T-Index 2012, the markets that matter on the web

T-Index

Which markets offer the most potential for your website?


T-Index is a statistical index that shows online market share per country. It combines the Internet population and its estimated GDP per capita.

T-Index assists companies in identifying their target markets and in selecting the right languages to translate their websites. This helps ensure online success and increase localization-derived revenue.

The study was conducted by Translated, a language service provider that has offered professional translation services for over 10 years, helping its customers achieve the best ROI from their website translation investments.

The underlying criteria for the study are described below.

2012 Data summary

T-Index for beginners

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Trend* Countries T-Index
2012
Projection
2016
Languages Internet population Internet
penetration
GDP p.c. of Int. pop.**
Download CSV
(!) Restricted access to internet.
* The arrows and the dash indicate the country's performance in the 2016 ranking.
** GDP per capita of the Internet population
Note: The Internet population of North Korea and the GDP per capita of the Internet population of the Vatican were estimated by our agency.
1
USA 22.5% 15.6% 1 245,203,319 78.1% $58,751
2
China (!) 13.5% 20.1% 1 538,000,000 40.1% $16,133
3
Japan 6.3% 4.6% 1 101,228,736 79.5% $39,863
4
Germany 4.6% 3.9% 1 67,483,860 83.0% $43,476
5
UK 3.4% 2.6% 1 52,731,209 83.6% $41,654
Localizing a website for these 5 markets gives you access to 50% of the worldwide online sales potential.
6
France 3.4% 3.2% 1 52,228,905 79.6% $41,580
7
Brazil 3.1% 4.3% 1 88,494,756 44.4% $22,265
8
Russia 2.9% 3.6% 1 67,982,547 47.7% $27,362
9
South Korea 2.4% 2.1% 1 40,329,660 82.5% $37,667
10
Italy 2.3% 1.3% 1 35,800,000 58.4% $41,797
11
Canada 2.1% 1.6% 2 28,469,069 83.0% $46,743
12
Mexico 2.0% 2.0% 1 42,000,000 36.5% $30,078
13
Spain 2.0% 1.8% 2 31,606,233 67.2% $39,625
14
India 1.8% 2.3% 2 137,000,000 11.4% $8,411
15
Australia 1.4% 1.1% 1 19,554,832 88.8% $45,848
16
Turkey 1.3% 1.7% 1 36,455,000 45.7% $23,524
17
Taiwan 1.3% 1.1% 1 17,530,000 75.4% $48,268
18
Iran (!) 1.2% 1.8% 1 42,000,000 53.3% $18,351
19
Netherlands 1.1% 0.93% 1 15,549,787 92.9% $45,192
20
Argentina 1.1% 1.4% 1 28,000,000 66.4% $24,485
21
Poland 1.0% 1.3% 1 24,940,902 64.9% $26,889
