Discover the top countries for online sales
Why we create this ranking
The study was carried out by Translated to guide business clients in their selection of markets and languages for internationalization projects and to help them get the best possible return on investment (ROI). T-Index was developed to help companies aiming to expand internationally to select their target markets and decide on the most suitable target languages when translating their website(s).
How to interpret the study
The country-specific T-Index and the product-specific T-Index are designed to guide companies in choosing the best languages and the best markets for the translation of their website. These versions take into account the country in which the company operates and from which the products will be exported and/or the particular product will be marketed, allowing for personalized and much more precise results.
Let’s see how it works.
A German company specializing in knives has a website in English and would like to have it translated into another language in order to expand into new markets. A market analysis shows that the company’s products have a good chance of succeeding in Japan, Spain and the Netherlands. Looking at the T-Index, the best country to focus on would therefore appear to be Japan: with a market share of 6.6%, it has greater potential for online sales than Spain and the Netherlands, which sit at 1.7% and 0.9% respectively.
However, if we refine the analysis by taking into consideration the exporting country and therefore the country-specific T-Index, we obtain a different result. In fact, if we are exporting from Germany, the Netherlands has the biggest market share at 6.9%, followed by Spain at 3.5% and finally Japan at 1.7%. If the company were based in Italy rather than Germany, the results would be different yet again and Spain would be the best market (5.4%), while the Netherlands and Japan would reach only 2.7% and 1.6% respectively.
We can go into even more detail by switching to the product-specific T-Index, i.e. by also considering the product that the company wants to sell online: knives. In this case, we get the following values for the product-specific
T-Index: Netherlands 5.3%, Spain 3.6%, and Japan 0.6%.
As we can see, Japan’s market share is further reduced compared to the result produced with the T-Index and the country-specific T-Index. If we consider a company that is also based in Germany but that specializes in screws and bolts, we get a different result, with Netherlands (3.5%) and Japan (3.5%) at the same level and Spain (1.2%) resulting much less attractive.
We can therefore see how the country-specific T-Index and the product-specific T-Index allows us to measure the potential for online sales.
The value of the country-specific T-Index is calculated by multiplying the flow of products between the exporting and importing countries by a correction factor that takes into account the wealth of the population segment with internet access in the arrival country. As explained below, this flow is obtained from the 2018 United Nations Commodity Trade (COMTRADE) data. We directly input a quantity that takes into account the volume of trade between the exporting and importing countries. The country-specific T-Index is available for the 169 countries covered by the COMTRADE database. Much in the same way, the value of the product-specific T-Index is obtained by multiplying the flow of the product in question between the departure and arrival countries by the same corrective factor, provided by the percentage of spending of internet users. The difference between the two indices therefore lies in the fact that the first takes into account the total flow between the two countries, while the second only uses the flow of the particular product that we want to export.
To calculate the country-specific T-Index we need three ingredients, namely trade flows between countries, internet penetration rate, and income distribution. A country’s internet penetration rate is calculated by dividing the number of people with internet access by the total population. Assuming we want to export goods from country A, the country-specific T-Index of country B is defined as:
(percentage of spending by internet users) * (total exports from A to B)
sum of the country-specific T-Index from country B to all possible importing countries
The percentage of spending by internet users is calculated by assuming that these users belong to the richest segment of the population, thus combining the data on internet penetration with the income distribution data. Similarly, if we are exporting a product P from country A, the product-specific T-Index of country B is calculated as:
(percentage of spending by internet users) * (total exports from A to B of product P)
sum of the product specific T-index from country B to all possible importing countries
For countries where no income distribution data was available, we used an estimate by averaging the distributions of other countries.
In Japan, the number of internet users is 118,333,485 out of a total population of 126,994,551. The internet penetration rate is therefore 93.18%. Using the country’s income distribution by quintiles, we estimated that 93.18% of the richest people in Japan spend 96.7% of the total expenditure of Japanese households. The flow of goods from Italy to Japan is 7852 million dollars, so the country-specific T-Index for exporting from Italy to Japan is:
96.7% * 7852
_______________________________________________________ = 1.56%
Similarly, if the product we are interested in is screws and bolts, the flow of this product from Italy to Japan is 2,77 million dollars, therefore the product- specific T-Index for exporting screws and bolts from Italy to Japan is:
96.7% * 2.77
_______________________________________________________ = 0.14%
The internet penetration in each country for the country-specific T-Index was obtained from the International Telecommunication Union (ITU) report titled ‘Proportion of individuals using the Internet’, while the income distribution by quintiles was obtained from statistical data from the World Bank’s Development Research Group. With regard to the data on trade flows between countries, we used a database built by our research group starting from the data collected by customs authorities and pre-processed by COMTRADE. In particular, the cleaning and reconstruction of the flows was carried out using special machine learning methods.
Countries and languages market share
Translating into these top languages lets you reach 80% of the online purchasing power worldwide. Furthermore, the markets with the higher online sales potential are listed below.
Want to know more? View the full list
There are still restrictions on Internet access
In certain countries, translating your website content may not be enough to transform local Internet users into potential customers. The map below shows the countries that currently impose restrictions on Internet access.
Source: Reporters Without Borders
Get insights to find the best market in which to sell online
|Country||T-Index||Internet users||Internet penetration rate||Expenditure p.c. (Internet users)**|
* The arrows and dash indicate the country’s projected performance in the 2021 rankings
** Estimated annual expenditure of each Internet user
*** The United Kingdom consists of four countries: England, Scotland, Wales and Northern Ireland
This ranking may be freely shared if a link back to this page is provided and it is made clear to users that the data comes from the T-Index study. Please copy and paste the following statement:
“T-Index Study 2018, by Translated. Translated is the leading online professional translation service provider, with 195,030 international customers and 241,597 vetted translators.”
Many thanks to all the people who provided us with useful data or tips:
Luciano Pietronero, Physics professor, CNR-ISC and Sapienza University
together with Giordano De Marzo – Ph.D. Student, University Sapienza – and Andrea Zaccaria – Researcher, ISC
Salvatore Giammarresi, Head of Localization, Airbnb
Daniel Goldschmidt, Speaker and educator in Software Internalization and Localization
Mark Lammers, Director, Management Consulting Services, Point B
Sergio Pelino, Localization Operations Senior Manager, Airbnb
Danielle Schweisguth, Economist at Société Générale, Coach
Brian Solis, Global Innovation Evangelist, Salesforce
Natalia Tsvetkov, Business Intelligence Engineer, Blueprint Technologies
Photo credits: Randi Tarampi, Unsplash