The State of Web Vitals

Chat & messaging impact

Performance impact by chat provider.

Field data PhoneDesktopAll Scope All sites Q2 2026 edition · Phone 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
1.8s
Best LCP (p75)
Re:amaze
The State of Web Vitals · Q2 2026 · 189,915 sites · phone field datacorewebvitals.io/state-of-cwv
2

The ranking sorted by LCP at p75, fastest first

# Provider LCP p75 Passing Sites
1 Re:amaze 1.8s 91.8%
132
2 Gorgias 2.2s 84.9%
214
3 Help Scout Beacon 2.2s 86.5%
50
4 Smartsupp 2.2s 81.7%
279
5 Zendesk Chat 2.3s 78.3%
700
6 Freshchat 2.4s 78.3%
80
7 Chatwoot 2.4s 75.6%
63
8 Tawk.to 2.5s 74.9%
1,002
9 Crisp 2.5s 74.6%
254
10 HubSpot Chat 2.6s 73.1%
1,379
11 LiveChat 2.7s 68.4%
334
12 Intercom 2.8s 65.7%
200
13 Tidio 2.8s 67.8%
424
The State of Web Vitals · Q2 2026 · 189,915 sites · phone field datacorewebvitals.io/state-of-cwv
3

Passing LCP per provider which group passes the LCP most often

ProviderSitesPassing LCPp75
Drift 0% 14 100% 2.2s
Re:amaze 0.1% 132 92% 1.8s
Help Scout Beacon 0% 50 86% 2.2s
Gorgias 0.1% 214 85% 2.2s
Olark 0% 43 82% 2.2s
Front Chat 0% 12 82% 2.3s
Smartsupp 0.1% 279 82% 2.2s
Zendesk Chat 0.4% 700 78% 2.3s
LiveAgent 0% 25 78% 2.4s
Freshchat 0% 80 78% 2.4s
Chatwoot 0% 63 76% 2.4s
tawk.to 0.5% 1,002 75% 2.5s
Crisp 0.1% 254 75% 2.5s
HubSpot Chat 0.7% 1,379 73% 2.6s
LiveChat 0.2% 334 68% 2.7s
Tidio 0.2% 424 68% 2.8s
Intercom 0.1% 200 66% 2.8s
Good Needs Improvement Poor Sorted best-passing first · median colored by its own rating · pass = good LCP (2.5s at p75) · one value per site

92% of Re:amaze sites pass LCP. Intercom trails 26 points behind, leaving 34% of its sites failing. computed

The State of Web Vitals · Q2 2026 · 189,915 sites · phone 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
HubSpot Chat 0.7%
732.6s
90154ms
810.06
642.1s
501.4s
Gorgias 0.1%
852.2s
82181ms
880.05
871.5s
88591ms
Tidio 0.2%
682.8s
90147ms
850.04
622.3s
581.6s
tawk.to 0.5%
752.5s
91148ms
800.08
662.1s
451.4s
Crisp 0.1%
752.5s
87158ms
860.04
662.1s
541.2s
Intercom 0.1%
662.8s
76195ms
800.09
642.0s
541.3s
Help Scout Beacon 0%
862.2s
94139ms
840.03
761.7s
701.0s
Front Chat 0%
822.3s
91166ms
820.02
642.1s
82737ms
LiveChat 0.2%
682.7s
88146ms
670.18
622.1s
461.4s
Smartsupp 0.1%
822.2s
92146ms
890.04
711.9s
431.3s
Zendesk Chat 0.4%
782.3s
89147ms
870.05
741.8s
541.1s
Re:amaze 0.1%
921.8s
87151ms
790.09
921.3s
92620ms
Chatwoot 0%
762.4s
93144ms
760.10
821.6s
641.1s
LiveAgent 0%
782.4s
100127ms
830.04
831.7s
571.1s
Olark 0%
822.2s
96153ms
890.02
791.7s
541.1s
Freshchat 0%
782.4s
82186ms
770.10
741.8s
64912ms
Drift 0%
1002.2s
83134ms
1000.02
631.9s
141.5s
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.

Re:amaze leads on LCP: 92% of its sites pass. Intercom trails at 66%. computed

The State of Web Vitals · Q2 2026 · 189,915 sites · phone 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: 33.9 ms 
SELECT 1 AS ok FROM site_providers LIMIT 0;
Query #2: 245.5 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: 39.6 ms 
SELECT COUNT(*) AS n FROM sites;
JSON file lookups (5)
20260625/meta.json 0.03 ms
20260625/types.json 0.51 ms
20260625/loaf-scripts.json 0.37 ms
20260625/menu.json 0.15 ms
20260625/providers.json 4.60 ms