Blog

Cut flowers age the whole time, but the rate depends on conditions. Most losses start before retail, in handoffs, pauses, and mixed storage. This guide maps where control is realistic, where it is limited, and what that means for shelf life and write-offs. It helps operators read results as the outcome of processes, not luck.

Flower imports often look predictable on paper but behave very differently in practice. This article explains how market structure, fragmented responsibility, and shipment variability affect real profitability. It focuses on where costs emerge after delivery and why standard indicators fail to protect margins. A practical lens for owners and buyers managing imported flowers.

A load can arrive looking acceptable, then fail a day or two later with the same symptoms across many stems. That pattern rarely comes from one obvious moment at the store. It is more often the outcome of time spent outside a stable handling mode across handoffs and waits. This article explains the mechanism behind the delay and the practical signals that point to where freshness was lost.

A flower shipment can look fine on arrival yet behave unevenly a few days later. This piece explains where a broker fits in that reality, beyond “just logistics.” It clarifies the broker’s scope, the parameters that matter, and how deviations are handled in a repeatable way. The goal is a sharper mental model, not a sales pitch.

Ecuador shipments often arrive looking strong, yet the outcome can diverge a few days later. The reason is rarely “the country” and more often the hours spent between stable cold segments. This piece maps the key handoffs before takeoff, around the flight, and after arrival. You’ll also see which in-store routines most reliably turn that potential into predictable sell-through.