Call Coaching

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

Coach a rep on how they handled a specific call — discovery quality, objection handling, talk dynamics, and next-call focus. Name the call if you know it, or let the skill pull recent calls and identify the most likely candidate to confirm. Uses conversation_intelligence to read how the conversation actually went. Use when someone asks "how did I do on the Acme call", "coach me on my last discovery call", "where did I lose them", or wants actionable feedback before the next conversation. Analyzes one call at a time.

AI 產生的概覽

運用對話智慧針對單一通銷售電話為業務代表提供輔導,涵蓋需求探詢、異議處理、談話動態與下次通話重點。

功能
此技能會針對單一通銷售電話產出結構化的輔導回饋。它先透過解析客戶或聯絡人並瀏覽近期會議來找出該通電話,接著分析對話中的需求探詢品質、異議處理、客戶情緒與談話動態。輸出內容包括做得好的地方、可改進之處及具體替代做法、談話平衡的判讀,以及一或兩個下次通話的重點。若沒有逐字稿,它會如實說明,而不是憑空編造評估。
適用情境
適用於業務代表詢問自己在某通電話中的表現、希望就最近一次需求探詢電話獲得輔導、想知道在哪裡失去了客戶,或希望在下次對話前取得可執行回饋的情況。它一次只分析一通電話。
執行需求
需要有效的行事曆或會議整合以瀏覽互動紀錄、至少一個已連接的會議來源以進行對話智慧分析,以及用於分析的 AI 額度。此技能不含指令碼,僅為指示。

Call Coaching

Give a rep specific, actionable feedback on a single call: what worked, what to improve, and what to focus on next time.

Prerequisites

browse_engagements (to find the call) is free but requires an active calendar/meeting integration; conversation_intelligence (to analyze it) requires at least one connected meeting source and consumes AI credits. If the call has no transcript to analyze, say so rather than coaching from assumption.

Input

Provided via $ARGUMENTS:

  • Which call (optional) — an account and/or date. If omitted, the skill identifies the most likely recent call and confirms before analyzing.
  • Focus (optional) — e.g. "discovery", "the pricing objection", "did I talk too much". Targets the coaching.

Workflow

  1. Identify the call. browse_engagements filters by date and by company/contact ID, not by call name, so resolve any named account or contact first via search_companies / search_contacts, then call browse_engagements (engagementType: MEETINGS, sort: -chronological) scoped to that ID and date window and pick the matching meeting from the results. If nothing was named, call browse_engagements for the user's recent meetings, propose the most likely candidate, and confirm it before spending credits. If more than one meeting plausibly matches, ask. Keep the chosen engagement ID.
  2. Analyze how it went. Run conversation_intelligence scoped to that engagement ID. Ask how the rep handled discovery (did they uncover pain, budget, timeline, decision process), how objections were handled, what the customer's reactions and sentiment were, and where the conversation stalled or advanced. Keep the query scoped to this one call.
  3. Coach against good practice. Assess the call against solid discovery and objection-handling fundamentals — open questions over pitching, listening over talking, surfacing next steps, addressing concerns directly. Ground every point in a specific moment from the call; cite what was said. Be candid and useful, not generic. If the transcript is too thin to judge something, say so rather than inventing a critique.

Output Format

Call coaching — [Call title, date]

What went well (2-3) — specific strengths, each tied to a moment in the call.

What to improve (2-3) — the highest-leverage changes, each with the moment that shows it and a concrete alternative ("when they raised price, you discounted; instead anchor on the value point from earlier").

Talk dynamics — a quick read on balance (who drove, listening vs pitching, questions asked) if the data supports it.

Focus for the next call — one or two things to do differently next time, tied to where this deal now stands.

When there is no data

If the call cannot be found or has no transcript, tell the user and offer to coach from notes they provide, rather than fabricating an assessment.

來源與署名

來源:Zoominfo/zoominfo-mcp-plugin位於skills/call-coaching提交d07402f

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