What kind of data does KNCT use to choose a shipping method?

KNCT uses a powerful combination of real-time shipping data and historical carrier performance to determine the most cost-effective and reliable method for every package. Unlike basic shipping rules that rely solely on weight or distance, KNCT evaluates each shipment across multiple variables to ensure the best total value is selected—balancing speed, cost, and delivery accuracy.

At the core of its decision-making, KNCT analyzes the weight and dimensions of each package to calculate not just actual weight, but dimensional weight. This helps avoid costly surprises related to volume-based pricing, especially for lightweight but bulky shipments. Next, the algorithm looks at the shipment’s point of origin and final destination. This helps determine how many shipping zones it crosses and whether a regional or national carrier would be the more efficient choice.

KNCT also takes current carrier performance into account. This includes on-time delivery history, error rates, regional delivery reliability, and seasonal performance fluctuations. If a carrier is known to experience delays in a certain region or during peak holiday volumes, the algorithm may route the shipment through a more consistent alternative.

Another key factor in the decision-making process is cost. KNCT pulls in live carrier rates, including fuel surcharges, accessorial fees, and peak season adjustments. These are often missed in traditional shipping calculations but can significantly affect the total landed cost of a shipment. By including these factors, KNCT ensures that each package is assigned a service that offers true cost efficiency, not just the cheapest base rate.

The system also evaluates available service levels such as ground, expedited, or priority and selects the tier that meets the delivery window required without unnecessary overspending. This is particularly useful for businesses offering customer delivery guarantees or operating with tight fulfillment SLAs.

Because KNCT re-evaluates these inputs with every shipment, it continuously adapts to changing shipping conditions. The result is a system that not only selects the optimal method at the time of shipping but also evolves over time to stay aligned with your logistics strategy and customer expectations.