Create a Human Review Rubric for AI Sales Content

“Looks good” is a weak review standard for an AI-written sales message. A polished draft can still contain an invented claim, an unwanted commitment, or a detail that should not be shared. A useful rubric tells reviewers what to inspect and which problems prevent approval.

Choose the content and its consequence

Build the first rubric for one content type, such as a post-meeting recap. Do not use the same checklist unchanged for a public landing page, an internal summary, and a commercial proposal. Each has a different audience, evidence requirement, and potential consequence if the wording is wrong.

Write down the intended recipient, purpose, and source material. A reviewer needs that context to decide whether the draft answers the right question. Without it, review tends to focus on grammar because grammar is the easiest visible property to judge.

Use gates before quality scores

Start with non-negotiable checks: factual support, authorized disclosure, accurate commitments, and correct recipient. Any failure blocks sending. Only after those gates pass should the reviewer assess clarity, relevance, tone, and brevity. A high style score cannot compensate for a false customer result or an unauthorized promise.

Use three judgments for each gate: pass, fail, or unresolved. Unresolved means the reviewer lacks evidence, not that the draft is probably acceptable. Give that item a named owner and a specific question so it does not disappear in a vague request to “double-check everything.”

If a service inquiry is part of your current review, the US$15/month offer can be assessed using the same standards for accurate scope and clear conditions. Leads Automation is an independent service, not affiliated with LinkedIn. Confirm the plan, eligibility, and terms before ordering.

Worked example: a recap with a hidden commitment

Fictional example: a draft says, “We will complete setup next week and reduce reporting effort by half.” The meeting notes only say that the seller will investigate setup timing and review the buyer's current reporting process. The draft fails both the commitment and evidence gates even if its tone is warm and concise.

A corrected version says that the seller will confirm setup requirements and examine the reporting workflow. The reviewer then checks whether those actions were actually agreed. Removing a specific number is insufficient if the remaining sentence still promises an outcome nobody approved.

Make subjective criteria observable

• Relevance: every paragraph serves the stated purpose or necessary context.

• Clarity: the recipient can identify the decision or next step without interpretation.

• Tone: the wording fits the relationship without invented familiarity or pressure.

• Brevity: repeated points and unnecessary product background are removed.

• Completeness: material conditions and unanswered questions remain visible.

Write one acceptable example and one failure example for criteria that reviewers interpret differently. “Professional tone” alone is too broad. A practical example might show how to acknowledge a delay without making an unsupported promise about when the problem will be fixed.

Calibrate reviewers with the same drafts

Have two reviewers independently assess a small sample. Compare the reasons for disagreements before changing the scores. They may have different evidence, different assumptions about the recipient, or genuinely different interpretations of the rubric. Resolve the underlying ambiguity rather than simply averaging their judgments.

Track the most common edit categories. If reviewers repeatedly remove unsupported benefits, revise the drafting input and claim library. If they repeatedly restore missing conditions, improve the instructions about preserving qualifiers. The rubric should help improve the workflow, not merely create an additional approval ritual.

NIST frames AI evaluation as part of voluntary risk management. Connect your review process to an approved vocabulary and claim verification for public material.

Before approving copy about the US$15/month offer, verify the wording with the provider and remove unsupported feature claims. Promotional clarity means describing the actual service, not making it sound like an official software plan.

Record the approved version, not just an approval comment on an earlier draft. If factual content, recipients, or commitments change afterward, return the affected checks to review. Approval should describe the message that will actually be used.