Create social posts and ad variations for a seasonal sale
Organic social posts and paid ad variations for each sale phase, with testing angles and creative briefs.
The prompt
Create the social posts and ads for my seasonal sale. This is step 4 of a seasonal campaign pack; it works on its own, but paste your offer messaging sheet (step 2) and timeline (step 1) if you have them.
Offer, dates, and exclusions: [DETAILS]
Hero products and why people buy them: [LIST]
Platforms: [e.g. Instagram, Facebook, TikTok, Pinterest, Google]
Ad budget and audiences: [e.g. retargeting site visitors, past customers, lookalikes, interests]
Creative assets available: [photos, videos, UGC with permission, none yet]
Brand voice: [DETAILS]
Return:
1. Organic posts by phase (teaser, launch, mid-sale, last day): caption, visual idea, and story frame text for each platform I use.
2. Ad variations (6-9) across 3 angles, e.g. the offer itself, the gift solution, and the product benefit. For each: primary text, headline, and description within typical character limits; and the audience it fits.
3. Retargeting vs. prospecting: which messages go to people who already know me vs. new audiences.
4. Creative briefs (3): for a designer or for me to shoot, with format sizes, first-3-seconds hook for video, and on-screen text.
5. Test plan: what to test first (angle, not tiny copy tweaks), when to check results, and the rule for shifting budget.
6. Comment reply bank for common questions: code not working, shipping times, exclusions.
Rules: Only use customer content I have permission to use. No fake scarcity. Check each platform's ad policies for discount and pricing claims.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Marketing & Brand prompts
What to fill in
- DETAILS
- LIST
- e.g. Instagram, Facebook, TikTok, Pinterest, Google
- photos, videos, UGC with permission, none yet
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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