The State of Web Vitals

Chat & messaging impact

Performance impact by chat provider.

Field data PhoneDesktopAll Scope All sites Q2 2026 edition · Desktop field outcomes
Metric LCP INP CLS
1

At a glance the headline numbers for Chat & messaging impact

Performance impact by chat provider.

13
Providers ranked
After min-sites filter
5,111
Sites in sample
Combined across all items
65ms
Best INP (p75)
Smartsupp
The State of Web Vitals · Q2 2026 · 189,915 sites · desktop field datacorewebvitals.io/state-of-cwv
2

The ranking sorted by INP at p75, fastest first

# Provider INP p75 Passing Sites
1 Smartsupp 65ms 100.0%
279
2 Tidio 71ms 99.5%
424
3 HubSpot Chat 73ms 98.9%
1,379
4 Zendesk Chat 74ms 98.4%
700
5 Crisp 76ms 98.7%
254
6 LiveChat 79ms 99.1%
334
7 Help Scout Beacon 81ms 100.0%
50
8 Intercom 89ms 98.4%
200
9 Re:amaze 94ms 100.0%
132
10 Gorgias 103ms 98.8%
214
11 Freshchat 108ms 92.5%
80
12 Tawk.to 122ms 97.2%
1,002
13 Chatwoot 159ms 93.8%
63
The State of Web Vitals · Q2 2026 · 189,915 sites · desktop field datacorewebvitals.io/state-of-cwv
3

Passing INP per provider which group passes the INP most often

ProviderSitesPassing INPp75
Smartsupp 0.1% 279 100% 65ms
Re:amaze 0.1% 132 100% 94ms
LiveAgent 0% 25 100% 61ms
Drift 0% 14 100% 49ms
Help Scout Beacon 0% 50 100% 81ms
Front Chat 0% 12 100% 91ms
Tidio 0.2% 424 100% 71ms
LiveChat 0.2% 334 99% 79ms
HubSpot Chat 0.7% 1,379 99% 73ms
Gorgias 0.1% 214 99% 103ms
Crisp 0.1% 254 99% 76ms
Zendesk Chat 0.4% 700 98% 74ms
Intercom 0.1% 200 98% 89ms
tawk.to 0.5% 1,002 97% 122ms
Chatwoot 0% 63 94% 159ms
Olark 0% 43 93% 65ms
Freshchat 0% 80 93% 108ms
Good Needs Improvement Poor Sorted best-passing first · median colored by its own rating · pass = good INP (200ms at p75) · one value per site

No provider stands out: pass rates sit between 97% and 100%. computed

The State of Web Vitals · Q2 2026 · 189,915 sites · desktop field datacorewebvitals.io/state-of-cwv
4

All five vitals at once the whole category without toggling - cell is the pass rate, small number the p75

LCP
INP
CLS
FCP
TTFB
LiveChat 0.2%
772.4s
9979ms
610.16
741.8s
531.3s
Smartsupp 0.1%
852.1s
10065ms
740.11
781.7s
461.3s
Zendesk Chat 0.4%
842.1s
9874ms
760.10
811.6s
621.0s
Re:amaze 0.1%
901.8s
10094ms
840.09
941.2s
97505ms
Chatwoot 0%
862.1s
94159ms
710.13
861.5s
61939ms
LiveAgent 0%
851.6s
10061ms
850.08
801.4s
55987ms
Olark 0%
762.3s
9365ms
620.19
861.4s
59960ms
Freshchat 0%
812.1s
93108ms
650.13
841.6s
74809ms
Drift 0%
1001.6s
10049ms
1000.02
1001.5s
291.0s
HubSpot Chat 0.7%
852.1s
9973ms
800.09
801.6s
601.2s
Gorgias 0.1%
912.0s
99103ms
770.09
921.3s
89531ms
Tidio 0.2%
772.4s
10071ms
720.11
731.9s
591.4s
tawk.to 0.5%
812.2s
97122ms
720.11
751.8s
471.4s
Crisp 0.1%
812.3s
9976ms
770.10
741.8s
521.3s
Intercom 0.1%
792.4s
9889ms
760.10
811.5s
64986ms
Help Scout Beacon 0%
931.8s
10081ms
730.11
881.4s
73855ms
Front Chat 0%
822.2s
10091ms
730.13
641.9s
82673ms
60%95%+ passing Cell: pass rate, small number = p75 · faded rows: under 100 sites

One row per provider, one column per vital - the cell is the share of sites passing, the small number the p75. No toggling needed to see where the category actually differs.

