PromptSharpDaily briefs › August 27, 2026

PromptSharp Daily · free web issue · #91

Prompt of the day

August 27, 2026 · the free cross-vertical sampler: get better at AI and prompting, and see the sharpest prompts from across the network. Today's comes from CPG.

CPG Data & InsightsFREE

Trade promo post-mortem that tells the truth

The event is over and the lift number looks good in the deck. Did the promotion actually pay, or did it just buy volume forward?

You are a trade promotion analyst writing an honest post-event review. I will paste the event results. Produce:

A) A VERDICT — paid out, broke even, or bought volume forward — with the arithmetic shown step by step using only the numbers I provide (base vs incremental volume, lift, deal depth, feature/display support, event cost if I have it). If the payout math cannot be completed from my numbers, say exactly which input is missing rather than estimating it.
B) DIAGNOSTIC QUESTIONS for what the data cannot see: forward-buying, pantry loading, cannibalization of my own items, and halo — each phrased as a specific check I can run.
C) THREE GUARDRAILS for the next event: a depth cap, a support requirement (feature/display condition), and a timing rule — each tied to what this event's numbers showed.

Event data: [PASTE: base volume, incremental volume, lift %, deal depth, support type, retailer, dates, cost if known]

Rules: Do not invent, estimate, or extrapolate any figure — if a number is not in the data I give you, write "not provided" and flag it. Mark every claim I should verify against my syndicated data or internal reporting before using it externally. Never include retailer-confidential terms or personally identifiable shopper data.

Why it works — Trade is most CPG companies' second-largest cost line and the post-mortem is usually a victory lap. Making the model show its payout arithmetic — and admit which inputs are missing — is the difference between a real read and a slide that launders a bad event.

Use AI today — a workflow to steal

WorkflowFREE

Turn a page of rough notes into a finished deliverable

The gap between 'I have thoughts' and 'I have a document' is where hours go. The model closes it and even tells you what you forgot.

Dump your messy notes and say: 'Turn these into a [client email / one-pager / proposal outline]. Flag anything that's missing or contradictory.'
  1. Paste raw notes (typos fine).
  2. Name the output format.
  3. Ask it to flag gaps, then fill them.

Sharpen it: For anything complex, break the ask into steps: outline first, then draft section by section. Big single asks produce shallow results; staged asks go deep.

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PromptSharp prompts are drafted with AI assistance and human-reviewed. They structure how a model reasons over data you provide — they do not source or verify facts for you, and you own every output. Nothing here is financial, legal, tax, or investment advice. Never paste confidential, client, or material non-public information into consumer AI tools; follow your employer's AI-use policy. © 2026 PromptSharp.