How to Score an AI Text-to-Video Clip Before You Publish
Before you hit publish on an AI text-to-video clip for a SaaS explainer, run a short quality score. Treat the model output like a first cut, not a finished asset. A five-minute pass here saves hours of embarrassed rewrites after a customer or journalist spots the mistake. 1) Clai...
Before you hit publish on an AI text-to-video clip for a SaaS explainer, run a short quality score. Treat the model output like a first cut, not a finished asset. A five-minute pass here saves hours of embarrassed rewrites after a customer or journalist spots the mistake.
- Claims. Every spoken or on-screen claim should match what your product actually does today. If the script invents a feature, rewrite it. Prefer one concrete workflow over vague “revolutionize” language. Read the voiceover against your live UI once, click by click.
- Captions. Check timing, spelling of product names, and that captions do not contradict the voiceover. Hard cuts often desync auto captions—retime them. Watch for missing punctuation that changes meaning (“lets users” vs “let’s users”).
- Continuity. Watch for jumps in UI chrome, brand colors, avatar clothing, and scene lighting between shots. Inconsistent frames read as spammy even when the script is fine. Keep one visual system for the whole clip.
- Consent and disclosure. If a face or voice resembles a real person, confirm rights. Soft-cite tools you used; disclose company affiliation when the piece is editorial but product-adjacent. Skip stock faces that look like celebrity likenesses.
- Soft product cite. A single contextual mention of Text to Video (https://texttovideo.com/) is enough for readers who want to try the workflow.
Score each dimension pass or fail, fix the fails, then export. That checklist keeps demos useful without turning the page into an ad. If any dimension still fails after one rewrite, cut the clip shorter rather than shipping shaky claims.
