COVID-19 Research
Mintel Consumer Research Methodology - COVID-19 Research
Mintel uses an online research approach to interview consumers covering age groups varying in range from 18+ or 16+ (will vary by market). Respondents are interviewed in regions and/or metro cities to represent the population distribution across each market for reporting.
Mintel applies a quota-sampling approach with quotas on age, gender and broad region or metro city. Our sample data is not nationally representative within each market. Instead it can be considered to be representative of the online population in some markets and an urban online population in others, providing a proxy of each market’s behaviours and attitudes. Our online, quota sampling approach provides comparable, statistically robust data and allows analysis of key demographic and geographic groups by market.
Our research partners
Kantar Profiles
Kantar Profiles is our research partner for our US, Brazil, Canada and European markets (excluding Northern Ireland and the Republic of Ireland). Kantar Profiles’ double opt-in online consumer panels deliver uniquely identified online respondents via extensive use of fraud detection and location-verification technology at multiple points in the research cycle, from initial registration through survey fielding and incentive redemption. Kantar Profiles' panellists are profiled on a wide variety of attributes to deliver the specific hard-to-reach demographics.
Dynata
Mintel partners with Dynata (formerly Research Now SSI) to complete it’s online research in India, Australia, the Republic of Korea, Thailand, Republic of Ireland and Northern Ireland. As a leading provider of first party data, Dynata serves nearly 6,000 market research agencies, media and advertising agencies, consulting and investment firms, and healthcare and corporate customers in North America, South America, Europe, and Asia-Pacific.
KuRunData
For our China (mainland) research, Mintel partners with KuRunData which which has been part of the ITWP Group since 2017. Founded in 2006 and headquartered in Shanghai, with branches in both Beijing and Guangzhou, KuRunData’s online panel consists of 5,300,000 respondents (as of Dec 2018). It owns the interactive panel website: www.1diaocha.com and www.votebar.com, in addition to a WeChat survey app. KuRunData is a member of both the China Market Research Association (CMRA) and ESOMAR.
Sample sizes by demographics and geographies
Mintel applies a quota-sampling approach with broad quotas on age, gender and region in all markets at minimum. Below outlines the broad quotas employed per market. In some instances, a sample larger than N=500 will be used but the quota proportions with remain the same.
Quotas: Asia Pacific
Thailand, Australia, Republic of Korea
|
Age by gender |
|
|
|
% |
|
Females 18-24 |
12.5 |
|
Females 25-34 |
12.5 |
|
Females 35-44 |
12.5 |
|
Females 45+ |
12.5 |
|
Males 18-24 |
|
| Region/City | % |
| Australia | |
| New South Wales | 32 |
| Victoria | 26 |
| Queensland | 20 |
| South Australia | 7 |
| West Australia | 10 |
| : | : |
| : | : |
Japan
|
% |
||
|
Male |
18-24 |
5% |
|
|
25-29 |
5% |
|
|
30-39 |
10% |
|
|
40-49 |
10% |
|
|
50-59 |
10% |
|
|
60-64 |
5% |
|
|
65+ |
5% |
| : | : | : |
| : | : | : |
| Region | % | District Included |
| 1 | 11 | Hokkaido, Hokkaido, Tohoku, Tohoku |
| 2 | 34.4 | Kanto, Kanto, |
| 3 | 18.2 | Chubu, Hokuriku and Tokai, |
| 4 | 16.3 | Kinki (Kansai), Kinki, |
| 5 | 8.8 | Chugoku, Chugoku, Shikoku, Shikoku |
| 6 | 11.3 | Kyushu, Kyushu, Ryukyu, Okinawa |
| Total | 100 |
India
| Region | Males | Females |
| % | % | |
| North | ||
| 18-24 | 3.7 | 3.7 |