Localizing a website for these 21 markets gives you access to 80% of the worldwide online sales potential.
22
Indonesia 0.86% 1.0% 1 55,000,000 22.1% $10,078
23
Saudi Arabia (!) 0.76% 1.1% 1 13,000,000 49.0% $37,713
24
Colombia 0.67% 1.0% 1 26,936,343 59.5% $15,999
25
Malaysia 0.65% 0.66% 1 17,723,000 60.7% $23,340
26
Thailand 0.62% 0.78% 1 20,100,000 30.0% $19,701
27
Sweden 0.58% 0.44% 1 8,441,718 92.7% $44,308
28
Belgium 0.58% 0.53% 2 8,489,901 81.3% $43,453
29
United Arab Emirates 0.57% 0.58% 1 5,859,118 70.9% $62,030
30
Hong Kong 0.53% 0.42% 1 5,329,372 74.5% $63,832
31
South Africa 0.51% 0.43% 2 8,500,000 17.4% $38,716
32
Switzerland 0.51% 0.40% 3 6,509,247 82.1% $50,330
33
Austria 0.50% 0.43% 1 6,559,355 79.8% $48,942
34
Egypt 0.49% 0.71% 1 29,809,724 35.6% $10,450
35
Singapore 0.48% 0.46% 2 4,015,121 75.0% $76,670
36
Nigeria 0.45% 0.71% 1 48,366,179 28.4% $5,973
37
Philippines 0.43% 0.64% 1 33,600,000 32.4% $8,279
38
Venezuela 0.41% 0.57% 1 12,097,156 43.1% $21,815
Localizing a website for these 38 markets gives you access to 90% of the worldwide online sales potential.
39
Norway 0.40% 0.32% 1 4,560,572 96.9% $55,572
40
Chile 0.39% 0.36% 1 10,000,000 58.6% $25,106
41
Czech Republic 0.36% 0.33% 1 7,426,376 73.0% $30,921
42
Greece 0.35% 0.28% 1 5,706,948 53.0% $38,925
43
Peru 0.34% 0.41% 1 10,785,573 36.5% $20,252
44
Israel 0.33% 0.35% 1 5,313,530 70.0% $40,412
45
Denmark 0.32% 0.23% 1 4,989,108 90.0% $41,106
46
Portugal 0.31% 0.12% 1 5,950,449 55.2% $33,107
47
Qatar 0.30% 0.29% 1 1,682,271 86.2% $115,207
48
Vietnam (!) 0.30% 0.43% 1 31,034,900 33.9% $6,152
49
Finland 0.29% 0.25% 1 4,703,480 89.4% $40,093
50
Romania 0.29% 0.30% 1 9,642,383 44.1% $19,024
51
Ukraine 0.28% 0.40% 1 15,300,000 34.1% $11,704
52
Ireland 0.27% 0.21% 1 3,627,462 76.8% $47,942
53
Pakistan 0.26% 0.32% 1 29,128,970 15.3% $5,736
54
Hungary 0.26% 0.28% 1 6,516,627 65.4% $25,409
55
Kazakhstan 0.25% 0.37% 1 7,884,905 45.0% $20,087
56
Morocco 0.20% 0.27% 1 16,477,712 51.0% $7,955
57
New Zealand 0.19% 0.13% 1 3,810,144 88.0% $31,688
58
Slovakia 0.19% 0.22% 1 4,337,868 79.1% $27,513
59
Ecuador 0.16% 0.21% 1 6,663,558 43.8% $15,148
60
Kuwait 0.16% 0.14% 1 1,963,565 74.2% $51,105
61
Belarus (!) 0.15% 0.19% 1 4,436,800 46.0% $21,579
62
Algeria 0.13% 0.20% 1 5,230,000 14.0% $15,804
63
Dominican Rep 0.12% 0.18% 1 4,643,393 46.0% $16,391
64
Azerbaijan 0.12% 0.17% 1 4,746,800 50.0% $15,763
65
Croatia 0.11% 0.11% 1 3,167,838 70.7% $23,013
66
