I designed the site from scratch in Figma, building a modular design system with strong visual hierarchy and scalable UI components that could flex across use cases. The core challenge was information architecture: how do you explain an AI platform that works across four distinct marketplaces to sellers who might only use one?
I structured the site around user outcomes rather than technical features, sections organised by what the seller gains (list faster, manage inventory across platforms, sell on more channels with less work) rather than by what the platform's architecture looks like under the hood.
In Webflow, I implemented a robust CMS architecture for features, integrations, marketplace-specific pages, and testimonials. This gives Listing Monster's team a template-driven system where new content slots into pre-designed layouts, the site scales alongside the product without requiring rebuilds.
Custom interactions and performance-optimised layouts were built in from day one: the site loads fast and feels polished, both signals of technical competence that SaaS buyers register whether they're conscious of it or not.
The programmatic SEO layer generates targeted landing pages dynamically from the CMS, pages like 'AI listing tool for eBay charity sellers' or 'automated Depop cross-listing software', capturing long-tail search intent at scale from sellers who are actively searching for solutions to specific marketplace problems.
I wired form submissions and demo bookings into their downstream sales stack via Webflow-native integrations and API connectors, ensuring no lead leaks between the website and their pipeline.
Every demo request arrives with full context: which page it came from, which features the visitor engaged with, and which marketplace they're interested in.