Cover --; Contents --; 1 INTRODUCTION --; 1.1 OVERVIEW --; 1.2 WHAT IS LATENT DEMAND AND THE P.I.E.? --; 1.3 THE METHODOLOGY --; 1.3.1 Step 1. Product Definition and Data Collection --; 1.3.2 Step 2. Filtering and Smoothing --; 1.3.3 Step 3. Filling in Missing Values --; 1.3.4 Step 4. Varying Parameter, Non-linear Estimation --; 1.3.5 Step 5. Fixed-Parameter Linear Estimation --; 1.3.6 Step 6. Aggregation and Benchmarking --; 1.3.7 Step 7. Latent Demand Density: Allocating Across Cities --; 2 SUMMARY OF FINDINGS --; 2.1 THE WORLDWIDE MARKET POTENTIAL --; 3 AFRICA, EUROPE & THE MIDDLE EAST --; 3.1 EXECUTIVE SUMMARY --; 3.2 AFGHANISTAN --; 3.3 ALBANIA --; 3.4 ALGERIA --; 3.5 ANDORRA --; 3.6 ANGOLA --; 3.7 ARMENIA --; 3.8 AUSTRIA --; 3.9 AZERBAIJAN --; 3.10 BAHRAIN --; 3.11 BELARUS --; 3.12 BELGIUM --; 3.13 BENIN --; 3.14 BOSNIA AND HERZEGOVINA --; 3.15 BOTSWANA --; 3.16 BULGARIA --; 3.17 BURKINA FASO --; 3.18 BURUNDI --; 3.19 CAMEROON --; 3.20 CAPE VERDE --; 3.21 CENTRAL AFRICAN REPUBLIC --; 3.22 CHAD --; 3.23 COMOROS --; 3.24 CONGO (FORMERLY ZAIRE) --; 3.25 COTE D'IVOIRE --; 3.26 CROATIA --; 3.27 CYPRUS --; 3.28 CZECH REPUBLIC --; 3.29 DENMARK --; 3.30 DJIBOUTI --; 3.31 EGYPT --; 3.32 EQUATORIAL GUINEA --; 3.33 ESTONIA --; 3.34 ETHIOPIA --; 3.35 FINLAND --; 3.36 FRANCE --; 3.37 GABON --; 3.38 GEORGIA --; 3.39 GERMANY --; 3.40 GHANA --; 3.41 GREECE --; 3.42 GUINEA --; 3.43 GUINEA-BISSAU --; 3.44 HUNGARY --; 3.45 ICELAND --; 3.46 IRAN --; 3.47 IRAQ --; 3.48 IRELAND --; 3.49 ISRAEL --; 3.50 ITALY --; 3.51 JORDAN --; 3.52 KAZAKHSTAN --; 3.53 KENYA --; 3.54 KUWAIT --; 3.55 KYRGYZSTAN --; 3.56 LATVIA --; 3.57 LEBANON --; 3.58 LESOTHO --; 3.59 LIBERIA --; 3.60 LIBYA --; 3.61 LIECHTENSTEIN --; 3.62 LITHUANIA --; 3.63 LUXEMBOURG --; 3.64 MADAGASCAR --; 3.65 MALAWI --; 3.66 MALI --; 3.67 MALTA --; 3.68 MAURITANIA --; 3.69 MAURITIUS --; 3.70 MOLDOVA --; 3.71 MONACO --; 3.72 MOROCCO --; 3.73 MOZAMBIQUE --; 3.74 NAMIBIA --; 3.75 NIGER --; 3.76 NIGERIA --; 3.77 NORWAY --; 3.78 OMAN --; 3.79 PAKISTAN --; 3.80 PALESTINE --; 3.81 POLAND --; 3.82 PORTUGAL --; 3.83 QATAR --; 3.84 REPUBLIC OF CONGO --; 3.85 REUNION --; 3.86 ROMANIA --; 3.87 RUSSIA --; 3.88 RWANDA --; 3.89 SAN MARINO --; 3.90 SAO TOME E PRINCIPE --; 3.91 SAUDI ARABIA --; 3.92 SENEGAL --; 3.93 SIERRA LEONE --; 3.94 SLOVAKIA --; 3.95 SLOVENIA --; 3.96 SOMALIA --; 3.97 SOUTH AFRICA --; 3.98 SPAIN --; 3.99 SUDAN --; 3.100 SWAZILAND --; 3.101 SWEDEN --; 3.102 SWITZERLAND --; 3.103 SYRIAN ARAB REPUBLIC --; 3.104 TAJIKISTAN --; 3.105 TANZANIA --; 3.106 THE GAMBIA --; 3.107 THE NETHERLANDS --; 3.108 THE UNITED ARAB EMIRATES --; 3.109 THE UNITED KINGDOM --; 3.110 TOGO --; 3.111 TUNISIA --; 3.112 TURKEY --; 3.113 TURKMENISTAN --; 3.114 UGANDA --; 3.115 UKRAINE --; 3.116 UZBEKISTAN --; 3.117 WESTERN SAHARA --; 3.118 YEMEN --; 3.119 ZAMBIA --; 3.120 ZIMBABWE --; 4 ASIA --; 4.1 EXECUTIVE SUMMARY --; 4.2 BANGLADESH --; 4.3 BHUTAN --; 4.4 BRUNEI --; 4.5 BURMA --; 4.6 CAMBODIA --; 4.7 CHINA --T
This econometric study covers the world outlook for search engine optimization (SEO) and Internet marketing across more than 200 countries. For each year reported, estimates are given for the latent demand, or potential industry earnings (P.I.E.), for the country in question (in millions of U.S. dollars), the percent share the country is of the region and of the globe. These comparative benchmarks allow the reader to quickly gauge a country vis-à-vis others. Using econometric models which project fundamental economic dynamics within each country and across countries, latent demand estimates are created. This report does not discuss the specific players in the market serving the latent demand, nor specific details at the product level. The study also does not consider short-term cyclicalities that might affect realized sales. The study, therefore, is strategic in nature, taking an aggregate and long-run view, irrespective of the players or products involved. This study does not report actual sales data (which are simply unavailable, in a comparable or consistent manner in virtually all of the 230 countries of the world). This study gives, however, my estimates for the worldwide latent demand, or the P.I.E. for search engine optimization (SEO) and Internet marketing. It also shows how the P.I.E. is divided across the world's regional and national markets. For each country, I also show my estimates of how the P.I.E. grows over time (positive or negative growth). In order to make these estimates, a multi-stage methodology was employed that is often taught in courses on international strategic planning at graduate schools of business.
Web search engines -- Economic aspects -- Statistics.
Web search engines -- Forecasting -- Statistics.
Web sites -- Internet marketing -- Forecasting -- Statistics.