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China Market Analysis - Market Assessment

Market research is a type of due intelligence that supplies a large amount of data which are worth analyzing fully and intelligently. Having a good research analysis would give our clients a clear vision of China market. Over the years, Starmass has developed and used multivariate statistical  methodologies to interpret the results in more depth to serve our clients better.

 

Through statistical analysis with our professional experience, we are able to perform comprehensive China market assessment, which can include:

 

   * Market supply and demand

   * Assessment of market size

   * Market segmentation and points of sales

   * Market competition

   * Opportunities and threats related to the industry

   * Overall efficiency of the industry

   * Strength and weakness analysis of the products

   * Analysis of market potentiality

   * Costs and profitability

   * Customers' needs and expectation

   * Analysis of market trends

   * Assessment of the overall marketability

 

The following are the common multivariate statistical analysis that we use after market research:

 

1. Regression analysis

 

Regression analysis studies the dependence of a single, interval scale variable (such as sales) on simple or multiple variables. Regression analysis can be used to predict or explain the value of one quantitative variable based on the value of another variable. It can also predict or explain the value of a quantitative variable based on the value of more than one other variable, and determine which of those other variables has the strongest influence on the variable being predicted.

 

2. Factor analysis

 

Factor analysis is an analytical tool that helps to reduce a large number of variables into a more manageable set. It does this based on correlations within the data by (i) identify the number of factors; (ii) define the factors as functions of the measured variables; (iii) analyze the factors which have been defined. The factors produced can show what judgment patterns lay behind people’s image evaluations of the products in our China market research analysis.

 

3. Principal component analysis

 

Cluster Analysis uses several techniques to classify people, objects, or variables into more homogeneous groups. It can be used to identify market segments, develop typologies and find target markets. For example, with the help of different cluster processes we can find out what the customer segments in the sector are and how attractive it is to process the segments according to their willingness to purchase.

 

4. Cluster analysis

 

Cluster Analysis uses several techniques to classify people, objects, or variables into more homogeneous groups. It can be used to identify market segments, develop typologies and find target markets. For example, with the help of different cluster processes we can find out what the customer segments in the sector are and how attractive it is to process the segments according to their willingness to purchase.

 

5. Discriminant analysis

 

Discriminant analysis examines how two or more groups of respondents differ from one another based on a few predictor variables. It is practical for (i) discovering variables (i.e., a discriminant function) which are the distinguishing factors, (ii) understanding differences among groups and (iii) forecasting market behavior based on demographic and psychographic variables. For example, we would be able to measure the average percentage increase in sales per month since advertising on the TV has started.

 

6. Conjoint analysis

 

Conjoint analysis is used to evaluate preferences and tradeoffs that buyers are willing to make for their desired product. We need to find out what kinds of products are complementary or substitutes for one another. The techniques are thus effective tools for developing bundling of product or service offerings, optimizing product configurations, and diagnosing competitive strengths and weaknesses.

 

7. Correspondence analysis

 

China market research frequently involves categorical data. With a contingency able, this method allows us to differentiate any relations between two or more categorical variables. This analysis could help us answer the questions: who our customers are? who else our customers should be? what new products we should create? etc.

 

8. Multidimensional preference analysis

 

Consumers’ preferences for goods are based on various factors. However, these factors are not often defined in the China market. Thus, a multidimensional preference analysis will be able to analyze such data by using a data matrix whereby the columns represent consumers and the rows represent products. By analyzing the data matrix, we will be able to find out patterns of consumers’ preferences and better marketing strategies can be formed.

 

9. Multidimensional scaling analysis

 

This method is used to find out what products are substitutes or complementary of one another. Thus, we will be able to find out how do consumers perceive your products and what products could affect the sales of your products.

 

10. Benchmarking analysis

 

In order to understand what level of comparable services the competitors are supplying, we could combine the benchmarking analysis with best-practice and relevance analysis. We do not just show where competitors are possibly performing better, instead we analyze in which areas it is worth being better. The benchmarking analysis shows how performance leads to good positioning in China market as consumers increase the purchasing intentions.

 

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