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Global Financial Crisis? America Beats Japan in Gluten Free Demand – The GFP Matrix Shows Why


This article compares previous research on gluten free e-demand in the Americas and Europe with analysis of major Asian countries using a re-developed GFP Matrix model. This model uses gluten free search term volumes in Google in specific communities to estimate the community’s gluten free market maturity. The matrix plots the raw gluten related search volumes versus ‘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 in different countries are searching for and why. One of the main concepts in this article is ‘Adjusted Celiac searches’ which is based on raw gluten search term volumes. These values are then adjusted (increased) to account for internet usage in a country as well as the probable total search engine gluten queries (using specific country Google Market share as the basis). This adjusted value thus estimates the 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 gain a monthly ‘adjusted celiac search’ value. That is, assuming that that the average celiac rate is approximately 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 for them each month. Note that as diagnosis in advanced countries may be as low as 20%, the actual number of times internet using celiacs currently search may be five times as much as the estimates predict!

To assist 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 fifty terms represent 95% of all terms.

Gluten Group Composition:

  • Generic GF Product: This group of search terms all involve the word gluten and are generic in nature, such a gluten, gluten free, gluten free products, gluten free meals. This group is also segmented into core and non-core terms. Core terms are those shown above, while non core terms are those such as: 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 such as recipes, baking, wheat free baking
  • Celiac related: These are terms related to information on the disease such as: celiac, 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 ‘adjusted celiac searches per month’ ratings of specific communities for Dec 2008 were:

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


Overall, the control groups, USA and Australia, remained higher search countries than the highest ‘raw searches per population’ countries of the Asian countries analysed, except for the Singapore English speaking community. Singapore has one of the best telecommunication systems in Asia and its internet penetration is similar to the US and Australia. It is believed that of those people who do search on the internet in Singapore, they search long and hard for what they want. With this high search level, the searches conformed to GFP Matrix conditions that 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 core searches. As per the GFP Matrix trend, the ‘celiac’ group was also high. Its eleven terms and 8% of top 50 searches was only 2% behind the second highest group ‘diet’.

In statistical terms, China traditional language, and Indonesia English speaking communities 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 wage and lower standards of living). This might typically suggest that these communities would have a low celiac diagnosis rate – however it is likely that any English speaking community in any under developed country, is likely to have more affluence and access to better medical facilities than the main population. If we assume that the resulting high celiac searches are correct, then clues to why this is so can be found in detailed analysis of the communities.

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

The ‘Indonesia English speaking’ community had a relatively low search volume of 325 thousand terms, however with only an 11% internet penetration this gives the community a celiac search rating of 5.5 searches by celiacs per month. The search group profile is non typical of high search countries. A relatively low generic group and the highest group ‘celiac’ used non-standard search terms. ‘Wheat free’ was also non-typically very high (16%). With ‘gluten free pizza’ being the highest specific food search, it appears that this community is more affluent than the indigenous community and has higher searchers. But they also use non-standard search terms as the Indonesian gluten online supply side is likely to be quite undeveloped.

All of the other Asian communities analysed were found in the very low search are of 1 to 2 adjusted celiac searches. Surprisingly Japan, (English and Japanese speaking) communities, were also found here. While they have slightly one of the larger raw gluten search volume values compared to all other Asian communities, their adjusted celiac search values are still only around 60% of the US and less than half of Australia’s. This could be caused by their predilection towards rice dishes and fish foods that don’t involve gluten. Japan English speaking had a low 100 terms and 187 thousand searches with the top four groups having similar search volumes around 18%. The very high searches for ‘gluten free restaurants’, and high ranking for the ‘celiac group’ suggests that there is an even spread between new diagnosed and sophisticated searchers.

Specific food terms of cakes, corn and muffins rather than food staples also suggest that Japan’s Japanese speaking people have risen above the need to find or make food staples such as bread. While the Japanese speaking community had double the searches of the English speaking community, they were located in virtually the same spot on the GFP matrix. The main difference was that its search profile was completely different. The Japanese speaking searchers spent 43% of their 391 thousand 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 searchers in an affluent society.

The lowest ranking communities were India (English and Hindu), Indonesia (Indonesian speaking), and China (English and Simplified Chinese language). These countries all share the similarity of being very large, having a low economic status and being predominantly non English speaking with low internet penetration.

Specific information is provided on these communities in the individual community analysis. However it might just be that like Japan, these countries have a low amount of gluten in their diet and this may also be a reason for low or non-triggering of celiac disease issues. That is aligned to the theory that it is an continued ‘overdose’ of high gluten foods that triggers celiac disease in the first place in many developed nations peoples.

Source by Bruce Dwyer

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