| 25-34 | 4.3 | 4.3 |
| 35-44 | 2.8 | 2.8 |
| 45+ | 1.7 | 1.7 |
| Total | 12.5 | 12.5 |
| : | : | : |
| : | : | : |
|
Regional City |
City tier |
Total (N) |
|
West |
|
|
|
Mumbai |
Metro |
10 |
|
Ahmedabad |
Tier 1 |
5 |
|
Anand/ Bhiwandi/ Kolapur |
Tier 2 |
5 |
|
Amravati/ Malegoan/ Nashik |
Tier 3 |
5 |
|
West total |
|
25 |
|
|
|
|
| : | : | : |
| : | : | : |
Quotas: Europe
Great Britain
|
|
GREAT BRITAIN |
|
|
% |
|
|
|
|
|
|
|
16-24 males |
7.5 |
|
16-24 females |
7.2 |
|
25-34 males |
9.2 |
|
25-34 females |
9.1 |
| : | : |
| : | : |
|
Region |
|
|
GREAT BRITAIN |
% |
|
Scotland |
8.5 |
|
North East |
4.1 |
|
North West |
11.3 |
|
Yorkshire & Humberside |
8.5 |
|
East Midlands |
7.4 |
|
West Midlands |
9.1 |
| : | : |
| : | : |
|
SEG |
% |
|
AB |
28 |
|
C1 |
28 |
|
C2 |
20 |
|
DE |
24 |
|
Total |
100 |
Ireland
|
IRELAND (ROI & NI) |
|
|
|
|
|
NORTHERN IRELAND |
REPUBLIC OF IRELAND |
|
|
|
% |
% |
|
|
|
|
|
|
|
16-24 males |
8 |
9 |
|
|
16-24 females |
7 |
8 |
|
|
25-34 males |
9 |
10 |
|
| : | : | : | : |
| : | : | : | : |
France, Germany, Italy, Spain, Poland
|
|
FRANCE |
GERMANY |
ITALY |
SPAIN |
POLAND |
|
|
% |
% |
% |
% |
% |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
16-24 males |
7.5 |
6.5 |
7.1 |
6.5 |
7.9 |
|
16-24 females |
7.3 |
5.9 |
6.6 |
6.1 |
7.6 |
|
25-34 males |
8.1 |
8.6 |
8.5 |
8.2 |
12.2 |
|
25-34 females |
8.5 |
8 |
8.2 |
8.2 |
11.7 |
| : | : | : | : | : | : |
| : | : | : | : | : | : |
|
Region |
|
|
FRANCE |
% |
|
Île de France |
18.8 |
|
Centre-Val de Loire/Bourgogne-Franche-Comté |
8.3 |
|
Normandie/Hauts-de-France |
14.4 |
|
Grand Est |
8.5 |
|
Pays de la Loire/Bretagne |
11 |
|
Nouvelle-Aquitaine/Occitanie |
18.3 |
| : | : |
| : | : |
Quotas: Americas
US
|
Age by gender |
IPop % |
|
Male, 18-24 |
5.97% |
|
Male, 25-34 |
9.19% |
|
Male, 35-44 |
8.60% |
|
Male, 45-54 |
8.18% |
|
Male, 55-64 |
7.93% |
|
Male, 65-74 |
5.51% |
|
Male, 75+ |
2.83% |
| : | : |
| : | : |
|
Region |
IPop % |
|
Northeast |
17.62% |
|
Midwest |
20.63% |
|
South |
37.92% |
|
West |
23.84% |
|
Race |
IPop % |
|
White |
70.13 |
|
Black |
15.00 |
|
Asian |
6.28% |
|
Other race |
8.59% |
|
Ethnicity |
IPop % |
|
Hispanic |
16.30 |
|
Non-Hispanic |
83.70 |
|
Income |
IPop % |
|
Less than $25,000 |
11.01% |
|
$25,000 - $49,999 |
16.63% |
|
$50,000 - $74,999 |
17.12% |
|
$75,000 - $99,999 |
14.14% |
|
$100,000 plus |
41.09% |
|
Device |
IPop % |
|
Smartphone |
50% |
|
Non-Smartphone |
- |
Canada
|
Age by gender |
Ipop % |
|
|
Male, 18-24 |
6.6% |
|
|
Male, 25-34 |
9.0% |
|
|
Male, 35-44 |
10.1% |
|
|
Male, 45-54 |
7.0% |
|
|
Male, 55-64 |
6.4% |
|
|
Male, 65+ |
10% |
|
|
Female, 18-24 |
6.2% |
|
| : | : | |
| : | : | |
|
Province |
Canada pop % |
|
|
Ontario |
37.7% |
|
|
Quebec |
24.6% |
|
|
British Columbia |
11.9% |
|
|
Alberta |
11.6% |
|
|
Saskatchewan |
3.0% |
|
|
Manitoba |
3.9% |
|
|
Atlantic Provinces (New Brunswick, Newfoundland/ Labrador, Nova Scotia, Prince Edward Island) |
7.2% |
|
|
Household Income |
Canada pop % |
|
|
Less than $25,000 |
14.0% |
|
|
$25,000 - $49,000 |
20.8% |
|
|
$50,000 - $69,999 |
15.0% |
|
|
$70,000 - $99,999 |
17.8% |
|
|
$100,000 and over |
32.4% |
|
|
Device |
IPop % |
|
Smartphone |
40% |
|
Non-Smartphone |
- |
Brazil
|
Age by gender |
iPop% |
|
Male, 16-24 |
9.93% |
|
Male, 25-34 |
12.60% |
|
Male, 35-44 |
12.40% |
|
Male, 45-54 |
7.00% |
|
Male, 55+ |
7.13% |
|
Female, 16-24 |
12.20% |
|
Female, 25-34 |
11.47% |
| : | : |
| : | : |
|
Region |
iPop% |
|
North |
8.52% |
|
Northeast |
22.24% |
|
Central West |
7.58% |
|
Southeast |
47.72% |
|
South |
13.94% |
|
SEG |
iPop% |
|
A |
2.9% |
|
B1 |
5.0% |
|
B2 |
17.3% |
|
C1 |
22.2% |
|
C2 |
25.6% |
|
DE |
27.0% |
