This report analyses the Japanese market.
Chapter 4: Location Strategy Successes and Failures continued
It has been exactly 15 years this year since we created our trade area analysis software for noodle specialty stores and I began analyzing our clients’ trade areas in April 2014.
During that time, we have probably done over 7,000 trade area analyses.
I have been proud of the groundbreaking method since I created it, but I have lost count of the number of customers that have been saved by this trade area analysis, and I am also sure that there are countless customers who have already closed their stores because they ignored the data from the trade area analysis and opened in impossible locations.
I believe that if we make more effective use of trade area analysis, we can contribute more to the success of our customers.
We are probably the only company in this industry that has such trade area analysis software and analyzes such a large number of cases, and thanks to this, we have accumulated a lot of know-how on trade area analysis over the past 15 years.
Although it is our staff that performs the analysis using the actual software and data, I have looked through all 6,000 of them and in some cases commented on them.
In case there is a mistake in the analysis by our staff, it would be a big problem, so I have looked through all the analyzed properties, and today (April 7, 2019) I am still in Frankfurt, but even when I am in a foreign country, I am always looking through the analysis data sent to me by e-mail, 100%, without dropping anything.
What I feel throughout the last 15 years is that the number of properties that students are requesting is getting smaller and smaller each year, with smaller and smaller seating areas and a very large increase in the number of smaller properties.
And I feel that there are more difficult properties with insufficient parking than before.
What a trade area analysis can tell us
A trade area analysis can reveal a great variety of things, but the largest factor is demographics. The trade area analysis software contains data from the most recent national census, including the number of daytime population, nighttime population, and age structure within the trade area, which can be used to determine how many parking spaces are needed.
The trade area is divided into three trade areas: walking trade area within a 500m radius, bicycle trade area within a 1km radius, and automobile trade area within a 5km radius, and the daytime and nighttime populations of each are analyzed.
Then, if the daytime population in a 500-meter radius walking trade zone is 20,000 or more, it is possible to operate without parking.
Through the trade area analysis, we can find out the following
Number of parking spaces required
Even in urban-type locations, there are many places where you would originally think that parking is unnecessary, but in reality, railroad tracks, highways, and rivers divide the trade area and require parking. From the results of the analysis, a figure for how many parking spaces are needed in relation to the number of seats is shown.
Daytime population density, nighttime population density
The color-coded map shows populated and unpopulated areas, categorized into daytime and nighttime populations, making it easy to determine whether the area is residential, commercial, or mixed-use.
Competitive conditions in restaurants
Dividing that trade area population by the number of restaurants gives an idea of the state of competition for restaurants in that area.
The average for Japan as a whole is 164 persons/restaurant. South Korea has the most competitive restaurant market in the world, with this number at 84 persons/restaurant, followed by Spain with 133 persons/restaurant, the second most competitive in the world, and Japan is third in the world. Therefore, more than 164 persons/restaurant is less competitive than the Japanese national average, and the smaller this number is, the more competitive the place is for restaurants.
Age composition of its trade area
Along with the population of a trade area, an important factor when opening a store is the age composition of that trade area. For example, a location with the largest number of people in their 20s will have a university nearby. Since Japan has an aging population, most places have a large number of elderly people.
Total population and population classification by walking trade area, bicycle trade area, and automobile trade area
Our trade area analysis identifies the daytime population, nighttime population, and the number of men and women in each within a 500 meter radius for walking trade areas, a 1 km radius for bicycle trade areas, and a 5 km radius for automobile trade areas. If only the walking trade area is targeted, parking is not required, in which case the daytime population within the walking trade area must be at least 20,000.
Matrix map shows the location of rival restaurants
The matrix map is a map colored to make it easier to see the difference between the total population and the total daytime population. The darker red areas are places with more daytime population and less nighttime population, while the darker blue areas are places with more nighttime population and less daytime population, and yellow are places with the same amount of population during the day and night, The darker any color is, the more populated it is. The blue dots on the matrix indicate the location of rival restaurants.
Net trade area population when trade area is cut off by railroad tracks, highways, and rivers
In many cases, in urban-type locations, the trade area is blocked by railroad tracks, highways, and rivers, and even if the daytime population appears to be 20,000 or more and no parking is needed, parking is in fact required. In such cases, the net trade area blocked off is illustrated on a map, its population is determined, and the number of parking spaces needed is drawn out.
The statistical data in the appendix provides more detailed trade area information.
Since a few years ago, we have been providing more detailed trade area data with the statistical data in the appendix below. These data are divided into three categories: within a 5km radius of the target area, the prefecture in which the trade area is located, and Japan as a whole, and provide the following data.
1.Total population, male, female, married, daytime youth (14 and under), productive (15 and over, 64 and under, and aged (65 and over), respectively
2.Total number of households, one, two, three, four, and five or more persons
3.Housing status, total number of owner-occupied, renter-occupied, and apartment buildings
4.Number of establishments, all industries, retail, food, and restaurants
5.Overall balance, establishments within a 5 km radius, daytime population, married couples, owner-occupied households, elderly, single persons living alone in the prefecture, compared to Japan as a whole (see case study)
| Chart Item | T.A | Fukuoka Prefecture | National |
|---|---|---|---|
| Number of offices | 1.12 | 0.94 | 1 |
| daytime population | 1.07 | 0.99 | 1 |
| married population | 0.92 | 0.95 | 1 |
| owner-occupied household | 0.76 | 0.86 | 1 |
| Elderly Population | 0.87 | 0.97 | 1 |
| one-person household | 1.1 | 1.08 | 1 |
1.Population pyramid
2.Composition of establishments in target area (ratio of households to establishments)
3.Daytime population ratio
4.Household composition by number of persons
5.Composition by 3 age groups
6.How to find a good location
Location and business model are closely related.
For example, a well-known nationwide chain of ramen restaurants has a 40-seat business model that is based on a populous urban location.
Another famous ramen restaurant with a nationwide chain of more than 200 stores has a suburban-type business model based on a 40-seat restaurant.
Thus, there is a close relationship between business model and location, just as the former will never succeed in seeking a suburban location and the latter will never succeed in seeking an urban location.
Therefore, a trade area analysis of a successful business model will reveal the unique trade area characteristics of that business model.
Therefore, since location selection is completely different depending on the type of business model, analyzing the trade area of a store in a different industry with business characteristics similar to those of the business you are about to start will reveal the characteristics of the trade area of the store you want to start.
In short, focus on stores in other industries that attract customers with similar lifestyles.
And the way to use trade area analysis strategically is to analyze the trade areas of rival stores you are interested in.
This way, you can see what kind of trade area base they are competing in and see through their rivals’ strategies.
Also, by shifting the points of the trade area analysis for the location where you want to open your store, you can see where the vacuum spots are in that entire trade area.
You will be able to see what you could not by analyzing only one location, and sometimes you will find that there are trade areas where there are no rivals and you can win alone.
In addition, in conjunction with the trade area analysis, you can also survey the area on foot or by driving around in a car and find places that are easy to reach by car and that your competitors may not yet be aware of.
By comparing the trade area analysis data with the actual trade area, you will be able to read deeper into the trade area analysis data, and you will gradually learn more and more about that trade area and where the sweet spots are.
All of the above takes time and energy, and securing a location is a life-or-death decision.