Global trade refers to the buying and selling of products, services, and capital among the countries of the world. The need for foreign trade arises from the fact that no nation is self-sufficient when it comes to all goods and services.
Most countries need to buy their deficit goods and services from different countries. In other words, international trade is a stimulus to a growing world. It helps in optimum utilization of a country’s resources.
Moreover, it allows countries to sustain their economies by selling their surplus goods to those who need them. Further, global trade is of two types, i.e., bilateral trade or import/ export between two countries and multilateral trade, i.e., business between more than two countries.
What’s The Significance Of Trade Data?
Global trade data comprises meta-information regarding all the international trade that takes place around the globe. The data also reflects the economic health of countries while giving a glimpse of their manufacturing capacity.
As per the theory of economic growth, a country’s exports should always increase in relation to its imports. That’s the only way for a country to overcome their respective trade deficits.
Global trade data contains shipping information containing importers and exporters, HS Codes, product-related information, value, quantity, origin, and destination port information.
Who Uses The Information From Trade Data?
The trade data generally comes in handy for exporters who better understand the trading scenario and sales opportunities in countries for their products and services. They also use data intelligence tools to generate valuable insights, which further help them in making critical managerial decisions.
Also, they formulate their different sales strategy based on predictions and projections generated by data intelligence algorithms which use global trade data as inputs. Furthermore, the shipping and logistics companies, government agencies, and customs departments also collect trade data to facilitate international trade.
Besides generating future trade projections, global trading partners also evaluate potential buyers based on their respective trade histories. Trade data intelligence algorithms are modulated to take trade statistics by country as inputs and reflect detailed information regarding potential markets and rivals in the business.
Various Approaches Of Using Trade Data
Trade data is used by import/ export entities in various manners. Broadly, there are three approaches to conducting data-based analysis. However, it is not necessary for companies to rely on an individual approach as they can also opt to use multiple approaches or formulate their own based on a combination of various approaches.
- Country Based Approach
In the country-based approach, which is also known as the market-based approach, data of trade between various countries is taken into account. It includes import and export statistics, duties and taxes, transportation costs and scenarios, geopolitical factors, among other attributes.
After that, analysts prepare a report of trade statistics by country and use the same to generate insights like future opportunities in the region and profitability of a business in the country. It is a normal practice to combine a country-based approach and a product-based approach, which we will discuss next.
- Product Based Approach
The next approach that trade businesses use is the product-based approach. In this method, market analysis is done by keeping specific products in focus. For example, an automobile exporter doesn’t need to include the scenario of food and beverages import and export between two regions. That is when a product-based approach comes into play.
They evaluate the trade data of a specific product between two regions and generate valuable insights to steer their business plan in the right direction. In modern data intelligence tools, there is an option to combine several products to form a product category and then run the analysis to better view the trade scenario.
- Business Based Approach
The business-based approach or entity-based approach is the final trade data analysis approach which traders use. It is the most simple approach as it only takes into account the particular business or entities with which the supplier wants to explore trade opportunities.
For example, a car upholstery manufacturer based in Bangladesh may wish to sell their products to Chevrolet automobiles in the USA. To explore their chances, they may want to take into account the trade data of Chevrolet.
For example, where do they import their current lot from? Do they have an in-house production team? They even may want to know the timeline when the automobile releases tenders for the same.
How Is Trade Data Intelligence Going To Affect International Business?
As of today, all the major global trading companies use trade data intelligence for market research and analysis. However, entering the international markets without knowing the scenario is like going for a trek without a map. Therefore, we can comfortably state that businesses that aim to make it big in the international markets will continue to trust trade data intelligence tools for their business. That only will make them stand out from the crowd.