Advanced Data Analysis
For clients who have already designed their questionnaires and are in need of sufficient samples for online surveys, we offer a diverse panel pool of different ages, genders, careers, etc. Clients will have a direct access and connection to our panel pool. The questionnaires and answers data are transferred and reserved on your system with the highest security and without any other parties’ interference. Besides, based on the specific requirements of the survey, clients can select their suitable group of respondents with various criteria.
 
CLUSTER ANALYSIS
Cluster analysis is a powerful tool in modern marketing as it helps product/service makers divide their potential consumers into different groups (clusters) based on their distinctive characteristics. Thus, product/service makers may get deep into their targeted segmentation to figure out their needs and desire to develop the best-fit products.
Using our Survey profile, along with other customized survey design and Cluster analysis methods might be the key for new market entrance in targeting their customers, designing their products and planning marketing campaign.
STRUCTURAL EQUATION MODEL (SEM)
In brief, structural equation model is a general extension of multiple regression analysis. In other words, multiple regression analysis may be regarded as a special case of structural equation model. Structural equation model is advanced and influential method in business analysis as it may measure the immeasurable issues such as customer satisfaction, expectation or engagement.
Structural equation model includes four steps:
(a) Initial model conceptualization
(b) Parameter identification and estimation
(c) Data-model fit assessment
(d) Potential model modification, which, taken together provide insight of actual business practices; thus, give our valuable clients a number of recommendations to design or re-design their policies and strategies.
MUTIPLE REGRESSION MODEL
Multiple regression analysis predicts the dependence of one dependent variable on two or more independent variables. Multiple regression analysis is one of the most popular tools that help to understand cause-effect phenomena happened ubiquitously in daily life in general. In business practice in particular, with multiple regression, we can shed the light on a number of phenomena, such as why even satisfied customers switch or what make employees loyal with their employers.
Cluster analysis is a powerful tool in modern marketing as it helps product/service makers divide their potential consumers into different groups (clusters) based on their distinctive characteristics. Thus, product/service makers may get deep into their targeted segmentation to figure out their needs and desire to develop the best-fit products.
Using our Survey profile, along with other customized survey design and Cluster analysis methods might be the key for new market entrance in targeting their customers, designing their products and planning marketing campaign.
In brief, structural equation model is a general extension of multiple regression analysis. In other words, multiple regression analysis may be regarded as a special case of structural equation model. Structural equation model is advanced and influential method in business analysis as it may measure the immeasurable issues such as customer satisfaction, expectation or engagement.
Structural equation model includes four steps:
(a) Initial model conceptualization
(b) Parameter identification and estimation
(c) Data-model fit assessment
(d) Potential model modification, which, taken together provide insight of actual business practices; thus, give our valuable clients a number of recommendations to design or re-design their policies and strategies.
Multiple regression analysis predicts the dependence of one dependent variable on two or more independent variables. Multiple regression analysis is one of the most popular tools that help to understand cause-effect phenomena happened ubiquitously in daily life in general. In business practice in particular, with multiple regression, we can shed the light on a number of phenomena, such as why even satisfied customers switch or what make employees loyal with their employers.
CONJOINT ANALYSIS
In a nutshell, conjoint analysis aims to answer the question which attributes /characteristics of a product/service are important to customers and to what relative importance they are. Conjoint analysis bases on the premise that each customer has different preference when he or she has to face a trade-off situation for a final determination of buy or not buy a product/service. There are different types of conjoint analyses such as self explicated model, adaptive conjoint analysis or choice based conjoint analysis with each dedicates to solve a particular problem faced by manufacturer and provider in marketing practices, mostly in market segmentation or new product development.
MULTIDIMENSION SCALING
MultiDimensional scaling (MDS) helps to create a specific description of a respondent’s perception about a product/service or others attribute of interest, in comparing with other product/service. In other words, it judges the similarity and difference of attributes between difference product/service. For instance, how different are two fast food hamburgers, one bought in a franchised fast-food restaurant with worldwide-recognized brand and another bought in newly established local fast-food restaurant? Which attributes of the hamburger are perceived as similar and which are different? Thanks to MDS technique, we can find answers for these above questions.
This method is particularly useful in understanding hard-to-measure items such as product quality and expectations, perceived by different individuals. MDS have been developed to solve a wide range of problems in both theory and practice, such as customer segmentation, new product development or branding equity and awareness.
In a nutshell, conjoint analysis aims to answer the question which attributes /characteristics of a product/service are important to customers and to what relative importance they are. Conjoint analysis bases on the premise that each customer has different preference when he or she has to face a trade-off situation for a final determination of buy or not buy a product/service. There are different types of conjoint analyses such as self explicated model, adaptive conjoint analysis or choice based conjoint analysis with each dedicates to solve a particular problem faced by manufacturer and provider in marketing practices, mostly in market segmentation or new product development.
MultiDimensional scaling (MDS) helps to create a specific description of a respondent’s perception about a product/service or others attribute of interest, in comparing with other product/service. In other words, it judges the similarity and difference of attributes between difference product/service. For instance, how different are two fast food hamburgers, one bought in a franchised fast-food restaurant with worldwide-recognized brand and another bought in newly established local fast-food restaurant? Which attributes of the hamburger are perceived as similar and which are different? Thanks to MDS technique, we can find answers for these above questions.
This method is particularly useful in understanding hard-to-measure items such as product quality and expectations, perceived by different individuals. MDS have been developed to solve a wide range of problems in both theory and practice, such as customer segmentation, new product development or branding equity and awareness.
 
PRICELIST