Factors Influencing Customer Satisfaction: A Case Study Of Auspaper

Survey Results and Correlation Analysis

Due to emerging technologies globally, businesses have been experiencing a myriad of challenges. The success of a business nowadays therefore depends on the approaches that an organization will employ to ensure that it remains afloat in the market amidst high class competition. To most firms, keeping abreast with technological changes in the business world has been their game changer. Apart from the firm keeping abreast with technological advancement, it is also paramount for companies to understand their customers from time to time because they also change due to the dynamics in the market.

Auspaper, a company that deals in paper product, has decided to take a cautionary step to safeguard their business. The company feels that due to technological advancement, the number of people who will be depending on paper work will be reducing greatly. It has been producing thousands of tonnes of paper that it has supplied to various continents of the world. Apart from exporting the papers, they have been selling the products either directly to the consumers or indirectly to through the retailers. With the advancement of technology and introduction of computers and more so smartphones, the company feels that most of the media will be accessed electronically through smartphones or computers. This will greatly interfere with the company’s revenue hence need to conduct a survey to understand their customers better once more. The survey carried out on managers who are customers to Auspaper Company.The table 1 above gives a descriptive statistics of satisfaction score depending on the previous purchases of the customers. The score were given from 1 to 10 where 1 indicated less satisfaction and 10 high satisfactions. It can be observed that the mean satisfaction is 6.95. This is an indication that the satisfaction of customers is above average. That is, customers of Auspaper products are satisfied with their previous purchases. This is further confirmed by the minimum score of 4.7 and maximum score of 10. The mode response regarding satisfaction was 5.4 which is also above average. 

1.2 Summary of whether one would consider strategic partnership with AuspaperFigure 1 above shows the proportion of Auspaper product customers that would consider strategic partnership even in the future. As can be observed, 57% of the respondents indicate that they are not willing to consider partnership with the company. Only 43% indicated that they are willing to consider having a strategic partnership with the company. This is a worrying trend if the statistics above are anything to go by. The company therefore should step up their marketing research to understand their customers better.

Regression Analysis

2.1 Factors influencing customer satisfaction

There are several factors that may have influenced customers’ satisfaction. However, some factors had significant influence on the satisfaction than others. To be able to identify the strength of the variables, a correlation analysis was conducted between the various variables and satisfaction. The following are the correlation analysis test results.

Correlation analysis

Tables 2

The correlation tests above were focused on finding the variables that had a high correlation coefficient. These were considered as having a significant importance in influencing the customers’ satisfaction.  The following variables were selected since they have a correlation coefficient of over 0.5.

• Product line
• Customer type
• Product quality
• Complaint resolution
• Distribution system
• Delivery speed
• Billing.

Product line

Product line has a correlation coefficient of 0.64. This indicates a strong correlation between customer satisfaction and product line considering that a strong correlation is between 0.5 and 1 whether positive or negative while zero indicates no correlation between variables.

Customer type

Customer type has a correlation coefficient of 0.7. This indicates a strong correlation between customer satisfaction and customer type considering that a strong correlation is between 0.5 and 1 whether positive or negative while zero indicates no correlation between variables.

Product quality

Product quality has a correlation coefficient of 0.52. This indicates a strong correlation between customer satisfaction and product line considering that a strong correlation is between 0.5 and 1 whether positive or negative while zero indicates no correlation between variables.

Complaint resolution

Complaint resolution has a correlation coefficient of 0.59. This indicates a strong correlation between customers’ satisfaction and complain resolution considering that a strong correlation is between 0.5 and 1 whether positive or negative while zero indicates no correlation between variables.

Distribution system

Distribution system has a correlation coefficient of 0.54. This indicates a strong correlation between customer satisfaction and distribution system considering that a strong correlation is between 0.5 and 1 whether positive or negative while zero indicates no correlation between variables.

Delivery speed

Distribution system has a correlation coefficient of 0.63. This indicates a strong correlation between customer satisfaction and delivery speed considering that a strong correlation is between 0.5 and 1 whether positive or negative while zero indicates no correlation between variables.