Tunisia 0.11% 0.17% 1 4,196,564 39.1% $17,338
67
Oman 0.11% 0.17% 1 2,101,302 68.0% $34,282
68
Bulgaria 0.11% 0.10% 1 3,589,347 51.0% $19,387
69
Serbia 0.093% 0.14% 1 4,107,000 56.4% $14,580
70
Angola 0.092% 0.035% 1 2,976,657 16.5% $19,878
71
Lithuania 0.092% 0.099% 1 2,293,508 65.1% $25,795
72
Cuba (!) 0.086% 0.14% 1 2,572,779 23.2% $21,534
73
Uzbekistan (!) 0.086% 0.13% 1 8,575,042 30.2% $6,426
74
Syria (!) 0.085% 0.14% 1 5,069,418 22.5% $10,690
75
Slovenia 0.081% 0.069% 1 1,440,066 72.1% $36,163
76
Lebanon 0.080% 0.089% 1 2,152,950 52.0% $23,914
77
Kenya 0.075% 0.080% 1 12,043,735 28.0% $3,990
78
Sri Lanka 0.072% 0.092% 1 3,222,200 15.0% $14,328
79
Uruguay 0.070% 0.092% 1 1,855,000 55.9% $24,173
80
Puerto Rico 0.070% 0.034% 1 1,771,643 48.0% $25,213
81
Costa Rica 0.067% 0.073% 1 2,000,000 43.1% $21,599
82
Luxembourg 0.066% 0.053% 1 462,697 90.9% $91,669
83
Sudan 0.063% 0.081% 1 6,499,275 19.0% $6,199
84
Panama 0.062% 0.088% 1 1,503,441 42.8% $26,427
85
Bolivia 0.056% 0.065% 1 3,087,000 30.0% $11,579
86
Guatemala 0.055% 0.084% 1 2,280,000 16.2% $15,413
87
Bahrain (!) 0.050% 0.058% 1 961,228 77.0% $33,614
88
Latvia 0.049% 0.041% 1 1,570,925 71.7% $19,942
89
Libya 0.049% 0.046% 1 954,275 17.0% $32,610
90
Bangladesh 0.047% 0.041% 1 8,054,190 5.0% $3,716
91
Ghana 0.044% 0.044% 1 3,568,757 14.5% $7,906
92
El Salvador 0.043% 0.045% 1 1,491,480 24.5% $18,420
93
Bosnia-Herzegovina 0.042% 0.058% 1 2,327,578 60.0% $11,644
94
Cyprus 0.042% 0.035% 1 656,439 57.7% $41,274
95
Estonia 0.039% 0.030% 1 993,785 78.0% $25,054
96
Jordan 0.038% 0.054% 1 2,481,940 38.1% $9,912
97
Paraguay 0.036% 0.054% 1 1,563,440 23.9% $14,561
98
Jamaica 0.034% 0.027% 1 1,581,100 54.7% $13,794
99
Yemen 0.032% 0.037% 1 3,691,000 14.9% $5,575
100
Trinidad & Tobago 0.032% 0.045% 1 650,611 53.1% $31,126
101
Tanzania 0.031% 0.026% 1 5,629,532 12.0% $3,549
102
Iraq 0.030% 0.031% 1 2,211,860 7.1% $8,588
103
Brunei Darussalem 0.029% 0.035% 1 318,900 78.0% $59,288
104
Macedonia 0.029% 0.036% 1 1,180,704 56.7% $15,881
105
Honduras 0.028% 0.039% 1 1,319,174 15.9% $13,382
106
Albania 0.027% 0.048% 1 1,471,400 49.0% $11,748
107
Macau 0.026% 0.031% 1 366,510 63.4% $45,194
108
Georgia 0.023% 0.038% 1 1,300,000 28.4% $11,531
109
Botswana 0.023% 0.024% 1 268,620 12.8% $55,641
110
Uganda 0.023% 0.036% 1 4,376,672 13.0% $3,407
111
Armenia 0.021% 0.025% 1 1,800,000 60.6% $7,321
112
Mauritius 0.020% 0.022% 1 458,927 35.0% $28,281
113
Iceland 0.018% 0.013% 1 304,129 97.1% $37,674
