問題への対処方法は、成功への対処方法以上にブランドを定義します。これらのプロンプトは、不満を鎮める回答の作成、初回コンタクトでの問題解決、怒った顧客を最大のファンに変える手助けをします。ChatGPT、Gemini、Claudeでテスト済みなので、最も冷静に対処できるモデルがわかります。
| やりたいこと | 最適な用途 |
|---|---|
| 怒っている顧客を落ち着かせる | Claude |
| 一般的な苦情への対応テンプレートを構築する | ChatGPT |
| 顧客の問題の根本原因を特定する | Gemini |
| エスカレーション対応プロセスを構築する | Gemini |
| 効果的な謝罪文を作成する | Claude |
| サービス障害からのリカバリー計画を立てる | ChatGPT |
プロンプト
怒っている顧客を落ち着かせる
Help me de-escalate this customer situation: What happened: [describe the issue] Customer's emotional state: [angry / frustrated / disappointed / threatening to leave] What they said: [paste their exact message or describe the call] What we can actually do: [your constraints and options] Relationship history: [new customer / long-time customer / VIP] Provide: 1. An opening response that validates their emotion without admitting fault prematurely 2. A bridge statement that transitions from empathy to problem-solving 3. Three resolution options to offer (good / better / best) 4. Language to avoid (phrases that make angry customers angrier) 5. A follow-up message to send 24 hours after resolution 6. An internal escalation template if I can't resolve it myself
最適な用途: CLAUDE
Claudeは最も共感的なエスカレーション緩和スクリプトを作成し、防御的にならずに顧客の感情を認めるトーンが優れています。
テスト済み Feb 15, 2026
プロのコツ
最初の30秒は何も解決しようとしないでください。まず聞いて認めましょう。「それは本当にご不便をおかけしましたね」という一言が、即座に解決策を提示するよりも効果的です。
一般的な苦情への対応テンプレートを構築する
Build a complaint response library for [business type]. Top 10 complaints we receive: [List each complaint category with approximate frequency] Brand voice: [professional / friendly / casual] Response time goal: [hours/minutes] Channels: [email, chat, phone, social media] For each complaint, create: 1. An empathy-first response template (customizable with [brackets]) 2. Resolution steps the agent should take 3. Compensation guidelines: when to offer what 4. Escalation criteria: when this needs a manager 5. A prevention note: what to flag for the product/ops team 6. A 'win-back' follow-up message for after the issue is resolved
最適な用途: CHATGPT
ChatGPTは最も多様な状況に対応する苦情テンプレートを作成し、テンプレートでありながらパーソナライズされた印象を与える書き方が得意です。
テスト済み Feb 15, 2026
プロのコツ
テンプレートは出発点であって最終形ではありません。各テンプレートにパーソナライズすべきポイントを2〜3箇所マークしましょう。完全にテンプレート化された返信は、返信しないのと同じくらい悪いです。
顧客の問題の根本原因を特定する
Help me find the root cause of this recurring customer issue: The symptom: [what customers report] Frequency: [how often it happens] Affected segment: [which customers experience it] Timeline: [when it started or got worse] What we've tried: [fixes attempted so far] Data available: [logs, tickets, metrics you have] Conduct a root cause analysis: 1. Five 'why' analysis: drill from symptom to root cause 2. Contributing factors: what makes this issue worse or more frequent 3. A fishbone diagram structure (categories: people, process, product, environment) 4. The most likely root cause with evidence reasoning 5. Three fix options: band-aid, medium-term, permanent solution 6. A measurement plan: how to verify the fix actually worked
最適な用途: GEMINI
Claudeは最も体系的な根本原因分析を行い、症状ではなく本当の原因を掘り下げます。「5つのなぜ」テクニックの適用が最も効果的です。
テスト済み Feb 15, 2026
プロのコツ
同じ問題が3回以上報告されたら、それは個別の問題ではなくシステムの問題です。パターンを見つけてAIに構造的な解決策を提案させましょう。
エスカレーション対応プロセスを構築する
Help me build an escalation framework for our support team. Team structure: [tiers, roles, managers] Ticket volume: [daily/weekly] Current escalation process: [what exists now, or nothing] SLA targets: [response and resolution times] High-risk scenarios: [situations that need immediate attention] Design an escalation playbook: 1. Escalation tiers: what gets handled at each level 2. Trigger criteria: specific signals that require escalation 3. Response templates for each escalation level 4. Communication protocol: who gets notified and how 5. SLA adjustments: how timelines change at each tier 6. Post-escalation review: learning from every escalated case
最適な用途: GEMINI
