> ## Documentation Index > Fetch the complete documentation index at: https://docs.vortexiq.ai/llms.txt > Use this file to discover all available pages before exploring further. # Performance Score Over Time, Website Performance (PageSpeed + CrUX) > Performance Score Over Time for Website Performance (PageSpeed + CrUX) stores. Tracked live in Vortex IQ Nerve Centre. How to read it, why it matters, and ... **Metrics type:** [Supporting Metrics](/nerve-centre/overview#metrics-types-explained) • **Category:** [Website Performance](/nerve-centre/connectors#connectors-by-type) ## At a glance > **Lab Performance Score over time**, daily time-series of the Lighthouse Performance Score (0-100) on mobile profile. **The deterministic engineering trend** that pairs with field-data trends ([`crux_pass_rate_trend`](/nerve-centre/kpi-cards/website-performance/speed-test-pass-rate-over-time)) for the full picture. Lab data updates in real-time after each audit run, while field data has a 28-day rolling lag. **Use lab trend for**: build-pipeline gating, post-deploy verification, engineering iteration. **Use field trends for**: ranking-impact decisions, monthly executive reporting. | | | | ------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | **What it counts** | Time-series of the per-URL Lighthouse Performance Score across daily audit runs. Each data point is the score from that day's audit (with 7-day rolling smoothing applied to reduce run-to-run variance). | | **Sample type** | **Lab data** from scheduled Lighthouse audits. Field equivalent (closest analog): [`crux_pass_rate_trend`](/nerve-centre/kpi-cards/website-performance/speed-test-pass-rate-over-time). | | **Why lab trend updates faster than field trend** | Lab measures one synthetic run; field needs 28 days of accumulated user data. **A deploy fixing performance shows in lab trend within 24-48 hours**; field trend takes 28 days for full reflection. | | **Run-to-run variance smoothing** | Single-day lab scores fluctuate ±5-10 points due to Lighthouse run-to-run variance. The trend uses 7-day rolling smoothing to filter noise; sharp deploys still appear as inflection points within 3-7 days of the actual deploy. | | **Common drift patterns** | Same as LCP trend (since LCP dominates the score). Step regressions on deploys; gradual drift on accumulated changes. **The score is more sensitive than individual sub-metrics** because all five contribute simultaneously; a small regression in TBT plus a small regression in LCP can drop the score visibly even when each individual sub-metric stays in band. | | **CI/CD usage** | Lighthouse CI uses this score as a build budget gate. **Common pattern**: fail builds when score regresses >5 points or drops below 60 absolute. Catches performance regressions before they reach production. | | **Currency** | n/a, 0-100 score time-series. | | **Time window** | `T/7D/30D rolling` | | **Alert trigger** | `7-day rolling score drops > 10 points vs 30-day baseline` OR `current score < 50` (red band). | | **Sentiment key** | `psi_perf_score` | | **Roles** | owner, marketing, operations | ## Calculation Calculated automatically from your Website Performance (PageSpeed + CrUX) data. See the At a glance summary above for what the metric tracks and the worked example below for a typical reading. ## Worked example A UK-based BigCommerce fashion store, mobile lab score trend over 6 months ending Wednesday 15 May 26. | Month | Score (7D rolling) | Δ vs prior | Field CWV pass rate (compare) | Notes | | -------------------- | -----------------: | ---------: | ----------------------------: | --------------------------------------------------------- | | Nov 25 | 72 | (baseline) | 84% | Healthy lab + field | | Dec 25 | 70 | -2 | 82% | Stable | | Jan 26 | 64 | -6 | 78% | Lab moved first, field followed at 28-day lag | | Feb 26 | 58 | -6 | 72% | Hero carousel deploy hit lab immediately, field caught up | | Mar 26 | 50 | -8 | 68% | Marketing-stack expansion + cache config change | | Apr 26 | 44 | -6 | 65% | BFCM imagery + cache stayed bad | | **May 26** | **42** | **-2** | **64.8%** | **Current state, lab and field aligned** | | **Cumulative drift** | **-30 points** | | **-19 percentage points** | **6-month silent score erosion** | What the lab + field comparison is telling us: 1. **Lab trend leads field trend by 4-6 weeks.** Each deploy / change shows up in lab within days; field absorbs over the 28-day rolling window. **Reading lab and field trends together** provides a leading-indicator + truth-source view. 2. **The Jan 26 6-point drop in lab was the early warning.** Lab caught the regression \~28 days before field-CWV-pass-rate visibly dropped. **A `+5 point lab score regression` alert** would have fired then; investigating immediately would have prevented the cascade. 3. **The Mar 26 8-point drop is the largest single-month regression.** Two contributing changes (marketing stack + cache config) deployed in the same sprint window. **CI/CD gating** at "score must not drop > 5 points vs baseline" would have blocked at least one of these deploys, preventing the compound regression. 4. **Current 42 score is in red band** (below 50). The optimisation cycle to recover to 70+ requires the work documented across the per-CWV cards: image optimisation, third-party deferral, render-blocking fix, cache restoration. **Lab score is the primary build-gate metric**; CI configuration update recommended to prevent recurrence. 