not know a CSM exists, and have no reason to prioritize the vendor relationship early in a new role
- Leading the new contact with usage statistics and renewal timelines — they don't have the context yet; this reads as pressure, not partnership
- Assuming the departing champion handled the transition internally — they often didn't; the new contact may know nothing about the product's value or the relationship history
- Treating this as a one-contact problem — champion departure often signals broader organizational change; the stakeholder map needs a full refresh
- Not escalating when the new contact is senior and CSM-level outreach won't establish credibility — an executive-to-executive introduction changes the dynamic

---

## Choosing the right playbook

| Signal | Playbook |
|---|---|
| New contract signed | 1. New customer onboarding |
| Quarterly cadence / renewal approaching | 2. EBR / QBR |
| Health green + expansion signal present | 3. Expansion / upsell trigger |
| Health yellow or red / any at-risk signal | 4. At-risk intervention |
| Renewal within 90/60/30 days | 5. Renewal |
| Champion or economic buyer departing | 6. Executive sponsor change |

Playbooks overlap and sequence — a healthy account runs onboarding → QBR → expansion → renewal. An at-risk account interrupts that sequence and pauses the normal cadence until health is restored. Executive sponsor change can interrupt any stage; it often triggers At-risk intervention simultaneously. The sponsor change playbook is not an add-on — run it in parallel with whatever the account's current stage is.
<!--fold:65cd01@file path="sources.md" mode="644"-->
# sources

Fetch these at task time. Ordered by relevance. CS metrics and benchmarks vary significantly by ARR tier, go-to-market motion, and industry — treat all benchmarks as directional until verified against a source matched to the company's profile.

## CS methodology and frameworks

1. Gainsight CS methodology — health scoring, playbooks, lifecycle management, NRR optimization:
   https://www.gainsight.com/guides/

2. Gainsight blog — practitioner-level articles on health scores, QBR design, churn prediction:
   https://www.gainsight.com/blog/

3. Totango blog — CS operations, onboarding-to-renewal lifecycle, CS-led growth:
   https://www.totango.com/blog/

4. Customer Success Collective (CS Insider) — practitioner community, CS playbooks, career development:
   https://www.customersuccesscollective.com/

5. Lincoln Murphy's Customer Success content — the foundational framing of CS as a growth function, not support:
   https://sixteenventures.com/customer-success

## NRR, churn, and SaaS benchmarks

6. Jason Lemkin / SaaStr — NRR benchmarks, churn math, what elite NRR looks like at different ARR bands:
   https://www.saastr.com/category/customer-success/

7. OpenView Partners SaaS benchmarks — NRR, GRR, expansion rate benchmarks by ARR tier and go-to-market motion:
   https://openviewpartners.com/saas-benchmarks/

8. Churn.fm podcast / Recur — practitioner interviews on churn root causes and retention strategy:
   https://churn.fm/

## QBR design and execution

9. Gainsight QBR guide — structure, agenda templates, how to orient QBRs around outcomes not usage:
   https://www.gainsight.com/guides/the-ultimate-guide-to-executive-business-reviews/

10. TSIA research on QBR effectiveness — what QBR formats actually improve retention:
    https://www.tsia.com/resources/

## Expansion and upsell

11. Gainsight expansion playbook guide — when to expand, how to identify accounts ready for upsell:
    https://www.gainsight.com/blog/expansion-playbook/

12. Winning by Design — revenue architecture for CS-led growth, land-and-expand motion:
    https://winningbydesign.com/resources/

## Stakeholder mapping and executive sponsor management

13. TSIA on stakeholder complexity — multi-threaded account management in enterprise CS, managing economic buyer vs. champion dynamics:
    https://www.tsia.com/resources/

14. Gartner B2B buying research — how buying committees work, why champion departure disrupts renewals, multi-stakeholder engagement:
    https://www.gartner.com/en/sales/insights/b2b-buying-journey

## AI in CS

15. Gainsight AI features — predictive health scoring, playbook triggering, churn prediction:
    https://www.gainsight.com/product/gainsight-ai/

16. Totango + Rocketlane — AI-assisted onboarding and automated playbook execution:
    https://www.totango.com/platform/

17. ChurnZero — real-time health scoring and automated play execution for mid-market CS:
    https://churnzero.com/resources/
<!--fold:65cd01@end-->
PORTDOWN_F3A896A4

# ── post ──
MARKER=$(awk '/^---$/ { f++; if (f==2) exit; next } f==1 && /^marker:[[:space:]]/ { sub(/^marker:[[:space:]]+/, ""); print; exit }' "$DEST")
[ -z "$MARKER" ] && { echo "seed: archive has no marker — corrupt" >&2; exit 1; }
awk -v m="$MARKER" -v outdir="$TARGET" '
  BEGIN {
    # Match <!--fold:<m>@file path="X"--> with an optional mode attr after
    # the path (fold emits  mode="644"  on executables).
    file_re = "^<!--fold:" m "@file path=\"([^\"]+)\"( mode=\"[0-9]+\")?-->$"
    end_re  = "^<!--fold:" m "@end-->$"
  }
  $0 ~ end_re { if (current) close(current); exit }
  $0 ~ file_re {
    if (current) close(current)
    line = $0
    sub(/^<!--fold:[^@]+@file path="/, "", line); sub(/".*$/, "", line)
    current = outdir "/" line
    dir = current; sub(/\/[^\/]*$/, "", dir)
    if (dir != current) system("mkdir -p \"" dir "\"")
    printf "" > current
    next
  }
  current { print >> current }
' "$DEST"
SEED_EXTRACTED=$(find "$TARGET" -type f -not -path "$DEST" 2>/dev/null | wc -l)
if [ "$SEED_EXTRACTED" = "0" ]; then
  echo "seed: archive contained no files — refusing to delete the source" >&2
  echo "  archive preserved at: $DEST" >&2
  exit 1
fi
rm -f "$DEST"

echo "" >&2
echo "✓ seed unpacked → $TARGET ($SEED_EXTRACTED files)" >&2
find "$TARGET" -type f | sort | while IFS= read -r _sf; do
  echo "  ${_sf#${TARGET}/}" >&2
done
echo "" >&2
if [ -f "$TARGET/SKILL.md" ]; then
  echo "This seed contains a skill (SKILL.md). Install it in your agent's skills directory." >&2
  echo "" >&2
fi
echo "Install the seed skill if not already installed:" >&2
echo "  https://seed.show/skill" >&2
echo "" >&2
echo "Publisher prompt:" >&2
sed 's/^/  /' >&2 <<'__SEED_PROMPT_END_AC1F2B__'
You have the customer success context. Read README.md for the CS mental model, health score framework, what agents get wrong, and what AI is changing. Read playbook.md for all six intervention playbooks (onboarding, EBR/QBR, expansion, at-risk, renewal, executive sponsor change). Fetch sources.md for methodology. To share your own context bundles: curl seed.show/skill | bash
__SEED_PROMPT_END_AC1F2B__
exit 0