ThinkWithPrompt by SynotticThinkWithPrompt

Write my webinar registration page and invitation emails

A registration page and a short invite email series that tell people exactly what they'll learn.

Marketing & BrandFew-ShotStandardEmailWriteFill-in TemplateStep-by-step

The prompt

Write the registration page and invitations for my webinar. This is step 2 of a webinar pack; it works on its own, but paste the title, promise, and agenda from step 1 if you have them. Webinar title and promise: [DETAILS] Date, time, time zones, length: [DETAILS] Speakers and why they're credible: [NAMES, ROLES, real credentials] Who it's for (and not for): [DETAILS] 3 takeaways: [LIST] Recording policy: [e.g. recording sent to all registrants] Audiences I'll invite: [e.g. customers, prospects list, LinkedIn followers, partners] Return: 1. Registration page: headline, subhead with date/time, "You'll learn" bullets (outcomes, not topics), who should attend, speaker bios (2-3 lines each), form fields (keep to the minimum I need; explain the trade-off of each extra field), button text, and the recording note. 2. Invite email 1 (2-3 weeks out): 3 subject lines, under 150 words. 3. Invite email 2 (1 week out): a new angle, e.g. a specific question the session answers. 4. Last-call email (day before): short and urgent without false scarcity. 5. 2 social posts for speakers to share in their own words. 6. Partner/co-host invite blurb if I'm co-hosting. Rules: No fake countdowns or "only 10 spots left" unless true. Mark unverified speaker credentials [CONFIRM]. Include a consent line for marketing follow-up that matches my region's rules.

Highlighted [brackets] are blanks to replace with your own details.

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What to fill in

  • DETAILS
  • NAMES, ROLES, real credentials
  • LIST
  • e.g. recording sent to all registrants
  • e.g. customers, prospects list, LinkedIn followers, partners
  • CONFIRM

How this prompt is built

This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.

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