Smartsupp leads on INP: 100% of its sites pass. tawk.to trails at 97%. computed

The State of Web Vitals · Q2 2026 · 189,915 sites · desktop field datacorewebvitals.io/state-of-cwv
Related signals Customer data platforms (6) → Font services (4) → A/B testing (12) → RUM (14) → Chrome field data from 189,915 sites, representing millions of real page loads · How we measured
Live queries (3) — admin only
Query #1: 69.6 ms 
SELECT 1 AS ok FROM site_providers LIMIT 0;
Query #2: 360.5 ms 
SELECT CAST(p.key AS VARCHAR) AS e, COUNT(*) AS sites,
  COUNT(*) FILTER (WHERE s.crux."all".lcp IS NOT NULL) AS all_lcp_n,
  quantile_disc(s.crux."all".lcp, 0.5) AS all_lcp_median,
  quantile_disc(s.crux."all".lcp, 0.75) AS all_lcp_p75,
  COUNT(*) FILTER (WHERE s.crux."all".lcp <= 2500) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."all".lcp IS NOT NULL), 0) AS all_lcp_good,
  COUNT(*) FILTER (WHERE s.crux."all".lcp > 2500 AND s.crux."all".lcp <= 4000) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."all".lcp IS NOT NULL), 0) AS all_lcp_ni,
  COUNT(*) FILTER (WHERE s.crux."all".lcp > 4000) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."all".lcp IS NOT NULL), 0) AS all_lcp_poor,
  COUNT(*) FILTER (WHERE s.crux."all".inp IS NOT NULL) AS all_inp_n,
  quantile_disc(s.crux."all".inp, 0.5) AS all_inp_median,
  quantile_disc(s.crux."all".inp, 0.75) AS all_inp_p75,
  COUNT(*) FILTER (WHERE s.crux."all".inp <= 200) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."all".inp IS NOT NULL), 0) AS all_inp_good,
  COUNT(*) FILTER (WHERE s.crux."all".inp > 200 AND s.crux."all".inp <= 500) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."all".inp IS NOT NULL), 0) AS all_inp_ni,
  COUNT(*) FILTER (WHERE s.crux."all".inp > 500) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."all".inp IS NOT NULL), 0) AS all_inp_poor,
  COUNT(*) FILTER (WHERE s.crux."all".cls IS NOT NULL) AS all_cls_n,
  quantile_disc(s.crux."all".cls, 0.5) AS all_cls_median,
  quantile_disc(s.crux."all".cls, 0.75) AS all_cls_p75,
  COUNT(*) FILTER (WHERE s.crux."all".cls <= 0.1) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."all".cls IS NOT NULL), 0) AS all_cls_good,
  COUNT(*) FILTER (WHERE s.crux."all".cls > 0.1 AND s.crux."all".cls <= 0.25) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."all".cls IS NOT NULL), 0) AS all_cls_ni,
  COUNT(*) FILTER (WHERE s.crux."all".cls > 0.25) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."all".cls IS NOT NULL), 0) AS all_cls_poor,
  COUNT(*) FILTER (WHERE s.crux."all".fcp IS NOT NULL) AS all_fcp_n,
  quantile_disc(s.crux."all".fcp, 0.5) AS all_fcp_median,
  quantile_disc(s.crux."all".fcp, 0.75) AS all_fcp_p75,
  COUNT(*) FILTER (WHERE s.crux."all".fcp <= 1800) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."all".fcp IS NOT NULL), 0) AS all_fcp_good,
  COUNT(*) FILTER (WHERE s.crux."all".fcp > 1800 AND s.crux."all".fcp <= 3000) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."all".fcp IS NOT NULL), 0) AS all_fcp_ni,
  COUNT(*) FILTER (WHERE s.crux."all".fcp > 3000) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."all".fcp IS NOT NULL), 0) AS all_fcp_poor,
  COUNT(*) FILTER (WHERE s.crux."all".ttfb IS NOT NULL) AS all_ttfb_n,
  quantile_disc(s.crux."all".ttfb, 0.5) AS all_ttfb_median,
  quantile_disc(s.crux."all".ttfb, 0.75) AS all_ttfb_p75,
  COUNT(*) FILTER (WHERE s.crux."all".ttfb <= 800) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."all".ttfb IS NOT NULL), 0) AS all_ttfb_good,
  COUNT(*) FILTER (WHERE s.crux."all".ttfb > 800 AND s.crux."all".ttfb <= 1800) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."all".ttfb IS NOT NULL), 0) AS all_ttfb_ni,
  COUNT(*) FILTER (WHERE s.crux."all".ttfb > 1800) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."all".ttfb IS NOT NULL), 0) AS all_ttfb_poor,
