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Welcome to the Freight Analytics demo. For the full experience, we recommend viewing on desktop.

📷 Let's take a high-level tour of Freight Analytics, a powerful tool built for chartering and trading teams to gain a market edge.

Freight Analytics is included in our Data Insights module — an optional add-on for Shipfix users who want deeper market visibility.

Freight Analytics aggregates cargo orders and tonnage circulars from the market to help you understand real-time supply and demand dynamics.

Forward Demand Dynamics

On the left side, you’ll see forward demand dynamics for cargo orders, including trends week-over-week, over two weeks, and month-over-month—giving you a clear view of how demand is evolving.

Forward Supply Dynamics

On the right side, you’ll see forward supply dynamics based on tonnage circulars, with trends displayed week-over-week, across two weeks, and month-over-month—providing a clear picture of how supply is shifting.

Global Filters

Across the top of the screen are global filters such as Ship Class, Area, Business Type, Forward Period, and Circulated Within—allowing you to tailor the data to your specific needs.

Here, you can filter by Ship Class. In this example, we’re viewing data for Panamax vessels.

In this view, we can filter by Area. In this example, we're looking at the USG and Gulf of Mexico region.

Next, we have the Business Type filter, where you can select either VOY or TC. In this example, we’ll view All.

Now we have the Forward Period filter, which defines the future time frame you want to focus on. In this example, we’re looking at Spot +20 days.

Lastly, we have the Circulated Within filter, which lets users choose how far back they want to include circulars in the dataset. In this example, we’ll be using circulars from the past 10 days.

Supply and Demand Curves

Now, if we scroll to the bottom, we can view the supply and demand curves and filter by Tonnage Open Areas. In this example, we’ll focus on the local area only.

We can also choose how we want to display the data, adjusting the view to suit our analysis needs.

The last filter available is for Baltic spot prices, where you can choose to view data by individual routes, ocean segments, or index averages. In this example, we’ll focus on the average of P1A, P2A, P6, and P7—Baltic Panamax Index routes that represent key global trade flows.

Now we can see the demand curve in blue, the supply curve in red, and the price curve in yellow. In this example, we have 17 cargo orders, 5 available vessels, and a price level of 15.95K.

Right now, we’re viewing data from July 12 to August 11 but you can easily expand the date range to analyze broader market trends.

We’ve now expanded the range to March 11 through August 11, giving us a broader view of the data and longer-term market trends.

What stands out to you from these curves? Did you notice how price—shown in yellow—typically follows behind demand, which is shown in blue? From May to June, demand dropped first, and only afterward did pricing begin to fall. Then, from June through August, demand started rising again, but pricing didn’t respond immediately—it followed with a delay.

Because Freight Analytics data is real-time—extracted before vessels hit the water.