This article will give you an overview of location-specific sampling structures and sampling sizes from consumer research done for Mintel Reports in the Asia-Pacific region. It also has information on additional local specifics where applicable.
Find more information on our research methods in this article and learn about our analysis techniques in this article.
💡 Tip: As a Mintel Reports subscriber you can find all reports within your subscription by applying the Report content type filter on Insight Home. Every report card on Insight Home includes the location for which the report was released in the bottom left corner.
China reports
Overview
For its China Report series, Mintel has commissioned exclusive consumer research through KuRunData, a Chinese licensed market survey agent. Online consumer research is run in ten cities, completing 300 interviews per city with a total sample size of 3,000.
Our consumer research is based on a random sample of internet respondents from a panel recruited by KuRunData. In each wave, we survey four major tier one cities ie Shanghai, Beijing, Guangzhou and Chengdu. For tier two, tier three or lower cities, we rotate amongst a selection of cities based on size and economic development (see sampling methodology and sampling structure below).
The research is not representative of the population as a whole, and is not being analysed as such. Mintel applies a quota-sampling approach with quotas on age, gender and monthly household income in these cities. Our sample data can only be considered as indicative of urban consumers in those regions rather than representative of China as a whole.
For category reports (eg chocolate confectionery), consumers will typically be asked about usage, frequency, location of purchase, consumption occasion, brand usage and a series of attitudinal statements about the category.
Lifestyle reports cover a broader range of attitudinal and behavioural topics.
Statistical confidence levels
Statistical confidence levels of +/- 2% or 3% can be applied to the data, depending on sample size and percentage of respondents. For example, if 20% of a total sample of 1,000 adults say that they do something, you can be 95% certain that the figure for the population lies between 17% and 23%. For a sample of 3,000 adults, you can be 95% certain that the figure lies between 18% and 22%.
Consumer research is stored in a database supervised by Mintel's statisticians. Additional analysis of information too abundant to be included in published reports can be made available upon request.
When the overall population of a city is large enough (> 20,000), sample size is not determined by the size of population. It is only when the population becomes quite small (eg less than 10,000) that the sample size calculation is affected.
As a result a sample size of 300 per city across all 10 cities in our survey was set. Statistically, this enables us to apply a confidence level at 95% with a margin of error of 5.66%.
Meet the Mintropolitans
There has long been unresolved debate as to how to define the middle class in China, using various formulas about income levels, educational attainment and ownership of certain key items. However, the notion of middle class is very much an invention of 19th century North America and Western Europe, and does not comfortably translate that well into 21st century China.
So, rather than continue to struggle to make the round peg of China fit into the square hole of the middle class, Mintel has decided to use a clear and practical definition to define those who not only have higher spending power but can also represent future consumption trends as Mintropolitans. They had to meet all of the following requirements.
They need to have a higher level of income, depending on which city they live in:
a household income of RMB 18,000 per month or more in tier one cities
a household income of RMB 16,000 per month or more in tier two, three or lower cities
They need to have a higher level of education, ie undergraduate or above.
They need to own a property – either outright or on a mortgage.
Lastly, they also need to demonstrate certain spending attitudes and lifestyles, chosen by Mintel to indicate their spending power, as well as reflecting their pursuit of a quality life.
Broadly, they should represent a sophisticated group of consumers who pursue quality of life rather than just wealth, are well educated and are the potential trendsetters.
Based on demographic data from the consumer research conducted across multiple Mintel Reports, Mintropolitans account for about 15% of total surveyed households – representing a population of 27 million households who live in China.
Compared to other groups of consumers, besides having a higher income, Mintropolitans are much more likely to be aged 30-39, married with children, have a postgraduate degree and work for foreign companies (compared to Non-Mintropolitans).
Sampling methodology and sampling structure
According to government figures, there are 645 cities in China. These cities are very different in terms of size, economic development, culture, history and lifestyle. To meet your interests (by region, by tier), ten cities are selected in each wave of research based on their geographic coverage and level of economic development (GDP and per capita income).
