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

Lightspeed

Lightspeed is our research partner for our US, Brazil, Canada and European markets (excluding Northern Ireland and the Republic of Ireland). Lightspeed’s 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. Lightspeed’s 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
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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
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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
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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
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		%	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
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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

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
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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

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	%	N (1000)

16-24 males	7.2	72
16-24 females	7.0	70
25-34 males	8.9	89
25-34 females	8.9	89
35-44 males	8.3	83
35-44 females	8.4	84
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Region
GREAT BRITAIN	%	N (1,000)
Scotland	8.6	86
North East	4.2	42
North West	11.3	113
Yorkshire & Humberside	8.5	85
East Midlands	7.5	75
West Midlands	9.0	90
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SEG	%	N (1,000)
AB	26	260
C1	29	290
C2	21	210
DE	24	240
Total	100	1,000

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
		100	1000

Indonesia	Jakarta	45	450
	Bandung	16	160
	Surabaya	12	120
	Yogyakarta	17	170
	Medan	10	100
		100	1000

Republic of Korea	Seoul	19	190
	Gyeonggi (including Incheon but excluding Seoul)	31	310
	Gyeongsang (including Busan, Daegu & Ulsan)	25	250
	Chungcheong (including Daejeon & Sejong)	11	110
	Jeolla (including Jeju & Gwangju)	11	110
	Gangwon	3	30
		100	1000
Thailand	Greater Bangkok	8.51	85
	Central Thailand (excl Bangkok)	25.94	259
	North Thailand	18.21	182
	Northeast Thailand	33.07	331
	South Thailand	14.26	143
		100	1000

Hong Kong, SAR of the PR of China	Hong Kong Island	16.6	166
	Kowloon	30.6	306
	New Territories East	24	240
	New Territories West	28.8	288
		100	1000

Malaysia	Central	26	260
	North	21	210
	South	18	180

	NORTHERN IRELAND		REPUBLIC OF IRELAND
	%	N (325)	%	N(675)

16-24 males	7.9	26	8.1	55
16-24 females	7.4	24	7.9	53
25-34 males	9.3	30	8.9	60
25-34 females	9.4	21	9.1	62
35-44 males	8.8	28	11.0	74
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	NORTHERN IRELAND		REPUBLIC OF IRELAND
	%	N (325)	%	N(675)

16-24 males	7.9	26	8.1	55
16-24 females	7.4	24	7.9	53
25-34 males	9.3	30	8.9	60
25-34 females	9.4	21	9.1	62
35-44 males	8.8	28	11.0	74
35-44 females	9.3	30	11.5	78
45-54 males	9.3	30	8.9	60
45-54 females	9.8	32	8.9	60
55+ males	13.6	45	12.3	83
55+ females	15.2	49	13.4	90
TOTAL	100	325	100	675

	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	28.9	196
Munster	24.3	164
Leinster (excluding city of Dublin)	29.1	196
Connacht	9.5	64
Ulster (excluding Northern Ireland counties)	8.2	55
TOTAL	100	675
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	FRANCE		GERMANY		ITALY		SPAIN		POLAND
	%	N (1000)	%	N (1000)	%	N (1000)	%	N (1000)	%	N (1000)


16-24 males	7.3	73	6.4	64	6.9	69	6.1	60	7.5	75
16-24 females	7.0	70	5.8	58	6.3	64	5.8	58	7.1	71
25-34 males	8.0	80	8.5	85	8.0	80	7.6	76	11.4	114
25-34 females	8.3	83	7.9	79	7.7	77	7.5	75	10.9	109
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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
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	DENMARK		NETHERLANDS		FINLAND		SWEDEN		NORWAY
	%	N (1000)	%	N (1000)	%	N (1000)	%	N (1000)	%	N (1000)


