Global Consumer
Mintel Consumer Research Methodology
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' panelists are profiled on a wide variety of attributes to deliver the specific hard-to-reach demographics.
Rakuten Insight
Mintel partners with Rakuten Insight to complete online research in Japan, Hong Kong SAR of the PR of China, Malaysia, Philippines, Singapore and Vietnam. Established in 1997, it’s since grown into a pioneer of Asian online sample providers, recruiting respondents from their member database and networks, serving both domestic Asian and international clients.
Dynata
Mintel partners with Dynata (formerly Research Now SSI) to complete online research in Ireland (Republic of Ireland and Northern Ireland), India, Australia, Indonesia, the Republic of Korea, Thailand and New Zealand. 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.
Offerwise
Mintel partners with Offerwise to complete online research in Chile, Colombia, Mexico, and Peru. As Internet penetration continues to boom throughout Latin America, Offerwise has positioned itself as an early leader of online panel providers and has one of the region’s largest online access panels in the industry. Currently, they offer one of the largest panels in Mexico, and Colombia along with fast growing panels in Chile, Peru, and Argentina.
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. Where the proportions are in line with internet representative or regionally representative statistics, these are revised on an annual basis.
Quotas: Asia Pacific
Australia, Thailand, Indonesia, Republic of Korea, Hong Kong, Malaysia, New Zealand, Philippines, Singapore, Vietnam
The quotas on age and gender are selected in a consistent way per market to allow ease of comparison and analysis across a variety of key target groups.
Age by gender |
||
|
% |
N |
Females 18-24 |
12.5 |
125 |
Females 25-34 |
12.5 |
125 |
Females 35-44 |
12.5 |
125 |
Females 45+ |
12.5 |
125 |
Males 18-24 |
12.5 |
125 |
Males 25-34 |
12.5 |
125 |
: | : | : |
: | : | : |
Region |
Region/City |
% |
N |
Australia |
New South Wales |
32 |
320 |
Victoria |
26 |
260 |
|
Queensland |
20 |
200 |
|
South Australia |
7 |
70 |
|
West Australia |
10 |
100 |
|
Others |
5 |
50 |
|
: | : | : | : |
: | : | : | : |
China (mainland)
Gender & Age per city |
|||||||
City |
Males aged 18-29 |
Males aged 30-39 |
Males aged 40-49+ |
Females aged 18-29 |
Females aged 30-39 |
Females aged 40-49+ |
Total |
Beijing |
17 |
17 |
16 |
17 |
17 |
16 |
100 |
Shanghai |
17 |
17 |
16 |
17 |
17 |
16 |
100 |
Guangzhou |
17 |
17 |
16 |
17 |
17 |
16 |
100 |
Chengdu |
17 |
