Instagram DM Automation with AI
Automate Instagram DM triage, FAQ responses, and escalation with AI-powered workflows that understand customer intent.
課題
Instagram has become a primary customer communication channel — brands receive hundreds of DMs daily with product questions, support requests, story replies, and purchase inquiries. Manually triaging and responding to each message is unsustainable. Response times slip, leads go cold, and support teams burn out.
ソリューション
The Instagram DM Automation workflow connects your Instagram Business account to JieGou and lets AI handle the entire inbound pipeline. When a DM arrives, AI reads the message, classifies intent using your knowledge base, drafts a contextual response with confidence scoring, and either auto-sends high-confidence replies or escalates to a human agent. Story mentions and comment-triggered DMs are handled in the same workflow.
ワークフローステップ
Receive Instagram DM
レシピステップWebhook receives the inbound DM via the Instagram Graph API. Extracts message text, sender info, and conversation context.
Classify Intent
レシピステップAI classifies the message intent — product inquiry, support request, order status, complaint, or general question — using your FAQ knowledge base for context.
Check Confidence
条件If confidence score is above threshold (e.g., 85%), auto-respond. Below threshold, route to human agent with AI-drafted suggested response.
Draft Response
レシピステップAI generates a personalized response using knowledge base context, brand voice settings, and conversation history. Supports rich text and link formatting.
Human Review
承認ゲートLow-confidence responses pause for human review. Agent can approve, edit, or reject the AI draft before sending.
Send Reply
レシピステップSends the approved response via Instagram DM API. Logs the interaction for analytics and knowledge base improvement.
期待される成果
- Response time drops from hours to seconds for high-confidence queries
- Support team focuses on complex cases while AI handles routine questions
- Every response is consistent with brand voice and knowledge base accuracy
- Conversation history and intent classification improve over time
- Story mentions and comment-to-DM workflows handled in the same pipeline
ラーニングループの実例
AI handles basic FAQ responses with ~70% confidence. Human agents review and correct most responses, building training signal.
Knowledge base grows from agent corrections. Auto-response rate reaches 50%+ as confidence scoring calibrates to your support patterns.
AI handles 75%+ of inbound DMs autonomously. Response quality matches trained agents. New FAQ entries are auto-generated from successful interactions.
その他のユースケース
リード評価の自動化
新規リードの調査、スコアリング、アウトリーチメールの作成を手作業なしで自動化します。
Marketingブログ・オムニチャネルコンテンツワークフロー
ブログ記事を1本書くと、ソーシャル、メール、ニュースレターのコンテンツが自動生成されます。
Supportサポートチケット解決ワークフロー
1つのフローでチケットの分類、返信草稿の作成、ナレッジベース記事の作成を行います。
HR採用ワークフローの自動化
求人票の自動生成、候補者の一括スクリーニング、面接資料の準備を行います。
Finance請求書処理の自動化
請求書データの自動抽出、差異チェック、承認ルーティングを行います。
Engineeringエンジニアリング・インシデント対応ワークフロー
インシデントの詳細からインシデントレポートの生成、ランブックの更新、ポストモーテムの作成を行います。