Can I test Seedance-generated ads before running them?

Yes. Upload the Seedance video to PreTestAds and an fMRI-trained model predicts second-by-second attention, benchmarked against 76 top-performing TikTok ads. You get a 0-100 percentile score, hook strength, and drop-off timing before spending on media.

Seedance (sometimes written Seed Dance) is ByteDance's AI video generation model. It is known for fast generation and coherent multi-shot output — clips that cut between scenes while keeping subjects consistent, a natural fit for short-form vertical ads.

Why do multi-shot AI ads lose viewers at scene changes?

Generation models place cuts on visual logic, not attention logic. A transition the viewer lacks context for breaks their engagement, and they scroll. Attention scoring shows the exact second it happens so you can regenerate with a corrected shot order or a delayed cut.

AI Creative Testing

Testing Seedance-Generated Ads

Seedance — ByteDance's video generation model, sometimes written Seed Dance — produces fast, multi-shot short-form video from the company that built TikTok. That pedigree makes it a natural fit for feed ads. It still can't tell you which of its own outputs will hold a viewer.

The TikTok-native generator

Seedance's edge is coherent multi-shot generation — it can cut between angles and scenes inside one clip while keeping subjects consistent, which is exactly the grammar of short-form ads: hook shot, product beat, payoff. Coming from ByteDance, it's unsurprising the outputs feel native to vertical feeds. For ad teams it means storyboard-shaped generations rather than single continuous takes, closer to a real ad script structure out of the box.

Multi-shot cuts, multi-shot risks

Every cut is a chance to lose someone. Scored multi-shot AI ads show a recurring pattern: attention holds through the first scene, then drops at a transition the viewer didn't have context for. The model decides where to cut on visual logic, not on attention logic — it doesn't know that your second scene is where engagement cratered. A human editor feels this instinctively; a generation model needs to be told. Which is exactly what a scored report lets you do.

Prompt with the attention data

Upload each Seedance generation to PreTestAds and get the percentile score, Hook Strength, and the exact second of drop-off — benchmarked against 76 top TikTok performers, the same feed Seedance content is destined for. Then prompt surgically: "attention drops at the cut to the wide shot at 5s — stay closer on the product and delay the scene change." Regenerate, re-score. Because Seedance generations are fast, a full improve-and-verify round takes minutes. Run it against Kling or Veo variants of the same concept and let the scores pick your champion.

Made for the feed it's tested against

There's a neat symmetry in testing Seedance ads against a TikTok top-performer benchmark: the model comes from TikTok's parent company, and the benchmark measures what survives that exact feed. If your Seedance ad scores weak against TikTok's best, it will struggle precisely where it was born to run. Close the loop with the full generate-score-regenerate workflow before the media budget goes anywhere.

Score your Seedance generations

Upload your cuts and see which survives the feed it was built for — first analysis free.

Test Your Seedance Ads