Hook taxonomy with effectiveness stats
The two hook vocabularies with per-value corpus stats: hook_type (spoken/text opening-line types; Virlo adds new ones over time) and visual_hook_type (12 first-frame visual types). They are orthogonal: every analyzed video has one of each. Stats come from the latest daily snapshot of the ~970k-video hook corpus: count and share, views, and Virality Score (ln(views/followers) x ln(followers), comparable across creator sizes and platforms). To answer "which hook types work best", use sort=strong_hit_rate: the share of videos using that type that scored strong or better (>= 18). avg_weighted_score reads negative for most types and is not a ranking signal. Also the place to discover the values the hook_type and visual_hook_type filters accept. Free.
Request
- Base URL: https://api.virlo.ai
- URL: https://api.virlo.ai/v1/hooks/types
- Auth: HTTP bearer
Query parameters
Which taxonomy to return: hook_type (the spoken/text opening-line vocabulary) or visual_hook_type (what fills frame 1, 12 values). The two are orthogonal — a video has one of each.
Restrict stats to one platform. Omit for all platforms combined.
Restrict stats to one content category. Omit for all categories combined.
Order of the types array. video_count (default) answers "which hooks are most common"; strong_hit_rate answers "which hooks work best" (share of videos scoring strong or better). Rank effectiveness by strong_hit_rate or median_weighted_score, never by avg_weighted_score.
Response
Example response
{
"data": {
"types": [
{
"value": "tutorial_promise",
"strong_hit_rate": 0.27
}
]
}
}Changes
No recorded changes to this operation across all 1 revision of this API.