16-24 males	7.3	73	7.1	71	6.7	66	6.8	68	7.2	72
16-24 females	7.0	70	6.8	68	6.3	63	6.2	62	6.8	68
25-34 males	8.2	82	7.9	79	8.5	84	9.2	92	8.8	88
25-34 females	7.9	79	7.7	77	8.0	79	8.7	87	8.4	84
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	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
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NIGERIA	%	N (1,000)

North (Central, East, West)	54	540
South East	11	113
South South	15	149
Lagos & South West	20	198
TOTAL	100	1000

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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
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Region	%	N (1,000)

Najid Region (Al-Riyadh, Al-Qaseem and Ha’il)	33	330
Hijaz Region (Al-Baha, Al-Madinah Al-Monawarah, Makkah Al-Mokarramah and Tabouk)	35	347
Other (Al-Jouf, Aseer, Eastern Region, Jazan, Najran and Northern Borders)	32	323
TOTAL	100	1000

NATIONALITY	%	N (1,000)

Saudi National	57	574
Non-Saudi National	43	426
TOTAL	100	1000

Age by gender	N=1,000	IPop %
Male, 18-24	60	5.97%
Male, 25-34	92	9.19%
Male, 35-44	86	8.60%
Male, 45-54	82	8.18%
Male, 55-64	79	7.93%
Male, 65-74	55	5.51%
Male, 75+	28	2.83%
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Global Consumer

Mintel Consumer Research Methodology

Our research partners

Sample sizes by demographics and geographies

Quotas: Asia Pacific

Quotas: Europe, Middle East and Africa

Quotas: Americas

Race	N=1,000	IPop %
White	701	70.13%
Black	150	15.00%
Asian	63	6.28%
Other race	86	8.59%
Total (all internet users aged 18+)	1,000	100%

Ethnicity	N=1,000	IPop %
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Household income	N=1,000	IPop %
Less than $25,000	110	11.01%
$25,000 - $49,999	166	16.63%
$50,000 - $74,999	171	17.12%
$75,000 - $99,999	142	14.14%
$100,000 plus	411	41.09%
Total (all internet users aged 18+)	1,000	100%

Age by gender	N=1,000	Canada I-pop %
Male, 18-24	66	6.60%
Male, 25-34	90	9.00%
Male, 35-44	101	10.10%
Male, 45-54	70	7.00%
Male, 55-64	64	6.40%
Male, 65+	100	10.00%
Female, 18-24	62	6.20%
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Province	N=1,000	Canada I-pop %
Ontario	377	37.70%
Quebec	246	24.60%
British Columbia	119	11.90%
Alberta	117	11.60%
Saskatchewan	30	3.00%
Manitoba	39	3.90%
Atlantic Provinces (New Brunswick, Newfoundland/ Labrador, Nova Scotia, Prince Edward Island)	72	7.20%
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Age by gender	N=1,000	Brazil pop %
Male, 16-24	116	11.60%
Male, 25-34	117	11.73%
Male, 35-44	107	10.68%
Male, 45-54	74	7.37%
Male, 55+	69	6.93%
Female, 16-24	102	10.16%
Female, 25-34	126	12.60%
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Age by gender
	Mexico		Chile		Colombia		Peru
	N=1000	iPop %	N=1000	iPop %	N=1000	iPop %	N=1000	iPop %
Male, 18-24	118	11.83%	126	12.60%	113	11.30%	149	14.90%
Male, 25-34	110	11.00%	118	11.80%	132	13.20%	153	15.30%
Male, 35-44	102	10.17%	101	10.10%	112	11.20%	91	9.10%
Male, 45-54	90	9.00%	84	8.40%	64	6.40%	45	4.50%
Male, 55+	48	4.83%	77	7.70%	61	6.10%	65	6.50%
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Mexico	Region (based on Electoral circumscriptions)	N=1000	iPop %
	Circunscripción 1	176	18%
	Circunscripción 2	203	20%
	Circunscripción 3	196	20%
	Circunscripción 4	207	21%
	Circunscripción 5	218	22%

Chile	Region	N=1000	iPop %
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