  COUNT(*) FILTER (WHERE s.crux."phone".lcp IS NOT NULL) AS phone_lcp_n,
  quantile_disc(s.crux."phone".lcp, 0.5) AS phone_lcp_median,
  quantile_disc(s.crux."phone".lcp, 0.75) AS phone_lcp_p75,
  COUNT(*) FILTER (WHERE s.crux."phone".lcp <= 2500) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."phone".lcp IS NOT NULL), 0) AS phone_lcp_good,
  COUNT(*) FILTER (WHERE s.crux."phone".lcp > 2500 AND s.crux."phone".lcp <= 4000) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."phone".lcp IS NOT NULL), 0) AS phone_lcp_ni,
  COUNT(*) FILTER (WHERE s.crux."phone".lcp > 4000) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."phone".lcp IS NOT NULL), 0) AS phone_lcp_poor,
  COUNT(*) FILTER (WHERE s.crux."phone".inp IS NOT NULL) AS phone_inp_n,
  quantile_disc(s.crux."phone".inp, 0.5) AS phone_inp_median,
  quantile_disc(s.crux."phone".inp, 0.75) AS phone_inp_p75,
  COUNT(*) FILTER (WHERE s.crux."phone".inp <= 200) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."phone".inp IS NOT NULL), 0) AS phone_inp_good,
  COUNT(*) FILTER (WHERE s.crux."phone".inp > 200 AND s.crux."phone".inp <= 500) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."phone".inp IS NOT NULL), 0) AS phone_inp_ni,
  COUNT(*) FILTER (WHERE s.crux."phone".inp > 500) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."phone".inp IS NOT NULL), 0) AS phone_inp_poor,
  COUNT(*) FILTER (WHERE s.crux."phone".cls IS NOT NULL) AS phone_cls_n,
  quantile_disc(s.crux."phone".cls, 0.5) AS phone_cls_median,
  quantile_disc(s.crux."phone".cls, 0.75) AS phone_cls_p75,
  COUNT(*) FILTER (WHERE s.crux."phone".cls <= 0.1) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."phone".cls IS NOT NULL), 0) AS phone_cls_good,
  COUNT(*) FILTER (WHERE s.crux."phone".cls > 0.1 AND s.crux."phone".cls <= 0.25) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."phone".cls IS NOT NULL), 0) AS phone_cls_ni,
  COUNT(*) FILTER (WHERE s.crux."phone".cls > 0.25) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."phone".cls IS NOT NULL), 0) AS phone_cls_poor,
  COUNT(*) FILTER (WHERE s.crux."phone".fcp IS NOT NULL) AS phone_fcp_n,
  quantile_disc(s.crux."phone".fcp, 0.5) AS phone_fcp_median,
  quantile_disc(s.crux."phone".fcp, 0.75) AS phone_fcp_p75,
  COUNT(*) FILTER (WHERE s.crux."phone".fcp <= 1800) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."phone".fcp IS NOT NULL), 0) AS phone_fcp_good,
  COUNT(*) FILTER (WHERE s.crux."phone".fcp > 1800 AND s.crux."phone".fcp <= 3000) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."phone".fcp IS NOT NULL), 0) AS phone_fcp_ni,
  COUNT(*) FILTER (WHERE s.crux."phone".fcp > 3000) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."phone".fcp IS NOT NULL), 0) AS phone_fcp_poor,
  COUNT(*) FILTER (WHERE s.crux."phone".ttfb IS NOT NULL) AS phone_ttfb_n,
  quantile_disc(s.crux."phone".ttfb, 0.5) AS phone_ttfb_median,
  quantile_disc(s.crux."phone".ttfb, 0.75) AS phone_ttfb_p75,
  COUNT(*) FILTER (WHERE s.crux."phone".ttfb <= 800) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."phone".ttfb IS NOT NULL), 0) AS phone_ttfb_good,
  COUNT(*) FILTER (WHERE s.crux."phone".ttfb > 800 AND s.crux."phone".ttfb <= 1800) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."phone".ttfb IS NOT NULL), 0) AS phone_ttfb_ni,
  COUNT(*) FILTER (WHERE s.crux."phone".ttfb > 1800) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."phone".ttfb IS NOT NULL), 0) AS phone_ttfb_poor,
  COUNT(*) FILTER (WHERE s.crux."desktop".lcp IS NOT NULL) AS desktop_lcp_n,
  quantile_disc(s.crux."desktop".lcp, 0.5) AS desktop_lcp_median,
  quantile_disc(s.crux."desktop".lcp, 0.75) AS desktop_lcp_p75,
  COUNT(*) FILTER (WHERE s.crux."desktop".lcp <= 2500) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."desktop".lcp IS NOT NULL), 0) AS desktop_lcp_good,
