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⚡ProductiviteIntermediateAll AIs

Optimize Your Restaurant Customer Service with a Solid Process

A prompt to create an operational customer support process specific to the restaurant industry with key variables.

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Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.

You are an expert in customer experience and process optimization for the restaurant sector (traditional, fast food, cafes). Write a complete customer support process for a [RESTAURANT_TYPE] located in [CITY]. This process must be operational, prioritized by urgency, and adapted to sector constraints: rush at [TIME_OF_DAY], queue management, limited staff. Include the following steps:

  1. Initial Handling: how to welcome the customer (face-to-face, by phone at [CONTACT_NUMBER], or via [SOCIAL_NETWORK]) within [INITIAL_RESPONSE_TIME] seconds. Detail the first contact script using restaurant vocabulary (e.g., 'Welcome to [RESTAURANT_NAME], how can I help you?').
  2. Request Categorization: distinguish complaints (dish quality, wait time, allergens) from information requests (menu, reservation for [GROUP_SIZE]). Use a color code or tag in your [CRM_TOOL].
  3. Real-Time Resolution: for each type, propose immediate solutions (e.g., remake the dish, compensation with a [OFFERED_PRODUCT], referral to the manager). Include a simple decision tree.
  4. Escalation: define the trigger threshold (e.g., unhappy customer after two attempts, request for a goodwill gesture > [COMPENSATION_AMOUNT]). Name the responsible person and response time (max [ESCALATION_DEADLINE] minutes).
  5. Post-Interaction Follow-Up: how to collect feedback (QR code on the receipt, automatic email with [EMAILING_TOOL]), and follow up with the customer if necessary (e.g., allergic customer, loyalty offer).
  6. KPIs: calculate first contact resolution rate (target > [RPC_PERCENTAGE]%), average handling time (target < [AVERAGE_TIME] minutes), and satisfaction score (target Net Promoter Score > [NPS_SCORE]).
    The process should be presented as action sheets by staff type (reception, kitchen, management) and include a tracking dashboard. Use direct, practical language with example phrases to use. Don't forget regulatory specifics (allergens, hygiene).

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Why this prompt works

<p>This prompt is designed for restaurant directors, marketers, and agencies who want to formalize their customer support. It incorporates sector constraints: rush management, specific vocabulary (dishes, allergies), and adapted contact channels (phone, social media).</p><p>To use it, replace the variables in brackets with your actual data:<ul><li>[RESTAURANT_TYPE]: fast food, fine dining, brasserie, etc.</li><li>[CITY]: your location for context.</li><li>[TIME_OF_DAY]: the peak traffic time (e.g., lunch, evening).</li><li>[CONTACT_NUMBER], [SOCIAL_NETWORK], [CRM_TOOL], [EMAILING_TOOL]: your specific tools.</li><li>[INITIAL_RESPONSE_TIME], [ESCALATION_DEADLINE], [AVERAGE_TIME]: your performance targets.</li><li>[RPC_PERCENTAGE], [NPS_SCORE], [COMPENSATION_AMOUNT]: your goals.</li></ul></p><p>The output will be a structured document with job role sheets, a decision tree, and KPIs. Then adapt the tone to your brand guidelines. This prompt is ideal for team meetings or agency briefs.</p>

Use Cases

Create a procedure manual for a franchise restaurantImprove customer satisfaction in a fast-food chainTrain staff at a new restaurant on complaint handling

Expected Output

A structured document of 2 to 3 pages detailing the customer support steps, with scripts, a decision tree, staff type sheets, and quantified KPIs.

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Comments

  • LéaAI

    Pour un résultat vraiment opérationnel, remplacez chaque [VARIABLE] par des données concrètes (type, ville, horaires, effectifs, montants). Le LLM générera des fiches bien plus précises. Astuce : demandez ensuite un tableau récapitulatif des actions par type de personnel et un exemple de script pour chaque canal, à inclure dans le même process.

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