Mintel defines the tier levels of cities in China as follows.
Tier one: Major economic hubs
Tier two: Provincial capital cities and some developed non-provincial capital cities
Tier three or lower: Other cities beside Tier one and Tier two cities
The table below shows an example of cities covered.
Region | Tier one cities | Tier two cities | Tier three or lower cities | Total |
North China | Beijing | Shenyang |
| 2 |
East China | Shanghai | Hangzhou | Jinhua | 3 |
Middle China |
| Wuhan |
| 1 |
West China | Chengdu |
| Hengyang | 2 |
South China | Guangzhou | Fuzhou |
| 2 |
Total | 4 | 4 | 2 | 10 |
📌 Note: Tier two, tier three, or lower cities in the table above are shown as examples only.
Within each city, our sampling structure is presented below.
Gender and age
In all cities, the sample consists of 50% men and 50% women for each of the following age groups:
18-29
30-39
40-49
50-59
Monthly household income in RMB
We defined three different levels for monthly household income according to different city tier:
Tier one cities
RMB 6,000 - 9,999
RMB 10,000 - 17,999
RMB 18,000 or above
Tier two, three or lower cities
RMB 5,000 - 8,999
RMB 9,000 - 15,999
RMB 16,000 or above
Chinese Consumer Monthly Tracker
The table below shows the cities we cover.
Region | Tier one cities | Tier two cities | Tier three or lower cities |
North China | Beijing | Haerbin | Xingtai |
East China | Shanghai | Hangzhou | Changzhou |
Mid-West China | Chengdu | Wuhan | Xinyang |
South China | Guangzhou | Fuzhou | Zhanjiang |
India reports
Mintel conducts face-to-face interviews with consumers representative of four broad regions of India, covering metros as well as cities in tiers 1 to 3, of ages ranging from 18 to 65 and socio-economic classes A to C. For more targeted reports, focusing on topics such as Alcohol or Baby Food, the methodology may vary.
Mintel's research partner in India is Ipsos Observer, which is part of Ipsos India.
📌 Note: From 2020 to 2022, the research was conducted using an online methodology due to the COVID-19 pandemic.
The CAPI (Computer assisted personal interview) is carried out using internet-enabled Android tablets. In order to achieve the required quotas for age, gender and socio-economic group, interviews are conducted door-to-door in seven local languages (Hindi, Gujarati, Marathi, Bengali, Oriya, Telugu and Tamil). Respondents are also given the option to take the survey in English if they wish to do so.
We apply the following four layers of quality checks:
accompanying the interviewer on 2% to 5% of the total sample
phone checks on 20% of the total sample
interview audio file assessment on 20% of the total sample
automated GPS location of the interviewing place in all cases
Mintel applies interlocking quotas on age by gender, region by socio-economic class and city tier by region. The sample is skewed towards the higher socioeconomic classes, A and B. Our face-to-face sample data can be considered as indicative of urban consumers rather than representative of India as a whole. While it does give a proxy of the nation’s attitudes it has been designed to provide comparable, robust results for a wide range of demographic segments.
Rather than mirror exactly India’s population distribution, sample sizes have been selected to provide comparable figures between regions, tiers and age groups. Specific quotas for a sample size of 3,000 people are listed below.
