Pricing Guide
Junbi.ai does one placement deeply: pre-testing ads against YouTube norms, including the five-second skip decision. Its pricing question is really a strategy question — is your spend concentrated enough in pre-roll to justify placement-specific tooling? Here's how to decide.
As a prediction platform (built with eye-tracking heritage from the EyeQuant lineage), Junbi has no per-study fieldwork underneath — subscriptions are shaped by testing volume, seats, and features, with current packaging on their site. That makes the economics closer to ours than to the panel platforms: the real differentiator is scope. Junbi's models and norms are tuned to YouTube — skip prediction, brand recognition in the pre-skip window — where a general benchmark is tuned to feeds.
What share of your media plan is actually YouTube pre-roll — now and next quarter? What's the effective cost per tested creative at your realistic volume? Do the YouTube-specific outputs (skip risk, pre-skip branding) map to edits your team actually makes? And for the rest of your placements — Shorts, TikTok, Reels, feed statics — what covers those? A placement-specific tool plus nothing is a coverage gap wearing a specialist's badge.
When pre-roll is your primary battlefield: brands with heavy YouTube budgets, agencies with YouTube-first clients, teams optimizing specifically around the skip. Placement-tuned norms genuinely beat general ones on their home turf, and the pre-roll craft problem — front-loading brand and reason-to-stay before the skip unlocks — rewards purpose-built measurement. Full comparison: PreTestAds vs Junbi and Junbi alternatives.
If your creative runs across TikTok, Reels, Shorts, and feed placements, one benchmark across all of it beats a specialist covering one slice: $49/month for 20 analyses (about $2.45 per test), packs from $45, up to 8 free credits — Hook Strength, the full attention curve, and the drop-off second against 76 public top performers, on any finished ad, filmed, designed, or AI-generated. Plenty of teams start general and add placement-specific tooling when one channel earns it.
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Junbi.ai sells subscription access to its YouTube pre-testing platform, typically shaped by testing volume and team needs, with sales conversations for larger plans. Check their site for current packaging — the durable part is the structure: you're subscribing to placement-specific prediction (YouTube norms, skip behavior) rather than paying per fieldwork study.
If YouTube pre-roll is where your money concentrates, yes — norms built around the skip decision answer questions a general benchmark can't. If YouTube is one placement among many, a general-purpose attention screen covers the whole mix for about $2.45 per test, and you can add placement-specific tooling when one channel dominates.
PreTestAds publishes everything: $49/month for 20 analyses (about $2.45 per test), packs from $45, up to 8 free credits with no card. It scores any finished ad against 76 public TikTok top performers — one benchmark across TikTok, Reels, Shorts, and feed placements, results in minutes.