Geminiは最も明確なエスカレーション基準と対応フローを作成します。各レベルの対応者、タイムライン、コミュニケーションテンプレートが整理されています。
テスト済み Feb 15, 2026
プロのコツ
エスカレーションのタイミングを明確にしましょう。「必要に応じて」では遅すぎます。「解決策を提示後30分以内に受け入れられない場合」のような具体的な基準を設定しましょう。
効果的な謝罪文を作成する
I need to apologize to a customer (or group of customers) for [describe the mistake/issue]. What went wrong: [be specific about the failure] Impact on customers: [how it affected them] Our fault level: [fully our fault / partially / external factor] What we're doing to fix it: [concrete steps taken] Compensation available: [what you can offer] Write: 1. A direct apology that takes ownership without corporate hedging 2. A clear explanation of what happened (honest, not defensive) 3. Specific steps we're taking so it won't happen again 4. Compensation or goodwill gesture with proper framing 5. A mass email version (if this affects many customers) 6. A personal version for high-value customers with extra care
最適な用途: CLAUDE
Claudeは最も誠実な謝罪文を作成し、責任を認めつつ前向きな解決策を提示するバランスが優れています。
テスト済み Feb 15, 2026
プロのコツ
「もしご不便をおかけしていたら」ではなく「ご不便をおかけしました」と言いましょう。条件付きの謝罪は謝罪ではありません。問題を認め、対策を伝え、補償を提案しましょう。
サービス障害からのリカバリー計画を立てる
A customer had a bad experience and I want to turn them into an advocate. Original issue: [what went wrong] How we resolved it: [what we did to fix it] Customer's current sentiment: [still upset / neutral / pleasantly surprised] Customer value: [lifetime value or tier] Relationship length: [how long they've been a customer] Build a service recovery plan: 1. A surprise follow-up gesture 1 week after resolution 2. A personalized check-in message at 30 days 3. An invitation to provide input on preventing similar issues 4. A loyalty program or exclusive offer as a genuine thank-you 5. A referral opportunity that benefits them (not just you) 6. A long-term relationship plan: quarterly touches that show you remember
最適な用途: CHATGPT
ChatGPTは最も包括的なリカバリー計画を作成し、即座の対応から長期的な信頼回復まで段階的なアプローチを提供します。
テスト済み Feb 15, 2026
プロのコツ
サービス障害後の最良の顧客は、最も怒っていた顧客になることが多いです。彼らの怒りに真摯に対応すると、最も忠実なファンに変わります。
実際のテストに基づいています — 推測ではありません。 テスト方法を見る
Gemini
Best for root cause analysis and escalation frameworks. Produces logical, structured systems that support teams can implement immediately. Less effective at writing emotionally sensitive customer responses.
結果元: Gemini 2.0 Flash · テスト済み Feb 15, 2026ChatGPT
Best for complaint response libraries and service recovery. Writes natural templates that agents can personalize quickly. Tends to over-apologize — push for specific action language instead.
結果元: GPT-4o · テスト済み Feb 15, 2026Claude
Best for de-escalation and genuine apologies. Reads emotional context deeply and writes responses that feel human. Sometimes too cautious with compensation recommendations — push for specific offers.
結果元: Claude 3.5 Sonnet · テスト済み Feb 15, 2026Grok
Delivers quick, practical solutions to customer issues without overcomplicating the resolution process. Best for straightforward problem-solving where speed matters more than ceremony. Less effective at writing empathetic, emotionally sensitive responses for upset or frustrated customers.
結果元: Grok 2 · テスト済み Feb 15, 2026Resolve the emotion before you resolve the issue. An angry customer can't hear your solution until they feel heard. Spend the first 2-3 sentences purely acknowledging their frustration before pivoting to problem-solving. Jumping to solutions too fast makes them angrier.
Measure first-contact resolution, not ticket volume. A team that closes 100 tickets but reopens 30 is less effective than a team that closes 70 and reopens 5. Track how often customers come back with the same issue — that's your real quality metric.
Document every resolution for future agents. Every solved issue is training data for your team. Build a searchable knowledge base of past resolutions so agents don't reinvent solutions for problems you've already fixed.