Pbfenergy: a phone-and-desktop teardown
These are the Core Web Vitals real Chrome users experience on https://pbfenergy.com, straight from Google's field data. No login, no insider access, no Harvv pixel needed.
TL;DRWhat jumped out
We could not load https://pbfenergy.com. Cloudflare bot protection turned our scanner away, so nothing below should be read as a clean bill of health. It is what we could see from outside. The block itself is the headline finding: whatever stops us almost certainly stops AI crawlers from reading your pages too.
Below: what's already working, every finding ranked by impact and tagged with the screen it affects, the speed numbers on phone and desktop, and a checklist of what to fix first.
01Findings, ranked by what hurts conversion most
| Severity | Finding | How we know |
|---|---|---|
| High | Your edge blocked our scanner (HTTP 429), and it is very likely blocking AI crawlers tooBoth We tried to load https://pbfenergy.com and Cloudflare bot protection turned us away with HTTP 429, so no on-page scan could run. That matters beyond this report: the same rule that stopped us stops ChatGPT, Perplexity and Claude from reading your pages, which means AI assistants cannot cite you even when you are the best answer. Allow-list the AI crawler user-agents (GPTBot, PerplexityBot, ClaudeBot, Google-Extended) at your edge, then re-run this scan. paste into Claude, Cursor, or ChatGPT | median across loads |
"How we know": unlabeled = a deterministic fact, identical on every load (e.g. element sizes). Most findings are this kind, so we only mark the exceptions: median across loads = a noisy lab metric, reported as a median. real-user field data = Google CrUX, actual Chrome visitors.
02Performance: phone, desktop, and real visitors
| Metric | Mobile | Desktop | Read |
|---|---|---|---|
| TTFB (lab median) | 127 ms | 107 ms | Lab |
| FCP (lab median) | 292 ms | 212 ms | Lab |
| LCP (lab median) | 316 ms | 228 ms | Good |
| Page weight (median) | 0.7 MB | 0.4 MB | OK |
Google Lighthouse (lab): Performance 63 mobile / 97 desktop, SEO 85, Accessibility 84, Best Practices 100.
Lab numbers are from a headless mobile browser on an unthrottled connection: treat them as a floor, not a typical experience. Add a Google API key to light up real-user field data (CrUX) and Lighthouse scores.
03Tiny buttons are hard to tap on mobile
2 of 2 tappable items on this page come in below 44×44 pixels, the size Apple and Google both recommend for reliable tapping on a phone.
The buttons measuring below the minimum on this scan:
- a 61x18 "Cloudflare"
- a 43x18 "Privacy"
The fix is CSS-only on most sites: add padding around the icon (don't just change the icon size) so the actual tap area is at least 44×44 pixels. No redesign, no new assets.
04Technical SEO & structured data
| Check | Result |
|---|---|
| Title | Just a moment... (16 chars) |
| Meta description | Missing |
| H1 | 1 on page |
| Canonical | Missing |
| Structured data (JSON-LD) | None |
| Open Graph | Incomplete |
05The fix checklist
Everything to fix, priority first, each tagged with the screen it affects and a rough effort. Work top to bottom.
- Your edge blocked our scanner (HTTP 429), and it is very likely blocking AI crawlers tooBothVaries
Effort is a rough read from the outside: "CSS only" means no new assets or backend work, "1 line" means a single tag, "Dev afternoon" means a developer needs to touch tracking or scripts.
06What this report cannot tell you
Everything above is from the outside, looking at the page on a simulated phone and desktop. The questions that actually decide revenue need real visitors. Install the Harvv pixel (one script tag, 16 KB, zero personal data, no engineering project) and within about 72 hours you'd know which buttons real customers tapped and missed, how often Google Analytics is missing visits, and exactly where mobile shoppers stalled and left. This report shows you where to look. The pixel shows you how often it happens, and to whom.
Drop the Harvv pixel on pbfenergy.com and we turn this one-off scan into ongoing measured behavior: which taps miss, where sessions stall, and the real drop rates. Free to start, no card needed.
Add the pixel free07How we did this, and what it can't prove
- 4 mobile + 2 desktop loads of one URL from headless Chrome (iPhone viewport at 390px, desktop at 1366px), July 31, 2026. Enough loads to separate real defects from random noise, not a full-site crawl.
- Lab numbers, not real-user numbers (no field data was available for this run). Real devices on real networks run slower.
- Friction is inferred, not counted. We can prove a button is small. We can't, from the outside, count how often it causes a missed tap. That requires the pixel on a live page.
- This page rotates its content load to load, which is on its own a reason a single-shot scan can't be the last word on it.
About Harvv, the source of this teardown
Harvv is a behavioral UX analytics platform (harvv.com). A lightweight JavaScript pixel captures how real visitors behave on a site (dead clicks, rage clicks, scroll depth, Core Web Vitals, JavaScript errors, and 50+ other signals) and the engine turns them into prioritized, plain-English findings. This teardown is the outside-in version of that: the same detectors run against a public page, with no pixel installed.
How to read it. Every finding here is a reproducible, automated measurement, not an opinion: element sizes, contrast ratios, load metrics, and structured-data checks that anyone can re-run against the same URL. The method is stated in full above. Automated testing catches a subset of issues, so this is a starting point, not a certification.
Full disclosure. Harvv makes the pixel that would measure the friction these findings imply, so we have a commercial interest. That is exactly why the findings are kept to things a reader can verify independently, and why nothing here is inflated: an unreproducible claim would undermine the tool it is meant to demonstrate.
Prepared by Harvv (harvv.com), a behavioral UX analytics platform. Last updated July 31, 2026.