# Marketing determinism scorecard

- Source: https://simeoncreatives.com/resources/marketing-determinism-scorecard
- Hub: AI & Business Automation

Score each marketing job on five yes-or-no questions. High score means a rule. Middle means rules around one narrow model step. Low means a model can draft and a person approves.

One row per job. Score it out loud with the person who owns the job. Write the date and the score so you can see what changed after an incident.
The score decides the shape of the workflow. It does not decide whether the job is worth automating. Use the process scorecard for that.

```mermaid
flowchart TD
    J["Job"] --> Q{"Score 4 to 5?"}
    Q -->|Yes| R["Rule or script"]
    Q -->|No| M{"Score 2 to 3?"}
    M -->|Yes| H["Rules + one model step + human approval"]
    M -->|No| D["Model drafts, sampled review"]
```
*A closed table beats a model on closed questions. Keep the model for text with no single correct form.*

## The five questions (one point per yes)

| Question | Yes means | Point |
| --- | --- | --- |
| Is there a written rule a new hire could follow? | The logic exists. Encode it. | 1 |
| Would two different outputs on the same input be a bug? | You need repeatability. | 1 |
| Does a wrong output touch money, consent, legal exposure, or a customer record? | A quiet error is expensive. | 1 |
| Must you explain the decision to a client, auditor, or colleague? | You need a reason you can show. | 1 |
| Is the input structured (fields, enums, numbers)? | A model adds risk and no skill. | 1 |

## What the score means

| Score | Shape | Gate |
| --- | --- | --- |
| 4 to 5 | Deterministic. Rule, table, or script. | Owner and review date for the rule |
| 2 to 3 | Hybrid. Rules in front and behind, one narrow model step. | Schema on the model output, human approval on anything that reaches a customer |
| 0 to 1 | Model-friendly. Drafting, summarizing, rewording. | Golden set, claims check, weekly sample review |

## Score your jobs

| Job | Q1 | Q2 | Q3 | Q4 | Q5 | Total | Shape | Date |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Write the job name |  |  |  |  |  |  |  |  |
| Write the job name |  |  |  |  |  |  |  |  |
| Write the job name |  |  |  |  |  |  |  |  |
| Write the job name |  |  |  |  |  |  |  |  |
| Write the job name |  |  |  |  |  |  |  |  |

## Jobs that usually score high

Check these first. If one is already run by a model, review it this week.

- [ ] Lead routing by region, size, or product
- [ ] Consent and unsubscribe checks before any send
- [ ] Campaign tags and analytics event names
- [ ] Send time and frequency caps
- [ ] Discounts, commissions, and invoice totals
- [ ] Field mapping between the customer relationship management (CRM) system and email tool

## If the score is 2 or 3

- [ ] Deterministic validation runs before the model step
- [ ] The model has one narrow job (extract, label from a closed list, or draft)
- [ ] Model output is validated against a schema. Failures go to a person.
- [ ] A table or rule makes the decision. The model never picks the owner, the price, or the send.
- [ ] A consent or approval gate sits between the model and any message
- [ ] Prompt and context pack version logged with every run

## Re-score when

- [ ] After any incident involving the job
- [ ] When weekly volume changes by a large factor
- [ ] When the model, prompt, or platform changes
- [ ] Once a quarter, even if nothing broke

## Related guides

- [Marketing jobs that must stay deterministic](https://simeoncreatives.com/blog/marketing-jobs-that-must-stay-deterministic)
- [Deterministic workflows vs LLM agents](https://simeoncreatives.com/blog/deterministic-workflows-vs-llm-agents)
- [Rules, retrieval, or an agent](https://simeoncreatives.com/blog/rules-retrieval-or-agent)
- [AI process scorecard](https://simeoncreatives.com/resources/process-scorecard)