Data Methodology

How we collect, process, and calculate freight market rates.

1. Data Sources

Cargobloom aggregates real-time freight offer data from major European freight exchanges and logistics platforms. Our data collection system captures:

Spot market offers - Real freight postings with actual prices
Route information - Origin and destination countries/regions
Distance data - Kilometers between loading and unloading points
Vehicle types - Curtainsider, box, refrigerated, and other body types
Timestamps - When offers were posted and captured

We do not fabricate or estimate data. Every rate shown is derived from actual market offers.

2. Data Filtering & Validation

To ensure data quality, we apply strict validation rules before including an offer in our calculations:

Inclusion Criteria

Price between 0 and 1,000,000 EUR
Distance between 1 and 5,000 km
Rate per kilometer between 0.20 and 10.00 EUR/km
Valid origin and destination country codes
Complete pricing and distance information

Exclusion Criteria

Outliers - Rates outside 0.20-10.00 EUR/km range
Incomplete data - Missing price, distance, or location
Zero-distance offers - Invalid routing data
Duplicate listings - Same offer posted multiple times

These filters prevent erroneous or manipulated data from skewing market averages.

3. Rate Calculation

The primary metric we display is the Rate per Kilometer (EUR/km). For each individual offer, the base rate is:

Base Rate = Price (EUR) / Distance (km)

However, the headline rate you see on the dashboard is not a simple average. We use a smoothed calculation:

Displayed Rate (EMA)

The rate shown on the dashboard uses an Exponential Moving Average (EMA) to smooth out short-term fluctuations and provide a more stable market indicator. EMA gives more weight to recent offers while still considering historical data, reducing noise from outlier transactions.

Market Volume

Total estimated value of freight on a route, calculated as the sum of all offer prices.

Volume = SUM(price_amount) for all offers

Price Change (%)

Percentage difference between current average rate and the historical rate.

Change = ((Current Rate - Previous Rate) / Previous Rate) x 100

4. Currency Normalization

All prices are converted to EUR at the time of data capture using official ECB (European Central Bank) exchange rates. This ensures:

Consistent cross-border rate comparisons
Historical data stability (uses rate at capture time, not current rate)
Support for PLN, CZK, HUF, RON, GBP, and other European currencies

Exchange rates are updated daily at 15:00 UTC from ECB reference rates.

5. Time Windows

We report data across multiple time horizons:

Metric	Time Window	Description
Today's Rate	Current day (UTC)	Average rate from midnight UTC to now
24h Change	Today vs Yesterday	Compares today's average to yesterday's
7d Change	Today vs 7 days ago	Week-over-week comparison
30d Change	Today vs 30 days ago	Month-over-month comparison
Sparkline	Last 7 days	Daily average rates visualized

All timestamps are recorded and processed in UTC timezone.

6. Limitations & Disclaimers

While we strive for accuracy, users should be aware of the following limitations:

Data represents spot market offers, not contracted rates
Actual negotiated prices may differ from posted offer prices
Coverage varies by region - some routes have more data than others
Historical data reflects market conditions at capture time
We are not responsible for business decisions made based on this data

For mission-critical applications, we recommend combining our data with your own market intelligence.

Questions?

If you have questions about our methodology or data quality, please contact us at [email protected] or check our FAQ page.

Last updated: December 2024