Next Best Action

作者 Zoominfod07402feb2b9无许可证收录于 2026年10月8日更新于 2026年10月8日

Recommend the next best action on a deal or relationship, grounded in the current conversation state. Uses conversation_intelligence as the primary source, with account_research for deal context. Identify the account or contact by ZoomInfo ID (preferred) or name (triggers a lookup), or point it at a specific engagement. Use when someone asks "what should I do next with Acme", "what's my next move here", "how do I advance this deal", or wants an evidence-based recommendation rather than a generic playbook. Reasons over the last few engagements only.

AI 生成的概览

基于对话智能和客户研究,为销售交易或客户关系推荐排序后的下一步行动。

功能
从对话智能和客户研究中读取交易或客户关系的当前状态,然后提出一到三个排序后的下一步行动。每个行动都关联具体的对话证据,并说明理由和预期效果。它还会列出会改变建议的未解问题,并在没有对话数据时回退到客户研究。
适用场景
当有人询问针对某个客户或联系人下一步该做什么、如何推进交易,或希望获得有证据支撑而非通用套路的建议时使用。适用于有近期邮件和会议背景的活跃或停滞交易。
运行要求
需要为对话智能连接邮件或会议来源,并需要 conversation_intelligence 和 account_research 工具,这些工具会消耗 AI 额度。范围通过 ZoomInfo ID、名称查询或特定互动来确定。不包含脚本。

Next-Best-Action

Read the current state of the conversation and recommend the one or two moves most likely to advance it.

Prerequisites

conversation_intelligence requires at least one connected email or meeting source; conversation_intelligence and account_research consume AI credits. If no conversation data exists, base the recommendation on account_research and say the read is limited, pointing the user to their ZoomInfo admin.

Input

Provided via $ARGUMENTS:

  • Scope (required) — an account, a contact, or a specific engagement (ID, or a name to resolve).
  • Goal (optional) — e.g. "get to a technical eval", "close this quarter", "re-engage a stalled deal". Sharpens the recommendation.

Workflow

  1. Resolve scope. Use a ZoomInfo ID directly, or resolve via search_companies / search_contacts and confirm an ambiguous match before spending credits (conversation_intelligence and account_research both cost AI credits, so a wrong resolution burns them). For a specific call not named, offer a browse_engagements shortlist first.
  2. Read the state. Run conversation_intelligence scoped to the account/contact/engagement for where things stand: open threads, stated next steps, blockers, buying signals, and unanswered questions. Pull account_research for deal stage and stakeholder context. Keep CI scoped to one ID; it sees only the last few engagements and cannot search by topic or count, so reason from what it returns.
  3. Recommend. Propose one to three concrete next actions, ranked, each tied to specific evidence from the conversations and aimed at the stated goal. For each, give the move, why now (the evidence), and the expected effect. Skip generic advice — if the evidence does not support a confident recommendation, say what is missing and what to find out next instead.

Output Format

Next best action — [Account / Contact]

State of play — 2-3 lines on where things stand right now, from the conversations.

Recommended moves (ranked, 1-3):

  1. [The move] — Why now: [evidence from a specific conversation]. Expected effect: [what it unlocks].

What we don't yet know — the open question(s) that would most change the recommendation, and how to get the answer.

When there is no data

If conversation data is unavailable, give the best account_research-based suggestion and flag that it is not grounded in recent conversations.

来源与署名

来源:Zoominfo/zoominfo-mcp-plugin位于skills/next-best-action提交d07402f

许可证: 无许可证

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