17 |
16 |
17 |
17 |
16 |
100 |
Yantai |
17 |
17 |
16 |
17 |
17 |
16 |
100 |
Changchun |
17 |
17 |
16 |
17 |
17 |
16 |
100 |
: | : | : | : | : | : | : | : |
: | : | : | : | : | : | : | : |
Monthly household income (RMB) by city |
||||
Tier 1 city |
6,000-9,999 |
10,000-17,999 |
18K+ |
Total |
Beijing |
33 |
34 |
33 |
100 |
Shanghai |
33 |
34 |
33 |
100 |
Guangzhou |
33 |
34 |
33 |
100 |
Chengdu |
33 |
34 |
33 |
100 |
Tier 2, 3 or lower city |
5,000-8,999 |
9,000-15,999 |
16K+ |
Total |
Yantai |
33 |
34 |
33 |
100 |
: | : | : | : | : |
: | : | : | : | : |
Japan
Gender by Age
|
% |
N |
|
Male |
18-24 |
5% |
50 |
|
25-29 |
5% |
50 |
|
30-39 |
10% |
100 |
|
40-49 |
10% |
100 |
|
50-59 |
10% |
100 |
|
60-64 |
5% |
50 |
|
65+ |
5% |
50 |
: | : | : | : |
: | : | : | : |
Region
Region |
% |
N |
District Included |
1 |
11.0 |
110 |
Hokkaido, Tohoku |
2 |
34.4 |
344 |
Kanto |
3 |
18.2 |
182 |
Hokuriku, Chubu |
4 |
16.3 |
163 |
Kinki |
5 |
8.8 |
88 |
Chugoku, Shikoku |
6 |
11.3 |
113 |
Kyushu, Okinawa |
Total |
100 |
1000 |
|
India
Gender by age per region |
||||||
Region |
Males |
|
Females |
|
Total |
|
|
|
N |
% |
N |
% |
N |
North |
18-24 |
37 |
3.7 |
37 |
3.7 |
74 |
25-34 |
43 |
4.3 |
43 |
4.3 |
86 |
|
35-44 |
28 |
2.8 |
28 |
2.8 |
56 |
|
45+ |
17 |
1.7 |
17 |
1.7 |
34 |
|
Total |
125 |
12.5 |
125 |
12.5 |
250 |
|
: | : | : | : | : | : | : |
: | : | : | : | : | : | : |
Region & city tier |
|||
North |
|
% |
N |
Delhi |
Metro |
10 |
100 |
Lucknow |
Tier 1 |
5 |
50 |
Jalandhar |
Tier 2 |
5 |
50 |
Nainita/Ambala |
Tier 3 |
5 |
50
|
North total |
|
25 |
250 |
|
|
|
|
: | : | : | : |
: | : | : | : |
Quotas: Europe, Middle East and Africa
Great Britain
Age and gender:
% |
N (1000) |
|
16-24 males |
7.1 |
71 |
16-24 females |
6.7 |
67 |
25-34 males |
8.9 |
89 |
25-34 females |
8.8 |
88 |
35-44 males |
8.2 |
82 |
35-44 females |
8.4 |
84 |
: | : | : |
: | : | : |
Region |
|
|
GREAT BRITAIN |
% |
N (1,000) |
Scotland |
8.6 |
86 |
North East |
4.1 |
41 |
North West |
11.3 |
113 |
Yorkshire & Humberside |
8.5 |
85 |
East Midlands |
7.5 |
75 |
West Midlands |
9.1 |
91 |
: | : | : |
: | : | : |
SEG |
% |
N (1,000) |
AB |
26 |
260 |
C1 |
29 |
290 |
C2 |
21 |
210 |
DE |
24 |
240 |
Total |
100 |
1,000 |
Ireland
|
NORTHERN IRELAND |
REPUBLIC OF IRELAND |
||
|
% |
N (325) |
% |
N(675) |
|
|
|
|
|
16-24 males |
7.8 |
25 |
8.1 |
55 |
16-24 females |
7.3 |
23 |
7.8 |
53 |
25-34 males |
9.2 |
30 |
8.6 |
58 |
25-34 females |
9.2 |
30 |
8.7 |
59 |
35-44 males |
8.8 |
29 |
10.6 |
71 |
: | : | : | : | : |
: | : | : | : | : |
|
NORTHERN IRELAND |
REPUBLIC OF IRELAND |
||
Social Grade (SEG) |
% |
N (325) |
