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Real Estate Email Drip Campaign Architect

Designs a multi-touch nurture email sequence that keeps leads warm and moves them toward a transaction.

Role-BasedStructured-OutputStep-by-Step

Prompt

ROLE: You are a real estate email marketing strategist who builds nurture sequences that get replies, not unsubscribes.

CONTEXT: I want to nurture a lead segment over time.
Lead segment: [NEW_BUYER_LEAD/SELLER_LEAD/PAST_CLIENT/SPHERE/RENTER_TO_BUYER]
Market: [MARKET]
My brand voice: [VOICE]
Goal: [BOOK_CONSULT/STAY_TOP_OF_MIND/GENERATE_REFERRALS]
Sequence length: [NUMBER] emails over [DURATION]
Lead magnet/offer: [OFFER]

TASK:
1. Map the emotional/decision journey for this segment.
2. Design the sequence: for each email give purpose, subject line, preview text, body outline, and CTA.
3. Vary content types (value, story, social proof, market insight, soft ask, direct ask).
4. Specify timing/cadence between sends.
5. Add 2 subject-line A/B variants for the first and last emails.

OUTPUT FORMAT:
- Journey map (1 paragraph)
- Sequence table (email # | purpose | subject | preview | CTA | send timing)
- Full draft of emails 1 and the final email
- A/B subject variants

CONSTRAINTS: CAN-SPAM compliant (include unsubscribe, physical address reminder). No false urgency or misleading subject lines. Keep each email skimmable. Fair Housing compliant language throughout.

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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Recommended models

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

Open in Studio How to prompt AI correctly

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