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From Steps to Clicks
Online Shopping Behavior of
Women in Low Tier Markets
Stephanie Chai, Liu Jie, Wang Yuan Yuan, Huang Jia, Wu Jin
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Female purchase power in China
- Disposable income of Chinese
females are on the rise
- Female contributes to 35.8%
of family income and spend
29.2% of her family’s money on
herself
- Many also make purchase
decisions for their families, their
parents & in-laws
They are avid online shoppers.
Tier 1/2 cities: 44%
Tier 3/4 cities: 23%
Their average annual spending
on online shopping:
Tier 1/2 cities: Rmb2,096
Tier 3/4 cities: Rmb1,757
Only Rmb339 behind
Source: Huakun Female Lifestyle Survey 2011
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China’s middle and
affluent classes are
spread all over the
country in pockets of
growth and wealth.
E-commerce helps
marketers break out of the
limiting reach of brick and
mortar stores.
Broadband internet
penetration is close to
90% in tier 1 to tier 4
cities.
Credit Suisse forecast
that China’s e-
commerce will reach
Rmb2,703 billion by
2015, accounting for
6.7% of retail sales.
E-commerce in China
Source: Credit Suisse Equity Research, March 2011
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Digitization
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Digitization taking low tier markets by storm
Media reach of tier 3/4 cities
Respondents: people aged 15-45 PDD 2007 n=6153 PDD 2009 n=7577 PDD 2011 n=5151
93%
24%
32%
26%
6%
94%
40%
29% 30%
6%
85%
50%
23% 21%
7%
TV (yesterday) Internet(yesterday)
Newspaper(yesterday)
Magazine (past 1week)
Radio (yesterday)
PDD 2007
PDD 2009
PDD 2011
-10%
-21% -30%
+25%
Data source: PDD2007, 2009, 2011
TV
(yesterday)
Internet
(yesterday)
Newspaper
(yesterday)
Magazine
(past 1 week)
Radio
(yesterday)
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E-commerce is fast penetrating low tier markets:
Online shopping is among top 10 online activities
Top 10 online activities Tier 3/4 female Tier 1/2 female
Instant messenger (MSN, QQ) 74% 79%
Watch movies/ TV series/ TV programmes online 61% 47%
Use search engine for information 44% 70%
Online gaming 33% 60%
Read news on media websites (eg. Renmin, Xinhua) 33% 33%
Email 31% 37%
Listen to or download music/ ringtones 24% 20%
Browse daily life information 23% 48%
Online shopping 23% 44%
Visit SNS (Kaixin, Renren) 21% 24%
Data source: PDD2011
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Women in low tier markets & online-shopping
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With the massive economic growth,
Chinese consumers are becoming richer
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5,062
8,147
Tier 3/4 Tier 1/2
The monthly HHI in tier 3/4 markets is still less
than that of tier 1/2 markets
Data source: PDD2011, CNRS2011
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5,062
8,147
3,198
5,636
Tier 3/4 Tier 1/2
2011
2009
However, the rate of increase of monthly HHI in
low tier markets is faster
+58%
+45%
Data source: PDD2009, 2011 CNRS2009,2011
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Lifestyle & consumption of women in low tier
markets have also changed, getting closer to
their counterparts in tier 1/2 markets
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In fact, they have a strong demand for “imported
compared with domestic products”
35
56 63
2009 Tier 3/4female
2011 Tier 3/4female
2011 Tier 1/2female
Data source: PDD2009,2011 CNRS2011
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And trust for international and well-known brands
17
37
45
2009 Tier 3/4female
2011 Tier 3/4female
2011 Tier 1/2female
Data source: PDD2009,2011 CNRS2011
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They can be “more enthusiastic” than their
counterparts in tier 1/2 cities
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10% more tier 3/4 consumers “like to keep up
with the latest fashions”
52
42
Tier 3/4 female Tier 1/2 female
Data source: PDD2011 CNRS2011
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8% more tier 3/4 consumers are likely to “spend
money without thinking”
39
31
Tier 3/4 female Tier 1/2 female
Data source: PDD2011 CNRS2011
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Online-shopping behavior
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70
79
59
39 42
35
77 79
71
32
41
31
2011 Tier 3/4 female 2011 Tier 3/4 female e-shopperTier 3/4 female Tier 3/4 female e-shopper
More active in offline modern channels
Wet market Street vendor Grocery store Shopping
mall/center
Convenience
store/Mini-
supermarket
Independent
supermarket/
Hypermarket
Modern channels Traditional channels
Data source: PDD2011
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88
63
34 31
20 12
6 6
77 71
80
57
30 37
17
6
Tier 3/4 female Tier 3/4 female e-shopper
(yesterday) (yesterday) (yesterday) (past 1 week) (past 1 week) (yesterday)* (past 1 month) (past 1 month)
Except for TV, female online-shoppers in low tier
cities consume more media
TV OOH Internet Magazine Newspaper Mobile Cinema Radio
Data source: PDD2011
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Online-shoppers adopt a variety of ways to
