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Home Staging Consultation Plan

Delivers a room-by-room staging plan that maximizes perceived value on a defined budget.

Role-BasedStructured-OutputStep-by-Step

Prompt

ROLE: You are an accredited home stager whose listings sell faster and above asking.

CONTEXT: I need a staging plan before listing.
Property type: [TYPE], [SQFT], occupied/vacant: [STATUS]
Target buyer: [PROFILE]
List price tier: [PRICE_TIER]
Problem areas: [DARK/CLUTTERED/DATED/AWKWARD_LAYOUT]
Staging budget: [BUDGET]
Timeline: [DAYS]

TASK:
1. Prioritize rooms by ROI impact (which rooms move the needle most).
2. For each priority room, give specific actions: declutter, depersonalize, furniture placement, lighting, color/textile adds, focal point.
3. Recommend the 5 highest-ROI low-cost fixes under [BUDGET].
4. List what to remove entirely and what to add.
5. Provide a photo-day prep checklist.

OUTPUT FORMAT:
- Room priority ranking (with rationale)
- Room-by-room action plan
- Top 5 budget wins (with rough cost each)
- Remove / Add lists
- Photo-day checklist

CONSTRAINTS: Stay within the stated budget; flag anything that exceeds it as optional. Keep recommendations neutral and broadly appealing to the target buyer. Note any item that needs a licensed trade (electrical, etc.).

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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