ThinkWithPrompt by SynotticThinkWithPrompt

Split my marketing budget across channels for next quarter

A channel-by-channel budget allocation based on past efficiency, saturation, and goals, with a reserve for tests.

Marketing & BrandFew-ShotStandardFinanceMarketingSalesFill-in Template

The prompt

Help me allocate my marketing budget across channels for next quarter. Total budget: [AMOUNT and period] Primary goal: [e.g. "pipeline", "new customers", "revenue", "awareness in a new region"] Last 2-3 quarters by channel: [PASTE: channel, spend, leads/customers, CAC or ROAS, pipeline or revenue] Channels I can't cut or must try: [COMMITMENTS, contracts, events, mandates] Known limits: [e.g. "search volume is capped", "team can run 2 new channels max"] Sales cycle length: [e.g. "same day", "90 days"] Steps: 1. Rank channels by marginal efficiency, not average: flag where more spend is likely hitting diminishing returns (rising CPA, high frequency, capped impression share). 2. Separate always-on demand capture (search, retargeting) from demand creation (paid social, content, events), and note the lag before the latter shows results. 3. Hold back 10-20% as a test budget unless I say otherwise. 4. Show what changes if the budget is cut by 20% or raised by 20%. Return: - A table: Channel | Last quarter spend | Proposed spend | Change | Expected result (range) | Why. - The test budget: 2-3 specific experiments with a success threshold each. - Leading indicators to check at week 3 and week 6 to reallocate mid-quarter. - Assumptions and data gaps, marked [CONFIRM]. Use only the numbers I give. Where a forecast is a guess, give a range and say so.

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

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What to fill in

  • AMOUNT and period
  • COMMITMENTS, contracts, events, mandates
  • e.g. "same day", "90 days"
  • 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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