Analysis Of Consumer Satisfaction And Variables That Affect It – Auspaper Case Study

Descriptive Statistics

The report depicts the measurable changes taking place in the business filed due to the adaptation of improved digitized technologies in terms of digital devices. In the modern world for the presence of different improved applications people get option to keep collect news by connecting themselves to the social media, websites. Even by watching YouTube and real time videos people can collect and share videos to others and also can stream live videos. In order to lead the business operation from the traditional to modern one, the way through which the business industries have adopted different challenges and those challenges are leading the business towards the modern business application are also elaborated in this report.  In order to ensure the balance between products purchase and selling the companies are keep on engaging the corporate capabilities and individual customers also (Wuyts, Rindfleisch & Citrin, 2015). This will help to build effective and efficient strategic relationship between the service providers and consumers. By specifying the strength and weakness of an enterprise the effect of sales could be understood. However, the view of the existing consumers cannot be understood by the business owners through the product purchasing and selling. Due to the higher rate of the newspapers and magazines the rate of newspaper purchasing are getting reduced frequently.

Due to the frequently decreasing rate of newspapers and magazine sales a company named as Auspaper is facing Major industrial loss. It has been analysed that in order to gain measurable success, revenue and competitive advantages from the market place the companies must build a better relationship along with the consumers by serving quality and affordable price ranged products (Lariviere et al., 2014). In order to predict the likelihood of the consumer satisfaction strategic alliance can be easily created with the help of the system.  

The information collected from various resources, through both primary and secondary data collection methodologies include information regarding the view of the consumers about the products and services served by the business organizations. Not only this but also the based on their views the products and services are rated on 0 to 10 ranking scale where 0 is the lowest score and 10 is the highest score (Sun & Kim, 2013). The ratings are based upon the number of consumer who bought products from Auspaper and the number of employees working for the newspaper and magazine company.  The satisfaction level of the consumers can be affected with the location of the consumers. On the other hand, from the sampled consumers the mode of product distribution process that is generally used for perceiving quality products are also can be extracted. Based upon the view of the consumers, whether the company could align towards the satisfaction level of the customers or not are created the management authority.

Form the survey it has been found that on the rating scale the average range got by the consumers is around 7.894. It indicates that the news paper and magazine selling company named as Auspaper, is enhancing their products and quality only for their customers. However for the products quality most of the consumers gave a customer rate around 9.9 out of 10. The quality of the products turned towards high ranged satisfaction level, because according to most of the consumers the paper served by Auspaper is very satisfactory (Moreno et al., 2015). However, the company is unable to solve the complaints got from the consumers from different zone. Though, the number of complaints received by the consumer’s ranges very less. Other averagely rated factors include product line, the image of salesforce, internal support level, extended development and new products produced for selling (Taylan Dortyol, Varinli & Kitapci, 2014). The satisfaction considering these factors, and price are rated about 6.98 out of 10. On the support and warranty level of the consumers the rating is about 6.04.

Identification of Noteworthy Variables for the Nominated Model

For some of the factors the consumer satisfaction level was underrated. These factors include whether the perception of billing and ordering are handles easily by the consumers or not, the delivery frequency, the existing e-commerce activity, price affordability and the advertise campaign. In order to improve the customer satisfaction level, that will increase the rate of alignment of the consumers towards the strategic alliance of Auspaper are also required to be considered (Den Hartog et al., 2013). From the average it is found that the satisfaction level is around 58% of the sampled customers. The firms purchasing newspaper and magazine from Auspaper are equally distributed between the newspaper and magazine industries. The demand for the magazines and newspapers are more from other countries than New Zealand and Australia. The indirect method for supplying the quality products produced by the company is more by 4% compared to other direct methods. The type of the consumers are divided in three phases such as less than 1 year, between 1 and five years, more than five years and these were equally distributed in there different groups.  

While conducting multiple regression process it is strictly needed to assume different assumptions. Initially, from a normal distribution, the response is required to be done accordingly. With the help of the histogram plotting, the assumptions are required to be tested by the management authority of the Auspaper (Sakhaei, Afshari & Esmaili, 2014). The distribution has turned out to be a normally distributed one it implies that the information was drawn from normally distributed population. For the second assumption is has been considered that a linear relationship is needed to be established, between the continuous predictors and response variable. In order to meet the requirement of the consumers it is necessary to develop a correlation matrix. It has been observed that with the response, only 6 variables had the moderate relationship.  

