Runs the ongoing relationship with accounts after the sale — segmenting coverage against account value, building a health score that predicts rather than describes, running reviews customers find worth attending, forecasting renewals honestly, and finding expansion that follows usage instead of quota. Use this to design a customer success motion, decide who gets a named contact, work out why renewals surprise you, or fix a health score everyone ignores.
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This is the motion that keeps accounts, as distinct from diagnosing why they leave — for the
churn analysis itself, see revenue:retention. The failure this discipline exists to prevent is
finding out at renewal.
Coverage is a cost decision and it should be made explicitly rather than by whoever shouts.
Assign by what the account needs, not only by what it pays. A large account that is live, stable and happy needs less than a small one mid-implementation.
Most health scores are a weighted average of whatever was available, colored red to green, and trusted by nobody. A useful one is built backwards: take accounts that churned and accounts that renewed, and find what actually differed six months out.
Validate it against outcomes and recalibrate. A score that did not predict last year's churn should not be steering this year's attention.
When one person is your entire relationship, their departure is your renewal risk, and it arrives with no warning. Track how many contacts each account has and treat single-threading as an actionable condition rather than a fact of life.
A business review that presents usage statistics back to the customer wastes both parties' time. The ones people attend cover what they set out to achieve, where they actually are against it, what is in the way, and what changes next — with the customer talking for at least half of it.
Frequency should follow value and risk, not a uniform quarterly cadence applied to everyone.
Renewal forecasting is more predictable than new business and is often done worse, because everything is assumed to renew until it does not.
Start the renewal conversation far enough ahead that a problem is still fixable — for an annual contract that is months, not weeks. Track renewals in stages with entry criteria, and separate gross retention from net so expansion cannot mask a leak underneath it.
Auto-renewal is a billing mechanism, not a relationship. An account that auto-renewed while disengaged is next year's churn with a delay.
The credible expansion conversation comes from something observable: they hit a limit, adopted the thing that leads to the next thing, added a team. Expansion pushed on a quota calendar into an account that has not realized its original purchase is how a renewal gets lost while chasing a smaller number.
Customer success platforms: Gainsight, Totango, ChurnZero, Vitally, Planhat, and similar. They earn their cost once you have more accounts than a person can hold in their head and product usage data worth joining to the account record — before that, the CRM plus a usage query does the job.
Renewal and expansion tracking belongs in the CRM alongside new business, not in a separate system, or the forecast will exist twice and disagree.
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概要と使いどころ
Designs and audits who can reach what — authentication, authorization models, privileged access, service credentials, and joiner-mover-leaver process. Use this to design a permissions model, run an access review, reduce standing privilege, handle offboarding, set up SSO or MFA, manage service and machine credentials, or diagnose why permissions have sprawled.
日本語の概要は準備中です。原文の説明を表示しています。
Concentrates marketing and sales effort on a named set of accounts rather than on volume — qualifying whether the model fits your economics at all, building the account list and the buying group inside each, tiering effort against account value, coordinating so the account experiences one campaign rather than several, and measuring account progression instead of leads. Use this to decide whether to run an account-based program, build one, or work out why an existing one produces activity and no pipeline.
日本語の概要は準備中です。原文の説明を表示しています。
Gets new users from signup to first real value — signup flow, onboarding, time-to-value, and the early experience that determines whether someone becomes a user or a lapsed account. Use this to design or fix signup and onboarding, diagnose why signups do not convert to active use, reduce time-to-value, or decide what a new user must accomplish first.
日本語の概要は準備中です。原文の説明を表示しています。
Designs orchestrator-and-subagent hierarchies for a repository — splitting agents by exclusive write surface, pairing every producer with an independent auditor, and enforcing the split with a script that runs in CI. Use this whenever the user wants to set up, expand, audit, or fix a multi-agent or subagent structure for a codebase; asks how to divide work between agents; wants agent charters, roles, or a surface map written; or is hitting agents that collide on the same files, review their own work, or drift from their remit. Also use when sizing a roster or deciding whether a new agent is justified.
日本語の概要は準備中です。原文の説明を表示しています。
Governs models and AI systems in production — intended use, evaluation, monitoring, human oversight, documentation, and the decision to deploy or retire. Use this before deploying a model or AI feature, when defining evaluation criteria, when a model's behavior has drifted, when assessing AI risk or regulatory exposure, or when deciding whether an AI system is fit for a consequential decision.
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Produces executive-level research — market sizing, competitor mapping, trend analysis, and strategic intelligence — grounded in cited sources with the confidence in each claim made explicit. Use this to analyze a market or industry, map competitors, evaluate a market-entry or build-versus-buy decision, produce a research brief, or assemble evidence for a decision. Also use when comparing options that need a structured, evidence-based verdict rather than an opinion.
日本語の概要は準備中です。原文の説明を表示しています。