Author: Mintel Group Ltd.
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Spending Habits in Lower Tier Cities - China - October 2020
Overview
 
Introduction
Compared to Tier 1 and 2 cities, lower tier cities suffered less from the outbreak of the COVID-19 pandemic in the first half of the year. However, they are also less sensitive to the economic recovery and confidence rebound in the second half of 2020. Currently, consumers tend to be cautious with spending, but are not downgrading. When choosing brands and products that suit themselves, they think more about the occasions where the products can be used, the significance of the products and how they can meet their emotional needs. Taking into account the costs of trial and error, they explore the fun brought by all kinds of consumption.

Through quantitative (based on the quantitative data from multiple Mintel Reports in 2019 and 2020) and qualitative research (based on in-depth interviews with 20 respondents from 10 Tier 3 or lower cities), this Report analyses the differences in consumer behaviour and attitudes in different city tiers. This Report examines changes in consumer confidence before and after COVID-19 and changes reflected in spending on credit, luxury spending, domestic product spending and leisure spending; it also explains to brands what strategies would effectively increase their competitiveness in lower tier cities using a series of cases.

Key issues covered in this Report
●	Consumer confidence change
●	Acceptance of spending on credit
●	Attitudes towards luxury spending
●	Brand perceptions and selections
●	Focuses in leisure spending

Objective and Methodology
According to the National Bureau of Statistics, there were 672 cities in China at the end of 2018, among which 297 are of the prefecture level and 375 are of the county level. As Mintel clients have interest in multiple different aspects (region, city size), Mintel selects different cities for each round of surveys considering their geographical location and level of economic development (eg GDP, per capita income). Mintel classifies China's cities according to the following criteria:

●	Tier 1 cities: large economic centres, ie Beijing, Shanghai, Guangzhou, Chengdu*
●	Tier 2 cities: provincial capitals (eg Jinan), municipalities (直辖市) (eg Tianjin, Chongqing), and economically developed prefecture-level cities (eg Suzhou, Dalian)
●	Tier 3 or lower cities: mostly prefecture-level cities (eg Weifang, Ganzhou, Pingxiang).

*Mintel chooses Chengdu to represent Tier 1 cities in the Midwest of China for the purpose of regional comparative analysis.

Through quantitative (based on the quantitative data owned by Mintel collected from 2018-20) and qualitative research (based on in-depth interviews with 20 respondents from 10 Tier 3 or lower cities), this Report compares and analyses consumer behaviour and attitudes in different city tiers. Meanwhile, the Report further explores effective strategies for companies to improve their competitiveness in lower tier cities by analysing cases.
 
Quantitative Research Methodology
Quantitative consumer research data was collected from various Mintel Reports over 2019-20. The consumer research exclusively commissioned for China Reports was conducted by a Chinese licensed market survey agent, KuRunData. The online consumer survey was sampled in 10 cities, each with a sample size of 300 people, for a total of 3,000 people.

FIGURE 1: the sample structure for each city is as follows:
 
| | Gender and age | | | | | | Household income (RMB) | |
Tier 1 cities | Total | Male 20-29 | Male 30-39 | Male 40-49 | Female 20-29 | Female 30-39 | Female 40-49 | 6,000-9,999 | 10,000-17,999 | 18,000+
Beijing | 300 | 50 | 50 | 50 | 50 | 50 | 50 | 100 | 100 | 100
Shanghai | 300 | 50 | 50 | 50 | 50 | 50 | 50 | 100 | 100 | 100
Guangzhou | 300 | 50 | 50 | 50 | 50 | 50 | 50 | 100 | 100 | 100
Chengdu | 300 | 50 | 50 | 50 | 50 | 50 | 50 | 100 | 100 | 100
Tier 2, 3 or lower cities | Total | Male 20-29 | Male 30-39 | Male 40-49 | Female 20-29 | Female 30-39 | Female 40-49 | 5,000-8,999 | 9,000-15,999 | 16,000+
City 1 | 300 | 50 | 50 | 50 | 50 | 50 | 50 | 100 | 100 | 100
City 2 | 300 | 50 | 50 | 50 | 50 | 50 | 50 | 100 | 100 | 100
City 3 | 300 | 50 | 50 | 50 | 50 | 50 | 50 | 100 | 100 | 100
City 4 | 300 | 50 | 50 | 50 | 50 | 50 | 50 | 100 | 100 | 100
City 5 | 300 | 50 | 50 | 50 | 50 | 50 | 50 | 100 | 100 | 100
City 6 | 300 | 50 | 50 | 50 | 50 | 50 | 50 | 100 | 100 | 100
Total | 3,000 | 500 | 500 | 500 | 500 | 500 | 500 | 1,000 | 1,000 | 1,000

Source: KuRunData/Mintel

Qualitative Research Methodology
To explore the “why” behind the quantitative data, Mintel conducted in-home or online interviews with 20 respondents from 10 lower tier cities listed below. Each in-home visit lasted for about two hours with a moderator doing in-depth interviews with respondents, to understand their lifestyles, purchase preferences and the factors that influence them.

