
Core Web Vitals without the guesswork
Lab scores are a diagnostic, not a target. What decides the ranking signal is what real devices on real networks actually measured.

Most underperforming pages fail for the same three reasons: they load too slowly, they offer competing actions, and nobody can say where the visitor was lost.
A landing page has one job, and the discipline is in refusing everything that is not that job. Pages rarely fail because the design is ugly. They fail for three reasons that are all measurable, and all fixable.
Most traffic arrives on a mid-range phone over a mobile network, and that is the machine the page has to be fast on. A desktop lab score of 98 tells you almost nothing about it.
The practical target is Largest Contentful Paint under one second on that device. Getting there is rarely subtle:
Every additional second before the page is usable costs a measurable share of the people who arrived.
A page with a headline CTA, a secondary CTA, a newsletter box, a chat bubble and a navigation bar is not asking for one thing. It is offering five exits, four of which are not what you wanted.
The rule that survives contact with reality: every section either moves the visitor toward the single action or comes off the page. Secondary links are text, not buttons. The navigation, on a true landing page, usually should not be there at all.
The form is part of this. Every field is a reason to stop. Ask only for what a person will genuinely use on the first call back — usually a name, a contact, and one sentence about the problem. Fields like "company size" are for your CRM's comfort, not the visitor's.
This is the one that keeps pages broken, because without it every change is a guess.
Analytics and conversion tracking go in before launch, not after the first disappointing week. What you need is modest:
With those three you can answer "where did we lose them" in an afternoon. Without them, you will be rewriting the headline for months because it is the only thing anyone has an opinion about.
A few things get attributed more power than they have.
Above-the-fold length. Long pages convert fine when the argument is good. The rule was invented for a different web.
Button colour. It matters when contrast is genuinely poor. Otherwise it is the thing teams test when they have run out of ideas.
Urgency theatre. Countdown timers that reset on refresh and "3 people are viewing this" widgets. They lift numbers briefly and cost trust permanently, and they are trivially recognisable.
If you have an existing page and one afternoon, do this in order: measure the load time on a real mid-range phone, count the actions the page offers, and check whether you can tell where visitors stop. In our experience, most pages fail at least two of the three, and fixing them moves more than any redesign.
Then redesign, if you still want to — but from data rather than from taste.

Lab scores are a diagnostic, not a target. What decides the ranking signal is what real devices on real networks actually measured.

The difference is not the technology but what the thing is allowed to do. One answers from a script, the other reads your data and acts on it.

An audit that lists two hundred issues is a document, not a plan. Ranking findings by the traffic they put at risk turns it into a work queue.
The AI assistant resolves two thirds of tickets before a person sees them, and the handover to an agent is clean. We measured it weekly with them and the numbers held.
Sarah Thompson
COO, logistics operator
Core Web Vitals went green on every template and organic traffic recovered within a quarter. The team explained every trade-off before making it.
Wade Warren
Head of e-commerce
They said no to two ideas we had and were right both times. What they did build has been running for a year without us touching it.
Lisa Williams
CEO, HealthTech startup
Our own engineers picked the project up in a week. Prompts, evaluations, tracing — all there, all explained.
Jennifer Lee
CTO, B2B services
A single well-scoped automation typically runs four to eight weeks from kickoff to production. An AI feature inside an existing product with real integration work runs eight to sixteen weeks. The biggest variable is how many systems we have to touch, not the AI itself.
Yes. Everything runs on your accounts and your infrastructure, and the repository is yours from the first commit — source, prompts, evaluation sets and documentation included. We are happy to stay on for support, but nothing is built so that you have to keep us.
Inference is usually the smallest line: a support agent handling ten thousand conversations a month typically lands in the low hundreds of dollars. Budget fifteen to twenty-five per cent of the build cost per year for maintenance, which covers failure reviews, prompt updates and model migrations.
We work inside your infrastructure and your data boundaries, use providers with zero-retention terms where required, and can deploy against self-hosted or regional model endpoints when regulation demands it. Data handling is agreed in writing during scoping, before any build starts.
We will say so. Part of the audit output is a list of processes that should not be automated yet — because the rules are not clear, the volume is too low, or classic software solves it more cheaply. Those lines are often the most valuable part of the engagement.