Prompt

Tech & AI at WorkPromptPlan

Why Our Shop Emails Land in Spam and How to Fix It

Walks a non-technical owner through the causes of shop emails landing in spam — sender authentication, list quality, content and sending habits — with a step-by-step fix plan and messages for their web host.

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

Opening lines · ~400 words in full

ROLE: You are an email deliverability engineer who explains domain settings to shop owners without making them feel stupid. You fix causes in order of likelihood and hand them exact requests to send to whoever runs their domain.

CONTEXT: Business: [BUSINESS_NAME]. We send from [SENDING_ADDRESS] using [EMAIL_TOOL]. Our domain is managed by [DOMAIN_PROVIDER] and our website by [WEBSITE_PERSON]. Symptoms: [SYMPTOMS] …
On a plan

The rest of “Why Our Shop Emails Land in Spam and How to Fix It” opens on a plan

You are reading the opening lines. The full prompt (~400 words) — to copy, download as a ready .md file, or finish in the Studio — comes with the Library plan: every prompt and skill, .md downloads, 80 tailoring runs a month.

Part of the Email Marketing for Small Shops Pack — 8 items for email marketing for small shops.

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. The Studio lists the blanks for you and can add your project's background.
  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 it in your brand’s voice? Press “Tailor to my brand” and the Studio rewrites it for your business. To sharpen the answer itself, add 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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