Billing

Distribution system has a correlation coefficient of 0.54. This indicates a strong correlation between customer satisfaction and billing considering that a strong correlation is between 0.5 and 1 whether positive or negative while zero indicates no correlation between variables.

2.2 Model to predict customer satisfaction

ANOVA Results

The regression model containing possible variables predicting the customers’ satisfaction is as in the table belowAs can be observed in the table multiple regression tables above containing 15 variables, the value of R-squared is 0.8466. This means that 84.66% variation in the response variable (satisfaction) can be explained by the explanatory variables. The coefficients of the independent variables also indicate that the variables have got varying strengths as far as influencing satisfaction is concerned. The variable with the greatest coefficient is firm size which has a correlation coefficient of 0.51 while the second one greatest was distribution system which had a coefficient of 0.34. Others were advertising and product line which had 0.34 and 0.33 respectively.The regression table above contains variables that were chosen as a result of their high coefficients. Their linear relationship with satisfaction is as in the table above. It can be observed that the values of the coefficients of the predictive variables have increased. It can also be observed that the value of R-squared is 0.6343. This shows that independent variables explain up to 63.43% of the variation in the dependent variable.

2.3 Test for interaction effect

Table 5

From the analysis of variance results above, it can be observed that the p-value is .014. This value is less than the level of significance, 0.05. Therefore it can be concluded that product line and customer location are independent of each other.

3.1 Model Building (Likelihood of Building Strategic Partnership)

The following variables were chosen as the best predictors of likelihood of building strategic partnership.

• Product quality
• Product line
• Personnel image
• Price flexibility
• Competitive pricing

It can be observed from the multiple regression above that the value of R-square is 0.4196. This value means that the independent variables are able to explain 41.96% of the variation in the dependent variables. This is an indication that much of the variation in the dependent variable (likelihood for partnership) is not explained by the independent variables. However, the variables have got different strengths of predicting the dependent variable going by their coefficients. Price flexibility and product quality can be seen to be having the greatest coefficients. Another model is therefore constructed to have the two variables only so as to assess whether the model predicts the variables better.

Second model with price flexibility and product qualityAs can be observed from the multiple regression model above, the explanatory variables are only able to explain 25.82% of the variation that occurs in the dependent variable (likelihood for partnership). It can also be said that a unit change in product quality leads to a corresponding negative change 0.2 units in the dependent variable. On the other hand, a unit change in price flexibility leads to corresponding negative change 0.2 units in the dependent variable. We can therefore conclude that price flexibility and product quality have a negative with “likelihood of partnership.

4.0 Financial turnover forecasting in the next 3 quarters

First quarter5. Conclusion

The analysis of the results of this survey has found that in as much as Auspaper has been in the market for several years, there are still gaps in their market which need to be attended to swiftly in order to save the company from losing customers. This is in regard to the finding that 57% of the customers were not willing to consider partnership with Auspaper going from previous purchases. This is a cause to worry about and should be addressed by the management of the company in order to ensure high level of customer retention. The study also found out that there was just average satisfaction among the customers as far using Auspaper product is concerned. This report recommends to the management of the organization to conduct further research so as to find out the reason why their customers’ rate of satisfaction is just average.

The study hypothesized that this could be as a result of better competing products from other companies. Customers who attested to having high levels of satisfaction highlighted the causes as complaint resolution. This is a good indication that this company does well when it comes to customer complaint resolution. Another reason for high satisfaction was the speed at which the company delivers products to the customers. However, this report recommends that more still need to be done as the scores were just slightly above average. Low satisfaction was highlighted due to reasons such as new products, technical support and price flexibility.

There could be indications that the new products produced by the company are not up to the standards of the consumers or there are other competing products from other companies. The technical department of the company needs to do more when it comes to technical services offered to their customers as this seems to one of the reasons the company might lose customers. The major limitations in this research survey was low response from participant since a good number were did not complete the survey. The other challenge was that some managers were not willing to give out information that was critical to this research.

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