We built Cartlyzer because every DTC brand we talked to had the same complaint
Their storefront was static. Their shoppers were not.
The gap between data and storefront
Jennifer Nguyen spent six years in e-commerce analytics at a Chicago-based retail platform, running session analysis and reporting for DTC brands that ranged from a few million to tens of millions in annual GMV. The problem she kept encountering: these brands had detailed clickstream data. Their storefronts were updated once a week, by hand, by a merchandising manager working a pivot table in a Tuesday morning ritual that felt more like archaeology than analytics.
The data said this shopper wants outerwear. The grid still opened on last month's best-selling sneakers. The gap was measurable in every report. It showed up as browse abandonment, as low revenue per session on collection pages, as PDPs that bled traffic because they sat in position 7 for a visitor who would have bought from position 1.
The technical pieces existed: per-session intent scoring, propensity modeling, real-time API infrastructure. What was missing was a product built specifically for DTC collection pages, designed so a merchandising team could see the ranking, understand the rules layered on top, and trust the output without filing a ticket with engineering.
Cartlyzer was founded in Chicago in 2025 to close that gap. One problem, done precisely. We are not building a marketing suite. The product ranks your collection pages better, and gives you the measurement to prove it.
Three principles, not a mission statement
We are not building a marketing suite. No ad optimization, no email flows, no loyalty engine. We rank your collection pages better, and we give you a clean way to measure the lift. That is the whole job.
Every Cartlyzer feature is tied to a revenue-per-session metric. If we cannot measure the impact of a feature before and after, we do not build it. This is not a constraint; it is how we stay honest with ourselves and with you.
Our team came from DTC operations and e-commerce analytics, not ad-tech. We know what a Q4 grid crisis looks like from the inside. We know what it costs to have the wrong SKU in position 1 on a flash sale day, and what it looks like when the model finally surfaces the right one.
Three people building this from Chicago
Six years in e-commerce analytics. Founded Cartlyzer in 2025 after watching brands leave conversion on the table session after session.
Previously built real-time recommendation systems at a B2C subscription platform. Leads Cartlyzer's ML inference layer and API infrastructure.
Ran e-commerce for a DTC outdoor brand before joining Cartlyzer. Knows what a missed Q4 grid decision costs, and what it looks like when it goes right.
Built in Chicago. Deployed on storefronts across the US.
Chicago, IL 60606