114
Senegal 0.016% 0.015% 1 2,269,681 17.5% $4,478
115
Malta 0.015% 0.013% 1 282,648 69.0% $33,672
116
Kyrgyzstan 0.014% 0.024% 1 2,194,400 39.9% $4,153
117
Bahamas 0.014% 0.021% 1 235,797 74.6% $38,631
118
Moldova 0.014% 0.020% 1 1,639,463 44.8% $5,383
119
Zambia 0.012% 0.015% 1 1,589,010 11.5% $5,043
120
Nepal 0.012% 0.014% 1 2,690,162 9.0% $2,860
121
Mongolia 0.011% 0.011% 1 635,999 20.0% $11,058
122
Namibia 0.011% 0.011% 1 259,899 12.0% $26,068
123
Barbados 0.0096% 0.012% 1 199,915 69.5% $30,879
124
Nicaragua 0.0095% 0.014% 1 783,800 13.7% $7,758
125
Kosovo 0.0089% 0.018% 1 377,000 20.5% $15,093
126
Cameroon 0.0084% 0.012% 1 1,006,494 5.0% $5,366
127
Montenegro 0.0084% 0.011% 1 328,375 50.0% $16,385
128
Gabon 0.0080% 0.0092% 1 128,665 8.0% $39,714
129
Turkmenistan (!) 0.0075% 0.0073% 1 252,741 5.0% $19,031
130
Tajikistan 0.0067% 0.011% 1 1,012,220 13.0% $4,213
131
Jersey 0.0063% 0.0065% 1 45,800 48.2% $87,943
132
Cote D'Ivoire 0.0060% 0.0099% 1 968,000 4.4% $3,983
133
Suriname 0.0060% 0.0089% 1 179,250 32.0% $21,511
134
Guyana 0.0060% 0.0060% 1 250,274 33.7% $15,350
135
Laos 0.0059% 0.0095% 1 592,764 9.0% $6,411
136
Congo 0.0059% 0.0092% 1 295,132 6.8% $12,875
137
Swaziland 0.0059% 0.0061% 1 251,448 18.1% $14,970
138
Cambodia 0.0058% 0.0063% 1 662,840 4.4% $5,591
139
Haiti 0.0055% 0.0077% 1 836,435 8.5% $4,211
140
Rwanda 0.0051% 0.0067% 1 818,048 7.0% $3,961
141
Liechtenstein 0.0048% 0.011% 1 31,206 85.0% $98,538
142
Mozambique 0.0047% 0.0043% 1 1,011,185 4.3% $2,977
143
Andorra 0.0046% 0.0080% 1 68,916 81.0% $43,027
144
Afghanistan 0.0045% 0.0073% 1 1,520,996 5.0% $1,903
145
Zimbabwe 0.0042% 0.0038% 1 1,981,277 15.7% $1,369
146
Guernsey 0.0041% 0.0021% 1 48,300 73.9% $54,598
147
Fiji 0.0038% 0.0035% 1 247,275 27.8% $9,789
148
Bhutan 0.0034% 0.0036% 1 150,548 21.0% $14,390
149
Monaco 0.0034% 0.0026% 1 30,700 84.4% $70,370
150
Ethiopia 0.0034% 0.0040% 1 960,331 1.1% $2,242
151
Saint Lucia 0.0033% 0.0036% 1 142,900 88.1% $14,684
152
Maldives 0.0032% 0.0048% 1 134,860 34.2% $15,414
153
Greenland 0.0032% 0.0031% 1 52,000 90.1% $38,877
154
Equatorial Guinea 0.0031% 0.0032% 1 42,024 6.1% $46,579
155
Seychelles 0.0030% 0.0030% 1 38,854 43.2% $49,960
156
Antigua & Barbuda 0.0029% 0.0035% 1 74,057 83.2% $25,528
157
Burkina Faso 0.0029% 0.0029% 1 518,253 3.0% $3,575
158
Myanmar (!) 0.0027% 0.0021% 1 534,930 1.0% $3,267
159
Belize 0.0026% 0.0032% 1 74,700 22.8% $22,209
160