% |
N(675) |
|
|
|
|
|
ABC1 |
55 |
179 |
57 |
385 |
C2DEF |
45 |
146 |
43 |
290 |
TOTAL |
100 |
325 |
100 |
675 |
Region |
|
REPUBLIC OF IRELAND |
IRELAND |
% |
N (675) |
City of Dublin |
29.1 |
196 |
Munster |
24.3 |
164 |
Leinster (excluding city of Dublin) |
29.1 |
196 |
Connacht |
9.4 |
64 |
Ulster (excluding Northern Ireland counties) |
8.1 |
55 |
TOTAL |
100 |
675 |
: | : | : |
France, Germany, Italy, Spain, Poland
FRANCE |
GERMANY |
ITALY |
SPAIN |
POLAND |
||||||
% |
N (1000) |
% |
N (1000) |
% |
N (1000) |
% |
N (1000) |
% |
N (1000) |
|
16-24 males |
7.2 |
72 |
6.2 |
62 |
6.7 |
67 |
5.9 |
59 |
7.0 |
70 |
16-24 females |
7.2 |
72 |
5.8 |
58 |
6.2 |
62 |
5.8 |
58 |
6.7 |
67 |
25-34 males |
7.9 |
79 |
8.3 |
83 |
7.8 |
78 |
7.4 |
74 |
10.7 |
107 |
25-34 females |
7.8 |
78 |
7.8 |
78 |
7.5 |
75 |
7.1 |
71 |
10.3 |
103 |
: | : | : | : | : | : | : | : | : | : | : |
: | : | : | : | : | : | : | : | : | : | : |
Region |
||
FRANCE |
% |
N (1,000) |
Île de France |
18.7 |
187 |
Centre-Val de Loire/Bourgogne-Franche-Comté |
8.2 |
82 |
Normandie/Hauts-de-France |
14.1 |
141 |
Grand Est |
8.6 |
86 |
Pays de la Loire/Bretagne |
11.0 |
110 |
Nouvelle-Aquitaine/Occitanie |
18.6 |
186 |
: | : | : |
: | : | : |
Starting with Wave 2
Net monthly household income - soft quota |
Germany |
France |
Spain |
Italy |
Poland |
|||||
|
min |
max |
min |
max |
min |
max |
min |
max |
min |
max |
Less than 1,500 € |
301 |
364 |
249 |
333 |
395 |
485 |
325 |
419 |
- |
- |
1,500 - 2,999 € |
329 |
397 |
288 |
385 |
303 |
372 |
317 |
409 |
- |
- |
3,000 € or more |
198 |
239 |
211 |
282 |
116 |
143 |
134 |
172 |
- |
- |
Less than 3,000 zł |
- |
- |
- |
- |
- |
- |
- |
- |
344 |
415 |
3,000 - 4,999 zł |
- |
- |
- |
- |
- |
- |
- |
- |
274 |
331 |
5,000 zł or more |
- |
- |
- |
- |
- |
- |
- |
- |
211 |
254 |
: | : | : | : | : | : | : | : | : | : | : |
Denmark, Netherlands, Finland, Sweden, Norway
|
DENMARK |
NETHERLANDS |
FINLAND |
SWEDEN |
NORWAY |
|||||
|
% |
N (1000) |
% |
N (1000) |
% |
N (1000) |
% |
N (1000) |
% |
N (1000) |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
16-24 males |
7.1 |
71 |
7.0 |
70 |
6.4 |
64 |
6.6 |
66 |
7.3 |
73 |
16-24 females |
6.8 |
68 |
6.8 |
68 |
6.2 |
62 |
6.0 |
60 |
6.9 |
69 |
25-34 males |
8.2 |
82 |
7.9 |
79 |
8.2 |
82 |
9.2 |
92 |
9.0 |
90 |
25-34 females |
7.9 |
79 |
7.7 |
77 |
7.8 |
78 |
8.8 |
88 |
8.7 |
87 |
: | : | : | : | : | : | : | : | : | : | : |
: | : | : | : | : | : | : | : | : | : | : |
Region |
|
|
|||
DENMARK |
% |
N (1,000) |
|||
|
|
||||
Hovedstaden |
31.7 |
317 |
|||
Sjælland |
14.3 |
143 |
|||
Syddanmark |
21.0 |
210 |
|||
Midtjylland |