5. **Lab vs field divergence is informative.** When lab and field move together (this site's pattern), real-user conditions roughly match emulation. When lab improves but field doesn't, real users have slower devices/networks than emulation assumes; investigate audience profile. The diagnostic flow: 1. **Compare lab trend with field trends.** Lab leads; field confirms. 2. **Identify deploys / changes correlated with lab inflection points.** Lab captures changes within 24-48 hours; cross-reference deploy log. 3. **Apply CI/CD gating** to prevent regressions reaching production. Rapid-response playbook: | Time horizon | Action | | -------------- | ------------------------------------------------- | | First 1 hour | Identify deploys correlated with lab score drops. | | First 24 hours | Roll back or fix-forward problematic deploys. | | Day 7 | Lab trend confirms recovery. | | Day 28 | Field metrics catch up. | ## Sibling cards merchants should reference together | Card | Why merchants reach for it | | ---------------------------------------------------------------------------------------------------- | ------------------------------------------------- | | [`psi_perf_score_summary`](/nerve-centre/kpi-cards/website-performance/performance-score-summary) | Static lab score snapshot. | | [`psi_performance_score`](/nerve-centre/kpi-cards/website-performance/performance-score) | Per-URL lab score gauge. | | [`crux_pass_rate_trend`](/nerve-centre/kpi-cards/website-performance/speed-test-pass-rate-over-time) | Field CWV pass rate trend; the field counterpart. | | [`crux_lcp_trend`](/nerve-centre/kpi-cards/website-performance/load-speed-over-time) | LCP-specific field trend. | | [`crux_inp_trend`](/nerve-centre/kpi-cards/website-performance/responsiveness-over-time) | INP-specific field trend. | | [`crux_cls_trend`](/nerve-centre/kpi-cards/website-performance/layout-stability-over-time) | CLS-specific field trend. | | [`psi_biggest_regression`](/nerve-centre/kpi-cards/website-performance/biggest-regression) | Per-URL regression detection. | | [`crux_regression_timeline`](/nerve-centre/kpi-cards/website-performance/crux-regression-timeline) | Composite regression detection. | ## Reconciling against the vendor's own dashboard **Where to look:** * **Lighthouse CI dashboard**, historical lab scores from CI builds. * **PageSpeed Insights**, current snapshot. * **Internal CI/CD logs**, deploy-correlated score history. **Why the Vortex IQ lab score trend may differ from external views:** | Reason | Direction | What to do | | --------------------------------------------------------------------------------------- | --------------------- | ------------------------------------------------------------------ | | **Audit cadence.** Vortex IQ runs scheduled audits (daily); CI runs per-commit. | Different granularity | Use CI for per-deploy attribution; Vortex IQ for trend monitoring. | | **URL set.** Vortex IQ audits configured URL list; CI typically audits build artifacts. | Different scope | Confirm same URLs for direct comparison. | | **Smoothing.** Vortex IQ uses 7-day rolling. | Smoothed | Single-day deploys show within 3-7 days of actual deploy. | **Cross-connector reconciliation:** primarily internal (with the field-data trend cards). **Quick rule for support tickets:** if a merchant says *"lab score dropped but field metrics didn't move"*, the field metrics will move 14-28 days later as the rolling window absorbs. Lab leads field by design. ## Known limitations / merchant FAQs **Should I trust lab trend or field trend more?** For different decisions: **lab for engineering** (deterministic, fast feedback), **field for ranking** (truth source). Use both. Lab catches issues in 24-48 hours; field confirms ranking impact 28 days later. **Why does my lab score fluctuate ±10 points?** Lighthouse run-to-run variance. The 7-day rolling smoothing reduces this; trust trend movements >10 points; treat smaller fluctuations as noise. **My lab score regressed but my CI build still passed. Why?** CI gating thresholds may be too lenient. **Recommended config**: fail builds on >5 point regression vs 30-day baseline; minimum absolute score 60. Update Lighthouse CI config accordingly. **Can lab score improve without field metrics improving?** Sometimes. Lab measures synthetic conditions; field measures real users. Real-user audiences with very slow devices may not benefit equally from optimisations that improve lab. **Persistent lab-vs-field divergence** suggests audience-condition-specific issues; investigate. **Should I report lab score or field pass rate to leadership?** Both, with context. **Lab** is the engineering signal; **field** is the business signal. Reporting only one misleads. Best practice: lab for weekly engineering reviews; field-CWV-pass-rate for monthly business reviews. *** ### Tracked live in Vortex IQ Nerve Centre *Performance Score Over Time* is one of hundreds of KPI pulses Vortex IQ tracks across Website Performance (PageSpeed + CrUX) and 70+ other ecommerce connectors. Nerve Centre runs the detection layer; Vortex Mind investigates the cause when something moves; Ask Viq lets you interrogate any number in plain English. [Start for free](https://app.vortexiq.ai/login) or [book a demo](https://www.vortexiq.ai/contact-us) to see this metric running on your own data.