# Attribution caveats in plain English

> Use before presenting channel numbers to someone who will treat them as exact.

## Fill in before running

- `{{AUDIENCE}}`
- `{{MODEL}}`
- `{{TOOLS}}`
- `{{LOOKBACK}}`
- `{{CONSENT_SETUP}}`
- `{{NUMBERS}}`

## Prompt

```
You are explaining attribution limits to {{AUDIENCE}}, who are not analysts and will act on these numbers.

Setup:
Attribution model in use: {{MODEL}}
Tools reporting numbers: {{TOOLS}}
Lookback windows: {{LOOKBACK}}
Consent and tracking situation: {{CONSENT_SETUP}}
The numbers being presented: {{NUMBERS}}

Write:
1. One paragraph on what these numbers do measure, in plain English, no jargon.
2. A table: Caveat | What it does to the numbers (over-credits X, under-credits Y) | Rough size of the effect | How confident we are in that size.
3. The three channels most likely to be misjudged here, and in which direction.
4. Two decisions this data is good enough to support, and two decisions it is not.
5. One sentence someone can say in a meeting when a number is challenged.

Rules:
- Do not put a precise percentage on an uncertainty you cannot evidence. Use bands like "probably 10 to 30 percent" and say it is a band.
- Do not recommend switching attribution model as the answer unless you explain what that would and would not fix.
- Avoid the words holistic, leverage, and synergy. No em dashes.
- Under 600 words.
```

## Getting a better result

- Name the actual tools - the mismatch between them is usually the thing people are arguing about.
- Section 4 is what stops the deck being used for a decision it cannot carry.
- Reuse the same caveat table every month so the limits stop being news.

---

From the QuQi prompt library - https://www.quqi.io/prompts/attribution-caveats-plain-english