Cape Verde 0.0023% 0.0036% 1 167,542 32.0% $8,897
161
Malawi 0.0023% 0.0041% 1 716,400 4.4% $2,031
162
Faroe Islands 0.0022% 0.0023% 1 39,948 80.7% $35,395
163
Benin 0.0018% 0.00052% 1 335,957 3.5% $3,525
164
Mali 0.0018% 0.0025% 1 414,985 2.7% $2,839
165
Gambia 0.0018% 0.0022% 1 200,057 10.9% $5,762
166
St Vincent & Grenadines 0.0018% 0.0031% 1 76,000 73.4% $14,853
167
Madagascar 0.0016% 0.0023% 1 418,099 1.9% $2,439
168
Papua New Guinea 0.0015% 0.00062% 1 135,000 2.1% $7,339
169
Chad 0.0015% 0.0022% 1 208,537 1.9% $4,615
170
Grenada 0.0014% 0.0016% 1 37,860 34.7% $24,545
171
San Marino 0.0014% 0.0020% 1 17,000 52.9% $53,301
172
Dem Rep Of The Congo 0.0013% 0.0017% 1 915,400 1.2% $914
173
Mauritania 0.0013% 0.0014% 1 151,163 4.5% $5,419
174
Dominica 0.0012% 0.0012% 1 37,520 51.3% $20,953
175
Togo 0.0011% 0.0011% 1 356,300 5.1% $1,948
176
Eritrea 0.0011% 0.0014% 1 377,363 6.2% $1,797
177
St Kitts & Nevis 0.00094% 0.00094% 1 22,480 44.3% $26,785
178
Tonga 0.00067% 0.00070% 1 26,479 24.9% $16,177
179
Niger 0.00063% 0.00078% 1 212,480 1.3% $1,888
180
Djibouti 0.00061% 0.00084% 1 61,320 7.9% $6,383
181
Central African Rep 0.00057% 0.00065% 1 150,920 3.0% $2,429
182
Guinea 0.00057% 0.00066% 1 141,504 1.3% $2,580
183
Lesotho 0.00055% 0.00067% 1 83,813 4.3% $4,189
184
Solomon Islands 0.00043% 0.00041% 1 34,313 5.9% $8,121
185
Samoa 0.00041% 0.00037% 1 17,940 9.2% $14,583
186
Vanuatu 0.00036% 0.00051% 1 19,172 7.5% $11,974
187
Sao Tome And Principe 0.00034% 0.000001% 1 36,928 20.2% $5,844
188
Sierra Leone 0.00034% 0.00029% 1 69,240 1.3% $3,112
189
North Korea (!) 0.00033% 0.00060% 1 50,000 0.2% $4,240
190
Somalia 0.00028% 0.00019% 1 126,070 1.2% $1,413
191
Comoros 0.00027% 0.00028% 1 40,550 5.5% $4,303
192
Burundi 0.00026% 0.00035% 1 176,040 1.7% $954
193
Micronesia 0.00024% 0.00019% 1 22,213 20.9% $6,834
194
Kiribati 0.00024% 0.00025% 1 10,074 9.9% $15,062
195
Liberia 0.00018% 0.00017% 1 116,637 3.0% $1,004
196
Guinea Bissau 0.00017% 0.00017% 1 43,484 2.7% $2,546
197
Palau 0.00015% 0.00012% 1 6,360 30.2% $15,525
198
Cook Islands 0.00012% 0.000100% 1 6,000 55.7% $13,067
199
East Timor 0.00011% 0.000096% 1 10,293 0.9% $6,795
200
Marshall Islands 0.000067% 0.000064% 1 7,260 10.6% $5,888
201
Tuvalu 0.000038% 0.000059% 1 4,300 40.5% $5,596
202
Vatican City State 0.000037% 0.000050% 1 480 57.4% $49,522
203
Niue 0.000011% 0.000006% 1 1,100 86.7% $6,269
204
Nauru 0.000009% 0.000001% 1 480 5.1% $11,776