22.9 |
229 |
|||
Nordjylland |
10.1 |
101 |
|||
: | : | : | |||
: | : | : |
Nigeria & South Africa
|
NIGERIA |
SOUTH AFRICA |
||
|
% |
N (1,000) |
% |
N (1,000) |
Male, 18-24 |
12.5 |
125 |
12.5 |
125 |
Male, 25-34 |
12.5 |
125 |
12.5 |
125 |
Male, 35-44 |
12.5 |
125 |
12.5 |
125 |
Male, 45+ |
12.5 |
125 |
12.5 |
125 |
Female, 18-24 |
12.5 |
125 |
12.5 |
125 |
Female, 25-34 |
12.5 |
125 |
12.5 |
125 |
: | : | : | : | : |
: | : | : | : | : |
NIGERIA |
% |
N (1,000) |
|
|
|
North (Central, East, West) |
54.0 |
540 |
South East |
11.3 |
113 |
South South |
14.9 |
149 |
Lagos & South West |
19.8 |
198 |
TOTAL |
100 |
1000 |
|
|
|
: | : | : |
: | : | : |
Saudi Arabia
Age and gender |
% |
N (1,000) |
Male, 18-24 |
12.5 |
125 |
Male, 25-34 |
12.5 |
125 |
Male, 35-44 |
12.5 |
125 |
Male, 45+ |
12.5 |
125 |
Female, 18-24 |
12.5 |
125 |
Female, 25-34 |
12.5 |
125 |
Female, 35-44 |
12.5 |
125 |
: | : | : |
: | : | : |
Region |
% |
N (1,000) |
|
|
|
Najid Region (Al-Riyadh, Al-Qaseem and Ha’il) |
31.8 |
318 |
Hijaz Region (Al-Baha, Al-Madinah Al-Monawarah, Makkah Al-Mokarramah and Tabouk) |
37.2 |
372 |
Other (Al-Jouf, Aseer, Eastern Region, Jazan, Najran and Northern Borders) |
31.0 |
310 |
TOTAL |
100 |
1000 |
Quotas: Americas
US
Quotas in the Americas are representative of the online population in each market.
Age by gender |
N=1,000 |
IPop % |
Male, 18-24 |
59 |
5.89% |
Male, 25-34 |
91 |
9.08% |
Male, 35-44 |
84 |
8.45% |
Male, 45-54 |
82 |
8.25% |
Male, 55-64 |
81 |
8.07% |
Male, 65-74 |
55 |
5.47% |
Male, 75+ |
29 |
2.86% |
: | : | : |
: | : | : |
Race |
N=1,000 |
IPop % |
White |
699 |
69.89% |
Black |
150 |
15.00% |
Asian |
61 |
6.06% |
Other race |
90 |
9.05% |
Total (all internet users aged 18+) |
1,000 |
100% |
Ethnicity |
N=1,000 |
IPop % |
: | : | : |
: | : | : |
Region |
N=1,000 |
IPop % |
Northeast |
175 |
17.44% |
Midwest |
207 |
20.73% |
South |
380 |
38.01% |
West |
238 |
23.81% |
Total (all internet users aged 18+) |
1,000 |
100% |
Household income |
N=1,000 |
IPop % |
Less than $25,000 |
107 |
10.68% |
$25,000 - $49,999 |
161 |
16.11% |
$50,000 - $74,999 |
153 |
15.34% |
$75,000 - $99,999 |
129 |
12.88% |
$100,000 plus |
450 |
44.99% |
Total (all internet users aged 18+) |
1,000 |
100% |
Canada
Age by gender |
N=1,000 |
Canada I-pop % |
Male, 18-24 |
68 |
6.90% |
Male, 25-34 |
76 |
7.60% |
Male, 35-44 |
96 |
9.6% |
Male, 45-54 |
65 |
6.5% |
Male, 55-64 |
81 |
8.10% |
Male, 65+ |
103 |
10.30% |
Female, 18-24 |
59 |
5.90% |
: | : | : |
: | : | : |
Province |
N=1,000 |
Canada I-pop % |
Ontario |
368 |
36.90% |
Quebec |
246 |
24.60% |
British Columbia |
136 |