access the internet
87% 86%
23%
31%
31%
7%
13%
22%
Blue for Total
Orange for online-shopper
Data source: PDD2011
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75
44
29 22
10
2 1
68
47
33
21 16
0 3
At home On going At work At school At someoneelse's home
Internetcafé*
Others*
Tier 3/4 female mobile internet user Tier 3/4 female e-shopper who uses mobile Internet
They are also heavy users of mobile internet,
gaining access from both in and out of home
On the go
Data source: PDD2011
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18% of female online-shoppers search for information and
16% write/read Weibo via mobile internet. Highly likely
that they share shopping information and experiences
anytime anywhere
17
12
18 16
For information Write/read microblog
Tier 3/4 female Tier 3/4 female e-shopper
Data source: PDD2011
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They also want to purchase on the spot
Source: Digital Natives @ apps.com, MEC 2011
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12 22 23
13 11 6 5 3 1 1
27
47 50
42 33
19 12
6 2 3
15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64
Tier 3/4 female e-shopper
Tier 1/2 female e-shopper
Female online shoppers in tier 3/4 markets are
younger than those in tier 1/2 markets
Data source: PDD2011, CNRS2011
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Women of North China are the most active online-
shoppers. Whereas for low tier markets, it is the
women of NW China that are most active
11 5
10 12 10 9 10
34
18
24 25
22 26 21
North China Northeast* East China Northwest Southwest South China CentralChina
Tier 3/4 female e-shopper Tier 1/2 female e-shopper
Data source: PDD2011, CNRS2011
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Top 5 categories tier 3/4 female online shoppers
like to purchase
Clothing/Accessory/shoes/bags
Skincare/cosmetics/perfume
Household products
Sport/leisure/outdoor products
Books/audios/softwares/magazines
IT digital products
Beauty & hair
Food*
Home appliances*
Baby care/children's wear*
Catering*
Mobile phones/ communication…
Others*
Air tickets*
Art Shows/ movies/ tickets*
Flowers/ gifts*
Photo*
Travel/holiday*
Automobile*
Pub/KTV*
Club/Gym*
Tier 3/4 female e-shopper
Tier 1/2 female e-shopper
Data source: PDD2011, CNRS2011
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Clothing/Accessory/shoes/bags
Skincare/cosmetics/perfume
Household products
Sport/leisure/outdoor products
Books/audios/softwares/magazines
IT digital products
Beauty & hair
Food*
Home appliances*
Baby care/children's wear*
Catering*
Mobile phones/ communication…
Others*
Air tickets*
Art Shows/ movies/ tickets*
Flowers/ gifts*
Photo*
Travel/holiday*
Automobile*
Pub/KTV*
Club/Gym*
Tier 3/4 female e-shopper
Tier 1/2 female e-shopper
More of them buy clothing/accessory, sport/leisure, IT
digital products and beauty & hair online than women in
tier 1/2 markets
Data source: PDD2011, CNRS2011
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Clothing/Accessory/shoes/bags
Skincare/cosmetics/perfume
Household products
Sport/leisure/outdoor products
Books/audios/softwares/magazines
IT digital products
Beauty & hair
Food*
Home appliances*
Baby care/children's wear*
Catering*
Mobile phones/ communication…
Others*
Air tickets*
Art Shows/ movies/ tickets*
Flowers/ gifts*
Photo*
Travel/holiday*
Automobile*
Pub/KTV*
Club/Gym*
Tier 3/4 female e-shopper
Tier 1/2 female e-shopper
With the development of online shopping in tier 3/4 cities,
household products have lots of upside potential
Data source: PDD2011, CNRS2011
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They only spend 339 RMB less on online-
shopping than their counterparts in tier 1/2 cities
Average annual expenditure
online (RMB) 2009 2011
Tier 3/4 female e-shopper 713 1,757
Tier 1/2 female e-shopper 1,450 2,096
Data source: PDD2009,2011, CNRS2009,2011
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Furthermore, the rate of increase is actually
much higher
Average annual expenditure
online (RMB) 2009 2011
Tier 3/4 female e-shopper 713 1,757
Tier 1/2 female e-shopper 1,450 2,096
+146%
+45%
Data source: PDD2009,2011, CNRS2009,2011
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And they are willing to spend more of their
annual household income on e-shopping than
their counterparts in tier 1/2 cities
2.3
1.8 1.4 1.6
Tier 3/4 female e-shopper
Tier 1/2 female e-shopper
2011
2009
Spent on e-shopping / monthly HHI (%)
+64%
+13%
Data source: PDD2009,2011, CNRS2009,2011
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Implications
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Implications - 1
Offline and online channels and platforms are intertwined
• Consumers tailor their usage of offline and online channels and
platforms based on availability, immediate needs, size of shopping list,
convenience in terms of time spent or geographical distance. Offline and
online should no longer be seen as standalone silos, but should be
treated as integral components of a single business model. The key is
to drive traffic from offline to online and vice versa as consumers move
along the purchase pathway.