The variable of the first model include product quality, complaint resolution model, salesforce image, the delivery speed, the billing and ordering perception, firm size, industry type, customer’s location, distribution system and complaint resolution method (Chen, Martin & Merchant,  2014). The level of customer satisfaction is calculated by the below formulae

Whereby,

The consumers are segmented into two dummy variables that would cater for the three levels categories. The first type is the base or reference group and other variables included in the model involved in the similar way. According to the presented model the variable can be interpreted.  

From the survey it has been determined that the customer satisfaction level varies based upon the time, it means that the consumers who are purchasing products for 1 to 5 year, less than one year and more than five years got 0.665, 0.726 and 0.061 respectively. Similarly, the customer satisfaction level is dependent on the delivery speed. The customers belong from out of New Zealand and Australia are more satisfied than the inner ranged customers.

By removing the insignificant predictors the customer satisfaction level can be measured. The second model is based upon removal of the unnecessary predictors. It is found that after the removal of the unnecessary predictors, the set of remaining predictors are all significant because their p-value is less than 0.00001. As the co-efficient are changed thus, the model will be reshaped on different weight (Xiao, Chen & Chen, 2014). The variable of the new model include product line, salesforce image, product quality, consumer types and firm size.

Model Construction for Predicting the Rate of Customer Satisfaction

The second model states that, with the increased product line the level of customer satisfaction will increase by 0.237. On the salesforce image the view of the consumers, are directly related to the customer satisfaction. The development in the opinion trough one score enhances by 0.353. In order to gain competitive advantages from the marketplace and to get measurable revenue from the competition, the main component that is required to be considered includes customer satisfaction and quality of the products (Swaminathan et al., 2014).  This particular model, considers the customer perception and from the improved quality the measured satisfaction level increased by 0.397.

In order to check the effect and significance of two different predictor variables and their interaction three different models are plotted professionally. In R-square of 41.78%, the preliminary model that was generated includes product line. On the other hand, the second model includes customer location along with the product line and thus the R-square value enhanced by 45.23%. It has been found that, both the product line and the customer location are significant at 95% of confidence level. After analyzing all the models and their features it has been found that, both predictors and heir interaction are important for the process analysis (Reilly et al., 2014). The predictors and the interaction levels are significant at 95% confidence level and about 50.3% R-square is improved. As the interaction effect was significant in this mode, thus, in this model, the customer location can be referred to as the interaction variable. The most suited model for this calculation is measured below:

Depending upon the interaction model, it has been found that, the product line score will enhance the overall level of customer satisfaction by the rated of 0.31. However, it is found that the consumer belongs to out of Australia and New Zealand is not that much satisfied as the other and it rated up to 2.927. The customer satisfaction will increase and improved by 0.555 by the effective interaction between the product line and religion help.

In order to predict the probability of strategic alliance that is based upon the product line and the sales force image, a logistic model is needed to be plotted (Brach et al., 2015). It has a sensitivity level around 70.90%, thus it can be said that the model has a lesser amount of due to its 76.31% specificity. It has found that, the confidence interval is 95% for both the model predictors. The model obtained is given below and from the equation the generated value is 0.2258 as the probability of having an alliance for the neutral (5) product line and sales force image.

From the analysis it has been found that, in the predictors different components are widely used those include quality of the products and price affordability and these are similar to the logistic model. In different levels the probabilities can be calculated from the model and formulae is given below:

		Price flexibility
Product Quality		0	5	10
1	0.0000	0.0007	0.0536
2	0.0000	0.0021	0.1398
3	0.0001	0.0061	0.3182
4	0.0002	0.0173	0.5727
5	0.0007	0.0482	0.7938
6	0.0019	0.1271	0.9171
7	0.0055	0.2948	0.9695
8	0.0156	0.5456	0.9892
9	0.0434	0.7752	0.9962
10	0.1154	0.9083	0.9987

The above table shows the variant difference and how the product flexibility and rated price varies from one other. The customer who has rated 0 price flexibility and 1on the product quality had no chance for having any kind of strategic alliance. Thus, it can be said that, the value will increase frequently if the rate increases (Namasivayam, Guchait & Lei, 2014). It will help to increase the alliance significantly (Ekinci et al., 2014). With the obtained ratings it is found that, for both of the ratings the probability is nearly around 1.

In order to estimate three periods that include the second, third and fourth quarter (in the year of 2017), a time series and linear prediction models are used by the management authority. Not only this, but also, through the thousands of dollars the values gained are respectively 5701.20, 5754.1 and 5807.  

References

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