13.60% |
Alberta |
121 |
12.10% |
Saskatchewan |
32 |
3.20% |
Manitoba |
32 |
3.20% |
Atlantic Provinces (New Brunswick, Newfoundland/ Labrador, Nova Scotia, Prince Edward Island) |
65 |
6.50% |
: | : | : |
Household income |
N=1,000 |
Canada I-pop % |
Less than $25,000 |
140 |
14.00% |
$25,000 - $49,999 |
208 |
20.80% |
$50,000 - $69,999 |
150 |
15.00% |
$70,000 - $99,999 |
178 |
17.80% |
$100,000 and over |
324 |
32.40% |
Total (all Canadian internet users aged 18+) |
1000 |
100% |
Brazil
Age by gender |
N=1,000 |
Brazil pop % |
Male, 16-24 |
90 |
8.96% |
Male, 25-34 |
112 |
11.16% |
Male, 35-44 |
111 |
11.11% |
Male, 45-54 |
72 |
7.20% |
Male, 55+ |
70 |
7.00% |
Female, 16-24 |
103 |
10.35% |
Female, 25-34 |
139 |
13.89% |
: | : | : |
: | : | : |
SEG |
N=1,000 |
Brazil pop % |
A |
25 |
2.50% |
B1 |
49 |
4.90% |
B2 |
164 |
16.40% |
C1 |
211 |
21.10% |
C2 |
264 |
26.40% |
DE |
287 |
28.70% |
Region |
N=1,000 |
Brazil pop % |
North |
75 |
7.46% |
Northeast |
232 |
23.23% |
Central West |
88 |
8.82% |
Southeast |
435 |
43.46% |
South |
170 |
17.04% |
Total (all Brazilian internet users aged 16+) |
1000 |
100.00% |
Mexico, Chile, Colombia and Peru
Age by gender |
||||||||||
|
Mexico |
Chile |
Colombia |
Peru |
Argentina |
|||||
N=1000 |
iPop % |
N=1000 |
iPop % |
N=1000 |
iPop % |
N=1000 |
iPop % |
N=1000 |
iPop % |
|
Male, 18-24 |
108 |
10.77% |
126 |
12.60% |
126 |
12.62% |
149 |
14.90% |
103 |
10.28% |
Male, 25-34 |
124 |
12.37% |
118 |
11.80% |
147 |
14.72% |
153 |
15.30% |
109 |
10.91% |
Male, 35-44 |
80 |
8.01% |
101 |
10.10% |
111 |
11.06% |
91 |
9.10% |
113 |
11.29% |
Male, 45-54 |
92 |
9.17% |
84 |
8.40% |
56 |
5.59% |
45 |
4.50% |
65 |
6.47% |
Male, 55+ |
73 |
7.28% |
77 |
7.70% |
43 |
4.33% |
65 |
6.50% |
71 |
7.11% |
: | : | : | : | : | : | : | : | : | : | : |
: | : | : | : | : | : | : | : | : | : | : |
Region
Mexico (based on Electoral circumscriptions) |
N=1000 |
iPop % |
Circunscripción 1 |
230 |
22.94% |
Circunscripción 2 |
198 |
19.83% |
Circunscripción 3 |
166 |
16.62% |
Circunscripción 4 |
192 |
19.19% |
Circunscripción 5 |
214 |
21.42% |
Chile |
N=1000 |
iPop % |
Metropolitana SGO |
432 |
43.20% |
Central |
310 |
31.00% |
Norte |
109 |
10.90% |
Sur |
149 |
14.90% |
Colombia |
N=1000 |
iPop % |
Atlantica/Caribe |
191 |
19.16% |
Central |
245 |
24.47% |
Oriental |
195 |
19.47% |
Pacifica |
170 |
17.00% |
Bogota |
199 |
19.89% |
Peru |
N=1000 |
iPop % |
Lima Metropolitana |
465 |
46.50% |
Non-Lima Metro |
535 |
53.50% |
Argentina |
N=1000 |
iPop % |
Buenos Aires (provincia & ciudad) |
366 |
36.6% |
Outside of Buenos Aires (provincia & ciudad) |
634 |
63.4% |