This article compares previous research on gluten-free e-demand in the Americas and Europe with analysis of major Asian countries using a redesigned GFP matrix model. This model uses volumes of Google gluten-free search terms in specific communities to estimate the maturity of the community’s gluten-free market. The matrix plots search volumes related to raw gluten against ‘Adjusted Celiac Searches’ and finds a linear relationship between the two variables. The analysis looks at what defines a mature gluten-free market, as well as what products people are looking for in different countries and why. One of the main concepts of this article is “Adjusted Celiac Searches,” which is based on volumes of raw gluten search terms. These values ​​are then adjusted (increased) to account for internet usage in a country, as well as the likely total gluten-free search engine queries (using a specific country’s Google market share as a base). This adjusted value thus estimates total gluten searches as if 100% of a country had Internet access and all search engine results were used.

This intermediate value is then divided by (community population divided by 100) to obtain a monthly ‘adjusted celiac search’ value. That is, assuming the average celiac rate is about 1 in 100 people (diagnosed and undiagnosed), this hypothetical value estimates on average, if all celiacs searched for gf products, how many times they searched each month. Keep in mind that since diagnosis in advanced countries can be as low as 20%, the actual number of times Internet-using celiacs currently search may be five times what estimates predict.

For ease of analysis, gluten-related search terms were divided into seven groups, as shown below. Only the top 50 terms were used for detailed statistical analysis, but in most cases these 50 terms represent 95% of all terms.

Ingredients from the gluten group:

• Generic GF Product: This group of search terms involves the word gluten and is generic in nature, such as gluten, gluten-free, gluten-free products, gluten-free foods. This group is also segmented into basic and non-basic terms. Head terms are those shown above, while non-head terms are those like: gf breakfast, gf snacks, gf desserts, gf gifts.
• Diet: These are terms that are related to the specifics of gluten-free diets such as: gluten-free diets, celiac diet.
• Recipe: terms like recipes, baking, wheat-free baking
• Related to celiac disease: These are terms related to information about the disease such as: celiac disease, celiac disease, gluten intolerance, allergies
• Wheat free: terms such as: wheat free, wheat gluten, wheat allergy
• Locations: gluten-free stores, shopping, restaurant
• Specific foods: bread, pizza, cakes, muffins

A summary of the ‘monthly adjusted celiac searches’ scores for specific communities for December 2008 was:

4.2 Australia 2.7 USA 1.9 China English-speaking 4.9 Traditional China 2.0 Simplified China 1.6 India English 1.0 India Hindi 5.5 Indonesia English 1.0 Indonesian-speaking Indonesian 1.3 Japan English 1.4 Japan Japanese-speaking 6.7 Singapore English-speaking

GFP Matrix ASIA SUMMARY

Overall, the control groups, the US and Australia, remained higher search countries than the highest ‘raw searches by population’ countries of the Asian countries analysed, with the exception of Singapore’s English-speaking community. Singapore has one of the best telecommunication systems in Asia and its Internet penetration is similar to that of the US and Australia. It is believed that of those people who search the Internet in Singapore, they search for a long time what they want. With this high search level, the searches conformed to the GFP Matrix conditions which suggest that high raw search communities have a high proportion of generic searches. In this case, 65% of all searches were in the generic group, of which 85% were main searches. According to the GFP Matrix trend, the ‘celiac’ group was also high. Its eleven terms and 8% of the top 50 searches were only 2% behind the second highest group, “diet”.

In statistical terms, the traditional language of China and the English-speaking communities of Indonesia are called “outliers”.. That is, most other data points fit a linear relationship between raw searches and adjusted celiac searches, except for these two communities. The common trait of these two communities is that they have very large populations and very low Internet penetration and low Gross Domestic Product per person (associated with low wages and lower living standards). This would typically suggest that these communities would have a low celiac diagnosis rate; however, any English-speaking community in any underdeveloped country is likely to have more wealth and access to better medical facilities than the mainstream population. If we assume that the resulting high celiac searches are correct, then clues as to why this is so can be found in a detailed analysis of the communities.

Chinese (Traditional Chinese Speak) it had 2.6 million massive searches. This is similar to the US, but China has much lower internet penetration, resulting in a higher celiac search estimate. The typical high celiac search community has a high search ratio for generic top 50 gluten, while ‘Traditional Chinese’ has only 38% of the volumes. However, it does follow the trend of having the ‘celiac group’ as the second highest search group (30%). So it would seem that ‘Traditional Chinese’ really does have a high celiac search community. The boom in the Chinese economy, particularly in large cities, has likely spawned a community hungry for information and funds to seek out medical facilities and purchase gluten-free products.

The ‘English-speaking Indonesia’ The community had a relatively low search volume of 325k terms, however with only 11% internet penetration this gives the community a celiac search rating of 5.5 celiac searches per month. The profile of the search group is not typical of high search countries. A relatively low generic group and the highest “celiac” group used non-standard search terms. ‘Wheat free’ was also unusually very high (16%). Since ‘gluten-free pizza’ is the highest specific food search, it seems that this community is more prosperous than the indigenous community and has more search engines. But they also use non-standard search terms, as the online supply side of Indonesian gluten is likely to be quite underdeveloped.

All other Asian communities analyzed were found in the very low search of 1 to 2 adjusted celiac searches. Surprisingly, communities from Japan (English and Japanese speaking) were also found here. While they have slightly one of the largest raw gluten search volume values ​​compared to all other Asian communities, their adjusted celiac search values ​​are still only about 60% of those of the US and less than half of those of Australia. This could be due to his predilection for rice dishes and fish that do not contain gluten. English-speaking Japan had a low 100 terms and 187,000 searches with the top four groups having similar search volumes around 18%. The very high searches for ‘gluten-free restaurants’ and the high ranking for ‘celiac group’ suggest that there is an even distribution between newly diagnosed and sophisticated searchers.

The specific food terms of cakes, corn, and muffins instead of staples also suggest that Japanese-speaking Japanese have outgrown the need to find or make staples like bread. While the Japanese-speaking community had twice as many searches as the English-speaking community, they ranked in roughly the same place in the GFP matrix. The main difference was that their search profile was completely different. Japanese-speaking searchers spent 43% of their 391,000 searches looking for specific gluten-free foods. The top specific searches were: cake, pizza, casein, cookies, chocolate, and beer. Again, these are the hallmarks of sophisticated seekers in a prosperous society.

The lowest ranked communities were India (English and Hindi), Indonesia (Indonesian speaking) and China (English and Simplified Chinese language). All of these countries share the similarity of being very large, having low economic status, and being relatively non-English speaking with low internet penetration.

Specific information about these communities is provided in the individual community analysis. However, it could be that, like Japan, these countries have a low amount of gluten in their diet and this may also be a reason why celiac disease problems are low or not. That’s in line with the theory that it’s a continual “overdose” of high-gluten foods that triggers celiac disease in many towns in developed countries in the first place.