At a glance the headline numbers for Third-party categories
Those third parties grouped by what they do.
26.1% of sites carry analytics. 9.3% embed video players.
The third-party categories mix who uses what, and how fast each group loads
Third-party categories. On the fleet: 26.1% analytics, 13.0% tag managers, 9.8% marketing pixels. 59.3% of sites use at least one analytics.
Passing INP per bucket every category and count level at once - color is the pass rate
Each row is a category, each column its own count bucket (few on the left, many on the right); the cell is the share of those sites passing INP.
Rum swings the hardest: 86% of sites pass INP with few, 62% with many. computed
Few vs many - does quantity cost INP? the pass rate with few vs many of each category
Per category: the pass rate among pages with FEW of it (hollow ring) against pages with MANY (solid dot), worst trend first. Thin buckets are excluded from the endpoints.
More Rum costs the most: the INP pass rate falls from 86% with few to 62% with many. computed
Why this matters for the Core Web Vitals, and where to start fixing it
Third parties grouped by what they do, and the category predicts the damage. Ads and chat inject visible UI, so they shift layout (CLS). Analytics and tag managers run code, so they block interactions (INP). Font and CDN services sit on the render path, so they delay paint (LCP).
Budget per category, not per tag. Most stacks need at most one of each: one analytics tool, one tag manager, one chat widget. The duplicates are where the easy wins live.
How does this affect the Core Web Vitals?
Third-party categories correlate with the INP. With Scheduling, 96% of sites pass the INP. With Rum, 84% do. The causal link is weak: the choice mostly marks what kind of site made it.
The split is bigger on CLS. With Ecommerce, 90% of sites pass it. With Push notifications, 69% do.
Chrome field data from 94,910 sites, representing millions of real page loads. How we measured.