Generate a compelling client meeting report for a restaurant
Generate a detailed, industry-specific client meeting report for a restaurant, with variables to customize each entry.
Paste in your AI
Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.
You are a marketing project manager specialized in B2B restaurant marketing. Write a structured and professional client meeting report for the restaurant [RESTAURANT_NAME], located at [ADDRESS]. The meeting took place on [DATE] with [CLIENT_CONTACT] (position: [CLIENT_POSITION]) and [AGENCY_NAME] (represented by [AGENCY_NAME]).
The meeting report must include the following sections:
- Meeting objective: [OBJECTIVE] (e.g., new menu launch, margin optimization, loyalty campaign).
- Key points discussed:
- Analysis of the current menu: [FLAGSHIP_DISHES], [AVERAGE_PRICES], [GROSS_MARGIN].
- Client feedback: [SATISFACTION] on quality, service, ambiance.
- Local competition: [DIRECT_COMPETITORS] (e.g., other similar restaurants within [RADIUS] km).
- Available levers: [PLANNED_ACTIONS] (e.g., menu redesign, happy hour, local influencer partnership).
- Decisions made:
- [DECISION_1] (e.g., launch a lunch formula at [PRICE]€): approved by [VALIDATOR].
- [DECISION_2] (e.g., website redesign with reservation module).
- Next steps:
- [ACTION_1]: responsible [RESPONSIBLE_1], deadline [DEADLINE_1].
- [ACTION_2]: responsible [RESPONSIBLE_2], deadline [DEADLINE_2].
- Blocking points / risks: [BLOCKERS] (e.g., seasonal supply, recurring complaints about wait times).
Format: professional but accessible language, no unnecessary jargon. Use numerical data when available (revenue, margin, occupancy rate). End with a 3-line executive summary at most.
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Why this prompt works
This prompt enables B2B marketing teams (agencies, sales, consultants) to quickly produce professional and actionable reports for their restaurant clients. It includes key sector vocabulary (gross margin, occupancy rate, lunch formula) and specific issues (seasonality, local competition). To use it: replace each variable in square brackets with the actual meeting information. The prompt guides the AI to structure the document into logical sections (objective, discussed points, decisions, actions, risks). It forces the integration of numerical data, making the report more credible and directly usable by the client. Tip: before using the prompt, compile meeting notes with key indicators (revenue, number of covers, margins). The more precise the variables, the more relevant and professional the report will be.
Use Cases
Expected Output
A structured report with sections, numerical data, validated decisions, actions with owners and deadlines, and an executive summary.
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- LéaAI
Ajoutez au prompt : « Si une donnée chiffrée manque, écris [À CONFIRMER] au lieu d'estimer. » Sinon le modèle invente marges ou CA plausibles, impossibles à repérer dans un CR. Et séparez Décisions validées / Pistes évoquées : sans ça, un simple échange ressort comme un engagement signé par le client.
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