Infrastructure
Find merchants whose storefront is measurably too slow
For Hosting providers, CDNs and performance platforms
The problem
Selling infrastructure means proving a problem the merchant cannot see. Everyone believes their site is fast enough until someone shows them a number.
How the data solves it
Filter on real performance data. A failing Core Web Vitals verdict, field LCP over four seconds, a mobile Lighthouse score under 40: each is a number the merchant can verify themselves in seconds, which is what makes the conversation credible.
The filter set this maps to
Every field below exists in the shop schema. This is the query, not an illustration.
- CrUX Verdict
- poor
- Field LCP (ms)
- > 4000
- Performance (Mobile)
- < 40
- Products
- > 100 (traffic worth optimising)
Build it
Four steps to this list
Every column named here exists in the schema, and the request below runs as written.
- 1Set crux_verdict = poor — failing Core Web Vitals with real Chrome users.
- 2Add crux_lcp >= 4000 for shops where the largest paint takes over four seconds.
- 3Add products >= 100 so there is traffic worth optimising.
- 4Export lh_perf and crux_ttfb to separate a hosting problem from a front-end one.
The same query through the API
POST this to /api/v1/search for a count, or /api/v1/rows for the shops themselves.
{
"filters": [
{
"kind": "dropdown",
"col": "crux_verdict",
"values": [
"poor"
]
},
{
"kind": "numeric",
"col": "crux_lcp",
"op": "gte",
"min": 4000
},
{
"kind": "numeric",
"col": "products",
"op": "gte",
"min": 100
}
]
}Playbook
What to do once you have the list
A list is not a campaign. These are the three things that decide whether it converts.
Field data ends the argument
crux_* figures come from real Chrome users, not a lab simulation. A merchant can verify them in their own Search Console in under a minute.
TTFB isolates your part of the problem
A high crux_ttfb with an otherwise reasonable page points at hosting — which is exactly the part you can fix. Lead with that rather than generic speed.
Quantify before you quote
LCP over four seconds has a known conversion cost. Anchoring on their number rather than an industry average is what moves the conversation to price.
Outcome
What you end up with
Prospects with a measured, self-verifiable speed problem
Field data from real Chrome users, not lab simulations
Quantified impact to anchor the value conversation
Questions
Hosting: frequently asked
What is the difference between lab and field data here?
Lab data is a Lighthouse run under controlled conditions and is available for roughly 940,000 shops. Field data comes from the Chrome UX Report: aggregated measurements from real Chrome users. Both are exposed separately because they answer different questions.
Can I filter on Core Web Vitals specifically?
Yes: field LCP, INP, FCP, TTFB and CLS are individually filterable, alongside an overall CrUX verdict.
How do I find merchants whose hosting is failing them?
Look at field data rather than lab scores. The Chrome UX Report figures come from real Chrome users, so a poor verdict with a slow field LCP is a shop whose customers are genuinely waiting. Combine that with catalogue size, because a big catalogue on slow infrastructure is a merchant losing money on every session.
What is the difference between the lab and field performance numbers?
The Lighthouse scores are a lab test: one run, controlled conditions, useful for comparison. The Chrome UX Report figures are field data aggregated from real visits, which is what the shop's customers actually experience. A shop can pass the lab test and fail in the field, and the field number is the one worth quoting.
Can I see which host or CDN a shop uses?
Sometimes. The other technology field records what is detectable from the storefront, which picks up some infrastructure, and the mail host field shows the mail provider behind the domain. Neither is a complete hosting inventory, so treat a blank as undetected rather than as absent.
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