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Implications - 2
From e-commerce to social commerce
• Social commerce refers to the use of social strategies to anticipate,
personalize and energize the shopping experience. Chinese consumers
are very social in their purchase process. They want confidence in what
they buy from their friends, and insight from their community. They are
prolific reviewers and readers of online product reviews. As this evolves,
the marketing mix will likely be more and more driven by consumers.
Marketers need to use new ways to sense and shape demand. The role
of brands is to be consumer’s friend and mentor, forging emotional
linkages with consumers. Brands can also create conversations with
consumers and provide them with materials to talk about in the social
space.
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Implications - 3
Building trust
• The issue of trust is central to building an effective, long-lasting online
relationship with consumers. This is especially true for the China market,
as consumers have an underlying wariness of fake products being sold
online. Reviews and recommendations from friends and fan communities
serve to alleviate some of the distrust. However, there are multiple facets
of consumer trust online, such as product quality, internet safety,
efficiency, return policy, warranty etc. Success for any e-commerce
player in China involves tackling the various components affecting trust
along every step of the purchase pathway.
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Implications - 4
Mobile strategy
• 70% of female online shoppers of low tier cities use their mobile phone to
access the internet at home, so a mobile strategy to offer convenience
and flexibility is necessary. The mobile strategy should be integrated into
the e-commerce and communication plan via the use of gamification,
augmented reality, social couponing and mapping/geospatial
technologies etc.
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Research methodology
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Research methodology
• This is a data mining exercise, drawing from GroupM Knowledge Center’s Project Deep Dive (PDD) surveys. PDD looked at consumption and media behavior of consumers in low tier cities (provincial level cities, county level cities and counties).
• 3 waves (2007, 2009 and 2011) of PDD survey data were used. The latest 2011 survey has a wider coverage, with the age bracket of respondents extended from 15-45 to 15-64 years old.
• Given that the respondents of PDD 2007 and PDD 2009 were in the 15-45 age bracket, only data of those who are from the same age group in PDD 2011 were used for YOY comparison.
• As for slides not involving YOY comparisons, the data were based on an age range of 15 to 64 years old. Due to the difference in the age group being used, the results may vary slightly between slides.
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Bibliography
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Bibliography
• Altimeter (2010) – Rise of Social Commerce : A Trail Guide for the Social Commerce
Pioneer, November 2010
• BCG (2010) – China’s Digital Generations 2.0: Digital Media and Commerce Go
Mainstream, May 2010
• BCG (2011) – The World’s Next E-Commerce Superpower, November 2011
• Huakun Female Lifestyle Survey 2011
• KPMG International (2011) – Going Social
• Credit Suisse (2011) – Equity Research: China Internet Sector, March 2011
• McKinsey Quarterly (2009) – The promise of multichannel retailing, October 2009
• McKinsey Quarterly (2010) – China’s Internet Obsession, February 2010
• MEC (2011) – [email protected]
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For more information, please contact:
Theresa Loo
National Director – Strategic Planning, Analytics & Insight
MEC China 29/F, 989 Changle Road
Shanghai China 200031
Direct line: +86 21 2307 7790
Switchboard: +86 21 2307 7800
Project Manager & Editor: Stephanie Chai
Data Analyst: Wang Yuan Yuan (Ivy)
Report write-up: Liu Jie (Jane)
Researchers: Amanda Song, Huang Jia (Fish), Wu Jin (Mandy), Cai Jing