Region | City | Tier | N (3,000) |
North | Delhi | Metro | 300 |
| Lucknow | Tier 1 | 150 |
| Jalandhar | Tier 2 | 150 |
| Ambala | Tier 3 | 150 |
East | Kolkata | Metro | 300 |
| Patna | Tier 1 | 150 |
| Bhubaneswar | Tier 2 | 150 |
| Aurangabad (Bihar) | Tier 3 | 150 |
South | Chennai | Metro | 300 |
| Coimbatore | Tier 1 | 150 |
| Tiruppur | Tier 2 | 150 |
| Amravati | Tier 3 | 150 |
West | Mumbai | Metro | 300 |
| Ahmedabad | Tier 1 | 150 |
| Anand | Tier 2 | 150 |
| Lonavala | Tier 3 | 150 |
In all regions, the sample consists of 75 men and 75 women for each of the following age groups:
18-24
25-34
35-44
45-54
55-65+
Socio-economic classification in %
Region | N (3,000) | A | B | C |
North | 750 | 45 | 29 | 26 |
South | 750 | 40 | 28 | 32 |
East | 750 | 27 | 33 | 40 |
West | 750 | 34 | 34 | 32 |
Japan reports
For our Japan Report series, we use an online research approach to interview consumers covering all ages from 18. Respondents are interviewed from all prefectures which are then grouped into six broad regional groups for reporting. Our Japanese consumer survey is conducted in cooperation with Rakuten Insight.
We apply a quota-sampling approach with quotas on age, gender and broad region. Specific region quotas and used to represent a sample of 2,000 respondents are shown below. For more targeted reports, focusing on topics such as mothers, the methodology will vary.
📌 Note: Our sample data cannot be considered to be nationally representative of Japan. Instead, we cover key demographics to give a proxy of the nation’s attitudes and behaviours. It has been designed to provide comparable, statistically robust results of the most relevant demographic and geographic segments for analysis.
Age groups by gender | Population % | N (2,000) |
Men, 18-24 | 5 | 100 |
Men, 25-29 | 5 | 100 |
Men, 30-39 | 10 | 200 |
Men, 40-49 | 10 | 200 |
Men, 50-59 | 10 | 200 |
Men, 60-64 | 5 | 100 |
Men, 65+ | 5 | 100 |
Women, 18-24 | 5 | 100 |
Women, 25-29 | 5 | 100 |
Women, 30-39 | 10 | 200 |
Women, 40-49 | 10 | 200 |
Women, 50-59 | 10 | 200 |
Women, 60-64 | 5 | 100 |
Women, 65+ | 5 | 100 |
Region | % | N (2,000) |
Hokkaido and Tohoku | 11.0 | 220 |
Kanto | 34.4 | 688 |
Chubu and Hokuriku | 18.2 | 364 |
Kinki | 16.3 | 326 |
Chugoku and Shikoku | 8.8 | 176 |
Kyushu and Okinawa | 11.3 | 226 |
Thailand reports
Mintel partners with Dynata and uses an online research approach to interview consumers covering age groups from 18-45+. Respondents are interviewed in regions and/or metro cities to represent the population distribution across each market for reporting.
We apply a quota-sampling approach with quotas on age, gender and broad region or metro city. The quotas on age and gender are selected in a consistent way per location to allow ease of comparison and analysis across a variety of key target groups. For more targeted reports, focusing on topics such as baby products, the methodology will vary.
Age groups by gender | % | N (1,500) | N (2,000) |
Women, 18-24 | 12.5 | 188 | 250 |
Women, 25-34 | 12.5 | 188 | 250 |
Women, 35-44 | 12.5 | 187 | 250 |
Women, 45+ | 12.5 | 187 | 250 |
Men, 18-24 | 12.5 | 188 | 250 |
Men, 25-34 | 12.5 | 188 | 250 |
Men, 35-44 | 12.5 | 187 | 250 |
Men, 45+ | 12.5 | 187 | 250 |
📌 Note: Our sample data is not nationally representative. Our online, quota-sampling approach provides comparable, statistically robust data and allows analysis of key demographic and geographic groups by market.
The table below shows the split by location.
Region/City | % | N (1,500) | N (2,000) |
Greater Bangkok | 10.4 | 156 | 208 |
Central Thailand (excl Greater Bangkok) | 23.3 | 350 | 466 |
North Thailand | 18.8 | 282 | 376 |
Northeast Thailand | 34.2 | 512 | 684 |
South Thailand | 13.3 | 200 | 266 |