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Metrics type: Supporting Metrics • Category: Website Performance

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At a glance

Performance Score broken down by page template (homepage, product detail, collection, cart, checkout, etc.). The most actionable surface for engineering prioritisation: instead of “site is slow”, the per-template view says “homepage scores 42, PDP scores 58, collection scores 48, fix homepage first because it has the worst score AND the highest traffic share”. Template-level fixes have multiplier effects: one PDP template fix lifts all 78 product detail pages simultaneously.

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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.

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Worked example

A UK-based BigCommerce fashion store, per-template lab scores Wednesday 15 May 26. What the template view is telling us:
  1. Collection page (-9.0) and homepage (-8.4) are the highest-leverage targets. Collection edges out homepage because of higher traffic share (28% vs 22%) despite a slightly less-bad score (48 vs 42).
  2. PDP (-5.5) is the third priority, meaningful traffic share (25%) with a moderate gap. Critical because PDP is the conversion page; performance work here translates directly to revenue.
  3. Cart, checkout, search, account all have small priority signals because either traffic share is low (account, checkout) or score is acceptable (cart, search). Don’t optimise these first; protect them from regression while focusing on the priority-3.
  4. Template-level fixes have multiplier effects: one PDP template fix lifts ~78 individual PDPs; one collection template fix lifts ~12 collection pages. Per-template work is more efficient than per-URL work when the underlying issue is shared.
  5. Recommended sequence:
    • Week 1-2: Collection template (filter widget refactor + responsive grid images)
    • Week 3-4: Homepage hero (image format conversion + responsive variants)
    • Week 5-6: PDP template (hero image + cart-drawer refactor)
    • Result: site-weighted mobile score from 51 → 70+
  6. Cross-reference with psi_mobile_score_compare for the same view with explicit mobile-vs-desktop gap; this card is mobile-focused and the device gap is implicit in the score values.
The diagnostic flow:
  1. Sort by score gap × traffic share. That’s the priority order.
  2. For each priority template, decompose by sub-metric (psi_lcp_by_template, psi_cwv_pass_by_template, psi_opportunity_by_template).
  3. Apply template-level fix patterns: image responsive variants on hero templates, widget refactors on interactive templates.
  4. Re-audit after each ship to confirm the template’s score moved.
Rapid-response playbook:

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Sibling cards merchants should reference together

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Reconciling against the vendor’s own dashboard

Where to look:
  • PageSpeed Insights, paste each template’s representative URL individually; assemble per-template view manually.
  • Lighthouse CI, runs per-URL audits in build pipeline.
Why the Vortex IQ template view may differ from manual PSI checks: Cross-connector reconciliation: primarily internal (with all per-template cards plus the per-URL ranking cards). Quick rule for support tickets: if a merchant says “my homepage scores higher in PSI than your card shows”, the difference is usually run-to-run variance plus URL choice. The Vortex IQ score is the 7-day rolling average; PSI is one snapshot.

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Known limitations / merchant FAQs

Should I optimise the worst-scoring template or the highest-traffic template? The product. Worst-score × traffic share gives the priority order. A 30-point gap on a 5% traffic template (priority signal -1.5) is less leverage than a 22-point gap on a 25% traffic template (priority signal -5.5). My checkout scores 73 mobile. Should I optimise it? Probably not. 73 is in the orange-band but acceptable; the 4% traffic share means optimisation impact is small. Protect from regression but don’t actively work on it. Why does collection page have a worse score than checkout? Different complexity. Collection pages have heavy filter widgets, 12+ product images, JS-driven sort/filter logic. Checkout pages are deliberately lean (fewer images, fewer scripts, focused on conversion). Different optimisation curves apply to different templates. Will fixing the homepage hero image help PDP scores? Sometimes, indirectly. If the homepage hero image and PDP hero use the same image-CDN config, fixing one may fix the other. More commonly: each template has its own optimisation work, with some shared infrastructure improvements. Can Vortex IQ tell me which template fix has the biggest impact? The “score gap × traffic share” column is exactly that. Sort descending; the top entries are the highest-leverage optimisations.

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Tracked live in Vortex IQ Nerve Centre

Score by Template 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 or book a demo to see this metric running on your own data.