Next Best Action

作者 Zoominfod07402feb2b9無授權條款收錄於 2026年10月8日更新於 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 產生的概覽

根據對話智慧與客戶研究,為銷售交易或客戶關係推薦排序後的下一步行動。

功能
從對話智慧與客戶研究中讀取交易或客戶關係的目前狀態,接著提出一到三個排序後的下一步行動。每個行動都連結到具體的對話證據,並說明理由與預期效果。它也會列出會改變建議的未解問題,並在沒有對話資料時改用客戶研究。
適用情境
當有人詢問針對某個客戶或聯絡人下一步該做什麼、如何推進交易,或希望取得有證據支撐而非一般制式建議時使用。適用於有近期郵件與會議背景的進行中或停滯交易。
執行需求
需要為對話智慧連接郵件或會議來源,並需要 conversation_intelligence 與 account_research 工具,這些工具會消耗 AI 額度。範圍透過 ZoomInfo ID、名稱查詢或特定互動來確定。不包含指令碼。

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.

來源與署名

來源:Zoominfo/zoominfo-mcp-plugin位於skills/next-best-action提交d07402f

授權條款: 無授權條款

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