Your landing page’s weakest score is Mobile web.

Fix Mobile web
58Growth scoreupdated

category scores

category scoresShowHide

Mobile web

44Poor

The phone experience as a first-class citizen.

Mobile web annotations on the mobile capture123
  1. Announcement banner — Three-line promo banner about the Prix Galien award eats the top of the fold and adds a dismiss tap before the hero.
  2. Hero headline block — Serif headline wraps into six tall lines, pushing the value prop's body copy and any CTA well below the fold.
  3. Body copy clipped — The supporting paragraph is cut off mid-sentence at the fold edge with no action above it.

Trust

52Fair

Proof that the product is real, competent, and safe to try.

SamaCare
Silna Health
Develop Health
Latent Health
Trust read
SamaCare"SamaCare Named 2026 Prix Galien USA Finalist for Best Digital Health Solution" announcement bar
Ruma Care"Featured on Launch YC — 1857" badge
Develop Health"High Confidence Answer" product UI card showing prior-therapy evidence (methotrexate, apremilast) for a prior authoriza
Latent HealthSupporting 60+ leading health systems and more than five million patient medication journeys every year
Banjo HealthCustomer logo strip showing FairScript and Kroger Prescription Plans (mobile capture)
Silna HealthCustomer logo bar under "EMPOWERING LEADING HEALTHCARE PROVIDERS" (Behavioral Innovations, ABS Kids, AnswersNow, HealthP

Information hierarchy

62Fair

Does the design help or inhibit what the page is trying to say?

SamaCare desktop capture for Information hierarchy

What works

What to improve

CTA

62Fair

Copy, size, verb, cost-feel — does the primary CTA earn the click?

SamaCare

How SamaCare compares

Recommended rewrites

Value props

68Fair

Title, subtitle, hero — do they sell the product's true value?

SamaCare’s headlineEnsuring Medical Benefit Prior Authorization Never Stands Between Patients and Prescribed TherapySamaCare delivers AI-native intelligence directly embedded into specialty practice workflows, powered by the largest real-world dataset in medical benefit prior authorization.

Working

Could improve