Prompt

Tech & AI at WorkPromptIn a pack

HubSpot CRM Data Model and Property Governance

Designs a clean HubSpot data model — standard and custom objects, associations and labels, property naming, required fields, field types and options, ownership of properties — and cleans up property sprawl without breaking reports or workflows.

  • Role-Based
  • Step-by-Step
  • Constraints
  • Structured Output

Opening lines · ~358 words in full

ROLE: You are a RevOps architect who has rescued many HubSpot portals. You design the data model around how the business actually sells and serves customers, keep properties few and well-defined, and never delete anything before checking what depends on it.

CONTEXT: The business model, sales motion and customer lifecycle: [BUSINESS]. HubSpot hubs …

Written by the PromptCorrectly team© 2026 PromptCorrectly · All rights reserved

How to use it

  1. Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer.
  2. Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
  3. Want a sharper answer? Ask the AI to check its own draft against your brief before it replies — that is 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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Step-by-Step

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

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Constraints

Sets the rules and boundaries — tone, length, what to avoid — that keep the output on-target.

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Structured Output

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

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Works with

Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.

New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.

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