2016 T-Index Projection | NEW!


The markets with the highest potential for online sales

T-Index Map - 2012

T-Index is a percentage value that indicates the online market share of each country on the Internet by combining the Internet population and its estimated GDP per capita. The higher the T-Index, the higher the online sales potential in a country.

Internet Freedom Map

In certain countries, translating your website content may not be enough to transform local Internet users into potential customers. Above is a map of countries currently imposing restrictions on Internet access. | Source: Reporters without Borders http://en.rsf.org

T-Index for beginners


T-Index was developed to help companies identify their target markets and select the appropriate languages for translating their websites.

Choosing among different potential markets is not easy. T-Index helps identify the market-language combination most appropriate for your investment with regards to customer base and online sales potential.

With a T-Index of 22,5%, the Unites States is the market with the highest potential for online sales. As such, it comprises 245 million internet users worldwide with an average GDP per capita of $ 58,751.

Before localizing a website for any country, we recommend you fully understand the local market and country, to ascertain whether the market is accessible.

Have you considered the following?

Example 1

An England-based company, specializing in the sale of winter sports merchandise has a website in English and would like to translate it into another European language. After conducting market research, the marketing manager concludes that their products would certainly be successful in Germany, Sweden and Norway. By accessing the T-Index, it quickly becomes clear that Germany, with a 4.6% market share is the market with the greatest potential for online sales because it covers 67,483,860 Internet users with an average $ 43,476 per-capita GDP. The T-Index has been decisive in choosing German as a language for the new site.

Example 2

A Canada-based company has a website in English and French and would like to translate into another language. By accessing the T-Index ranked by language, the marketing manager realizes quickly that Simplified Chinese, Spanish, Japanese and German are, in 2012, the languages with the highest online potential. By clicking on the sign on the data summary table for a complete overview of the countries covered by these four linguistic markets, the manager thinks about the fact that the Chinese language market includes two countries, while those that speak Spanish, Japanese and German respectively comprise twenty-one, one and four countries. After studying the markets in question, he realizes that his company would have access only to the following markets: Singapore, Mexico, Spain, Japan and Germany for various considerations related to logistics, financial, competitive and cultural aspects. This gives the following real values for the four languages considered:

For the Canadian company, Japanese demonstrates having a market share larger than all the others. Therefore, the company choses to translate its website into Japanese to develop their online business.

2016 Projection


To calculate the projection through 2016, we have extrapolated a line between the 2005 and 2012 data points using Simple Linear Regression*. The projection assumes a linear growth trend for all countries.

According to the T-Index projection, China could overtake the United States and take first place in 2015, with a market share of 18.5% compared to 13.5% in 2012. Actually, the United States on line purchasing power would change from 22.5% in 2012 to 17.3% in 2015. In 2016, China would retain the top spot and is widening the gap with the United States showing a 20.1% market share compared to 15.6% for the United States.

Japan would maintain its third place until 2016, despite a drop of -26.9% in its market share compared to 2012.

With a change in its market share estimated at + 16.1%, Brazil could win fifth place in 2013 and go pass the UK and France. In 2016, it could even climb to fourth place, also leaving Germany behind, which would suffer a 15.2% drop compared to 2012.

Russia would change from eighth to seventh place in 2013, and down to sixth place in 2014 with a 17.2% variation compared to 2012.

France would lose one place in 2014 with a -2.9% change compared to 2012.

The United Kingdom would go from fifth to eighth place in 2013, with a change in its market share equal to -5.9% compared to 2012.

South Korea would hold ninth place until 2016 despite a 12.5% variation ​​compared to 2012.

The surprise comes from Mexico which would enter the top 10 as of 2013, taking the Italy's place which would undergo a -17.4% drop between 2012 and 2013.

All emerging countries including China, Brazil, Poland, Russia, India/English, Nigeria and Vietnam see growth in the 2016 projection. The top emerging countries by growth would be Nigeria (+55,6%), China (+48,8%), Vietnam (+43,3%), Brazil (+35,4%) and Poland (+30%).

* See Wikipedia for further information:
http://en.wikipedia.org/wiki/Linear_regression

The study

Assumptions and method

T-Index was developed to help companies choose their target markets and the right languages for translating their websites.

Each country has been assessed according to a single language, except where the T-index value of the country is in excess of 0.1%, in which case we have assessed the country within several language markets. For example, Switzerland, which has a T-index of 0.51%, has been assessed in three different language markets (German, French, and Italian). As country language, we have considered that used for business, written communication, and the Internet.

A lot of languages in use today are not yet represented on the Internet. In many African and Caribbean countries, for example, English is the official language and often the unifying language, widely used in government, public administration, education, business and online. Local languages are often spoken as everyday informal languages by the majority of the population. The T-Index study only considered languages that are used for business, written communication, and the Internet.

Languages that have international variations depending on the country have been grouped together into their respective standard language. As an example, UK English and US English have been classified under the English language.

Dependent territories have been evaluated according to the governing state, if they share the same language. If they do not share the same language, as is the case with Puerto Rico and the United States, they are included as separate entries based on the language market they belong to.