  COUNT(*) FILTER (WHERE s.crux."desktop".lcp > 2500 AND s.crux."desktop".lcp <= 4000) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."desktop".lcp IS NOT NULL), 0) AS desktop_lcp_ni,
  COUNT(*) FILTER (WHERE s.crux."desktop".lcp > 4000) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."desktop".lcp IS NOT NULL), 0) AS desktop_lcp_poor,
  COUNT(*) FILTER (WHERE s.crux."desktop".inp IS NOT NULL) AS desktop_inp_n,
  quantile_disc(s.crux."desktop".inp, 0.5) AS desktop_inp_median,
  quantile_disc(s.crux."desktop".inp, 0.75) AS desktop_inp_p75,
  COUNT(*) FILTER (WHERE s.crux."desktop".inp <= 200) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."desktop".inp IS NOT NULL), 0) AS desktop_inp_good,
  COUNT(*) FILTER (WHERE s.crux."desktop".inp > 200 AND s.crux."desktop".inp <= 500) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."desktop".inp IS NOT NULL), 0) AS desktop_inp_ni,
  COUNT(*) FILTER (WHERE s.crux."desktop".inp > 500) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."desktop".inp IS NOT NULL), 0) AS desktop_inp_poor,
  COUNT(*) FILTER (WHERE s.crux."desktop".cls IS NOT NULL) AS desktop_cls_n,
  quantile_disc(s.crux."desktop".cls, 0.5) AS desktop_cls_median,
  quantile_disc(s.crux."desktop".cls, 0.75) AS desktop_cls_p75,
  COUNT(*) FILTER (WHERE s.crux."desktop".cls <= 0.1) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."desktop".cls IS NOT NULL), 0) AS desktop_cls_good,
  COUNT(*) FILTER (WHERE s.crux."desktop".cls > 0.1 AND s.crux."desktop".cls <= 0.25) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."desktop".cls IS NOT NULL), 0) AS desktop_cls_ni,
  COUNT(*) FILTER (WHERE s.crux."desktop".cls > 0.25) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."desktop".cls IS NOT NULL), 0) AS desktop_cls_poor,
  COUNT(*) FILTER (WHERE s.crux."desktop".fcp IS NOT NULL) AS desktop_fcp_n,
  quantile_disc(s.crux."desktop".fcp, 0.5) AS desktop_fcp_median,
  quantile_disc(s.crux."desktop".fcp, 0.75) AS desktop_fcp_p75,
  COUNT(*) FILTER (WHERE s.crux."desktop".fcp <= 1800) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."desktop".fcp IS NOT NULL), 0) AS desktop_fcp_good,
  COUNT(*) FILTER (WHERE s.crux."desktop".fcp > 1800 AND s.crux."desktop".fcp <= 3000) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."desktop".fcp IS NOT NULL), 0) AS desktop_fcp_ni,
  COUNT(*) FILTER (WHERE s.crux."desktop".fcp > 3000) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."desktop".fcp IS NOT NULL), 0) AS desktop_fcp_poor,
  COUNT(*) FILTER (WHERE s.crux."desktop".ttfb IS NOT NULL) AS desktop_ttfb_n,
  quantile_disc(s.crux."desktop".ttfb, 0.5) AS desktop_ttfb_median,
  quantile_disc(s.crux."desktop".ttfb, 0.75) AS desktop_ttfb_p75,
  COUNT(*) FILTER (WHERE s.crux."desktop".ttfb <= 800) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."desktop".ttfb IS NOT NULL), 0) AS desktop_ttfb_good,
  COUNT(*) FILTER (WHERE s.crux."desktop".ttfb > 800 AND s.crux."desktop".ttfb <= 1800) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."desktop".ttfb IS NOT NULL), 0) AS desktop_ttfb_ni,
  COUNT(*) FILTER (WHERE s.crux."desktop".ttfb > 1800) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE s.crux."desktop".ttfb IS NOT NULL), 0) AS desktop_ttfb_poor
                    FROM site_providers p
                    JOIN sites s ON s.origin = p.origin
                    WHERE p.category = 'chat'
                      AND p.key IS NOT NULL AND CAST(p.key AS VARCHAR) <> ''
                    GROUP BY p.key;
Query #3: 32.4 ms 
SELECT COUNT(*) AS n FROM sites;
JSON file lookups (5)
20260625/meta.json 3.39 ms
20260625/types.json 1.76 ms
20260625/loaf-scripts.json 1.00 ms
20260625/menu.json 2.30 ms
20260625/providers.json 5.31 ms