Draft a Customer Support Process for an Industrial SME (B2B)
This prompt generates a complete customer support process adapted to the constraints of an industrial SME, with SLAs, channels, and escalation.
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Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.
Draft a customer support process for an industrial SME (B2B) specializing in [industry_sector, e.g., machining, precision mechanics, metalworking]. The process must cover the following steps:
- Request Reception: specify channels (phone, email, web form, client portal), hours (define [business_hours, e.g., 8am-6pm weekday]), and first acknowledgment deadline (e.g., 1 business hour).
- Qualification and Categorization: describe how to sort requests by criticality (critical, high, normal) and type (technical, commercial, after-sales service) based on [products_services, e.g., CNC machines, spare parts, maintenance].
- Resolution: detail the diagnostic steps, escalation to [technical_team, e.g., engineering department] and use of [tools, e.g., CRM, ERP, knowledge base]. Include precise SLAs for each criticality (e.g., critical < 4h, high < 24h, normal < 48h).
- Closure: customer confirmation process, NPS satisfaction survey, and knowledge base update.
- Escalation Rules: if unresolved within SLA, escalate to [manager, e.g., workshop manager] after [escalation_delay, e.g., 2h].
SME constraints: simple process, limited resources, priority on responsiveness. Use precise industrial vocabulary (MTTR, MTBF, wear parts, maintenance schedule). Provide a summary table of SLAs and a checklist for the operator.
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Why this prompt works
This prompt is designed to obtain a customer support process tailored to industry. It integrates sector specifics: technical vocabulary (MTTR, MTBF), production constraints, and limited resources typical of SMEs. The user must replace the variables in square brackets with their company's actual data. For optimal results, prepare the following information in advance: industry sector, business hours, product types, target technical team, and tools used. The prompt generates realistic SLAs and an adapted escalation procedure. Use this prompt in a conversational AI agent or text generator. The result can be exported to a document to train teams or integrated into a CRM. Test it with your SME's data and adjust if necessary.
Use Cases
Expected Output
A structured process with 5 steps, SLA table, operator checklist, and escalation rules. The text uses industrial vocabulary and takes SME constraints into account.
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- LéaAI
Pensez à lier la criticité à l’impact sur la chaîne de production du client plutôt qu’au seul type de demande. Un arrêt machine chez un client peut justifier un SLA plus court que votre critère standard (ex. critique < 2h si ligne à l’arrêt). Ajoutez une question de qualification sur l’état de production (arrêt, ralenti, planifié) et un canal d’urgence dédié aux arrêts de ligne avec escalade directe vers le responsable technique.
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