The T-Index study includes every country for which we were able to find data concerning the number of Internet users and GDP per capita. Without such data, it would have been impossible to make an evaluation.

Furthermore, in order to determine the GDP per capita of the Internet population, we made the assumption that Internet users in each country belong to the richest segment of the country’s population. We did this because T-Index is meant to gauge commercial opportunity and is aimed at identifying people who have the financial means and tools to surf and buy on the web.

Firstly, we gathered information about the number of Internet users and the total population, from which we determined the Internet penetration rate* for each country. We then analyzed each country's GDP per capita and income distribution to determine the proportion of GDP which is theoretically earned by Internet users, the average Internet user GDP per capita. Finally, from this information, we were able to establish a value for each country.

For those countries where income distribution data was not available, we calculated the average income distribution for all countries and used this estimate.

The T-Index is a useful tool for companies making website translation decisions. But other factors, not just the absolute sizes of each market, need to be considered when choosing languages for translation (factors like local market demand, competition, etc.). Website translation is a necessary step towards attracting new customers, but other key factors, such as the quality of the products and services or the user-friendliness of the interface, are essential in attracting new customers and ensuring they make a buying decision.

Example

In Japan, the number of Internet users is 101.228.736 out of a total population of 127.368.088. The Internet penetration rate is 79.5%. The estimated GDP per capita of Japan for 2012 is $35.578,219. According to income distribution by quintiles, we estimated that 79.5% of the richest Japanese earn 89.05% of Japan’s wealth. To obtain the GDP per capita of the Internet population, we made a simple calculation:

(total population x GDP per capita x part of wealth earned by Internet users) / number of Internet users

of Japan: (127.368.088 x 35.578,219 x 89.05%) / 101.228.736
The estimated GDP per capita of the Internet population in Japan is $39.863.

To obtain the T-Index value, we multiplied the number of Internet users by the average GDP per capita of the Internet population. For Japan this is: 101.228.736 x $39.863. Finally, to obtain a percentage value for each country, we divided each country's T-Index value by the sum of T-Index values of all countries. This explains how we obtained a share potential of 6.3% for Japan.

*The Internet penetration rate is the percentage of Internet users in a country.

Sources

Statistics used in the T-Index study were taken from the following reliable Internet based sources.

The number of Internet users for each country was taken from the Internet World Stats website which provides up-to-date world Internet statistics. The statistics were up-to-date as of June 30, 2012.

In order to assign each country to a language market, we looked at the most commonly used languages in business, and online, in each country in question. Our worldwide network of freelance translators has also contributed to the project, helping to make it a reliable tool that reflects the reality of each country.

The total population of each country was taken from the Central Intelligence Agency World Factbook. The statistics were estimates from the US Census Bureau, July, 2012. For countries whose total population was not specified in the CIA World Factbook, data were extracted from official statistical sources in each country.

GDP (Gross Domestic Product) per capita data were taken from the International Monetary Fund World Economic Outlook Database. The data refer to 2012 and is presented in current international dollars. For the countries or territories for which the GDP per capita was not indicated in the International Monetary Fund World Economic Outlook Database, the data were taken from the Central Intelligence Agency World Factbook.

To determine if a country has restricted access to online information, we looked at the ranking given by the international non-governmental organization Reporters without Borders, available on its official website: http://en.rsf.org/internet.html.

The percentage shares of income indicated by quintiles were taken from the online statistical data of the World Bank's Development Research Group: http://data.worldbank.org/indicator/SI.DST.05TH.20. Not all the data refer to the same year (the World Bank data are from 1992 to 2011).

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The T-Index Study www.translated.net/en/languages-that-matter was carried out by Translated, a language service provider founded in 1999 that manages 68.000 translators in over 110 countries for 26.000 customers. In 2008, Translated was selected by Eurispes as representative of Italy's Excellence. Worldwide, Translated ranks amongst the most innovative LSPs in the development of productive processes to help translators in their daily endeavours.

Credits

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