FIGURE 2: Interviewed cities in the qualitative research
  
Source: Mintel

In the qualitative research, Mintel selectively recruited affluent and educated respondents aged 25-39. In each city, Mintel recruited one male and one female respondent with a personal income of RMB6,000-10,000 if single, or a household income of RMB14,000-25,000 if married. These respondents are more sensitive to market trends and better able to express their opinions. This ensures the smooth running of the research and is critical to getting meaningful insights.

FIGURE 3: Profiles of respondents to the qualitative research
 
City | Gender | Age | Marital status | Education | Company type | Occupation | Income | Household members
Liuzhou, Guangxi | Male | 35 | Married with a 6 year old daughter | Postgraduate | State-owned business | University lecturer | Monthly household income RMB20,000 | Living with partner, one child and parents
Liuzhou, Guangxi | Female | 28 | Single | Undergraduate | State-owned business | Real estate salesperson | Monthly personal income RMB7,000 | Living with parents
Zhanjiang, Guangdong | Male | 27 | Single | Undergraduate | Self-employed/freelancer | Milk tea house owner | Monthly personal income RMB8,000 | Living alone
Zhanjiang, Guangdong | Female | 32 | Married with a 2 year old daughter | Undergraduate | State-owned business | Junior college lecturer | Monthly household income RMB16,000 | Living with partner, one child and mother-in-law
Linfen, Shanxi | Male | 30 | Single | Undergraduate | Self-employed/freelancer | Health supplement business owner | Monthly personal income RMB6,000 | Living with parents
Linfen, Shanxi | Female | 26 | Married with a 10 month-old daughter | Junior college | State-owned business | Port security | Monthly household income RMB20,000 | Living with partner and one child
Dezhou, Shandong | Male | 36 | Single | Junior college | Privately owned/foreign-owned business | Risk control at a private financial company | Monthly personal income RMB10,000 | Living alone
Dezhou, Shandong | Female | 29 | Married with a 3 year old daughter | Undergraduate | Privately owned/foreign-owned business | Insurance salesperson at a foreign-owned enterprise | Monthly household income RMB18,000 | Living with partner and one child
Hengyang, Hunan | Male | 29 | Single | Junior college | State-owned business | Production coordinator at a steel pipe manufacturer | Monthly personal income RMB6,000 | Living with parents
Hengyang, Hunan | Female | 37 | Married with an 11 year old daughter and a 6 year old daughter | Undergraduate | State-owned business | Vocational school teacher | Monthly household income RMB20,000 | Living with partner, two children and mother-in-law
Shangqiu, Henan | Male | 26 | Single | Undergraduate | State-owned business | Environmental assessment at an environment company | Monthly personal income RMB8,000 | Living alone
Shangqiu, Henan | Female | 38 | Married with a 12 year old son | Junior college | Privately owned/foreign-owned business | Field marketing at a life insurance company | Monthly household income RMB20,000 | Living alone, with the child at boarding school and husband working in another city
Ganzhou, Jiangxi | Male | 29 | Single | Undergraduate | Privately owned/foreign-owned business | Marketing at a manufacturing company | Monthly personal income RMB10,000 | Living alone
Ganzhou, Jiangxi | Female | 36 | Married with an 8 year old son | Junior college | Privately owned/foreign-owned business | Salesperson of funds and stocks at a foreign-funded financial company | Monthly household income RMB24,000 | Living with partner and one child
Anqing, Anhui | Male | 27 | Single | Undergraduate | Privately owned/foreign-owned business | Developer and customer coordinator at an international trade company | Monthly personal income RMB8,000 | Living alone
Anqing, Anhui | Female | 32 | Married with a 2 year old son | Undergraduate | Self-employed/freelancer | Mother and baby shop owner | Monthly household income RMB22,000 | Living with partner and one child
Jilin, Jilin | Male | 33 | Married with a 3 year old daughter | Undergraduate | State-owned business | Human resource at a state institution | Monthly household income RMB14,000 | Living with partner and one child
Jilin, Jilin | Female | 25 | Single | Undergraduate | Privately owned/foreign-owned business | Course consultant at a private educational institution | Monthly personal income RMB6,000 | Living with parents
Xianyang, Shanxi | Male | 30 | Married with a 1 year old daughter | Undergraduate | Privately owned/foreign-owned business | Salesperson at a pet food company | Monthly household income RMB14,000 | Living with partner and one child
Xianyang, Shanxi | Female | 29 | Single | Junior college | State-owned business | Telecommunications service | Monthly personal income RMB8,000 | Living with parents

Source: Mintel

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