Investigating Consumer Perception Of Fonterra Co-operative Group Limited: A Marketing Research Proposal

Background

Topic: Investigation of the consumer perception of the product line-“A case study of Fonterra Co-operative Group Limited”

This report is a marketing research proposal for the organization named Fonterra Co-operative Group Limited. Marketing research proposal aims to collect data based on the needs of the consumers and business to draw relevant conclusion in the study. The report will aim to identify the perception of the consumers regarding the products offered by Fonterra in order to identify the issues in stagnancy in sales for the past decade.

Fonterra Co-operative Group Limited is owned by more than 10,000 farmers in New Zealand and the company contributes to almost one third of exports all over the world. It is the largest organization in the country of New Zealand (fonterra.com, 2018). The organization has gone through ups and downs where the organization has been awarded for environmental conservation efforts and at the same time has been has faced allegation and criticisms for deforestation and use of light coal respectively. The biggest scandal the organization has to face was Sanlu milk scandal in China which killed a number of infants and many fell sick (LOUISSON, 2018).

Fonterra has been considered as a failure in both practice and concept which shows the level. Even though, the organization has maintained their monopoly in the New Zealand market, but the strategies implemented by the organization has failed miserably for the stakeholders and has heavily affected the corresponding environment. The analysis of the data from the past 17 years shows that the organization has not been able to increase their returns. This is a shocking fact that production of milk has increased by 108% but revenue has stagnated (LOUISSON, 2018). The improvement in the total payout received by the farmers in New Zealand is limited, even though the farmers have slogged their way to double the production of milk. The company has contributed immensely to the degradation of the natural environment which shows that the organization could fall under scrutiny for their practices (LOUISSON, 2018). Therefore, this report will propose the organization to conduct a study for identifying reasons for lack of improvements is sales and return.

Fonterra Co-operative Group Limited has not been able to increase their return significantly in the past 20 years even though the production of milk has doubled. This is one of the biggest areas of concern for the organization and improvement is required for long term sustainability and profit margin. Therefore, this research has aimed to identify the reasons for the lack of increase in sales volumes in the past decades so that they can make informed decisions based on the statistical data collected. The statistical analyses conducted on the data collected will provide valuable insights on the issues and the strategies that has to be implemented to improve the return for the farmers. The objectives of the current marketing research proposal are as follows:

• To investigate the factors that has affected the sales volumes in Fonterra Co-operative Group Limited
• To investigate the product line of Fonterra Co-operative Group Limited to identify the most popular products
• To investigate the perception of the consumers regarding the brand and the products offered by them
• To examine the sales of the products based on their pricing
• To identify the consumer segment that has not been utilized properly by Fonterra Co-operative Group Limited
• To evaluate the sales of the product offered by Fonterra Co-operative Group Limited in all the cities in New Zealand
• To determine the most sold product of Fonterra Co-operative Group Limited
• To identify the sales of the products based on different criteria such as gender, frequency, monthly expenditure and market share

Objectives

In this current market research, primary and secondary data sources have been used by collecting data for identifying the factors affecting the sales volumes and revenue of Fonterra Co-operative Group Limited. The primary data will be collected through questionnaire and the questionnaire will developed by using google forms. The secondary data will be collected from web articles, government report, official statistical data portals, social media platforms and company official website.

• Web articles will provide information regarding the perception of the consumers and different users about the company. It will also have valuable data about comparisons with other companies and current trends in the market. The identification of the current market trends is essential for developing effective strategies.
• The New Zealand Government is a website providing detail information about the different regions and the cities in the country(New Zealand Government, 2018). This will assist in gaining information about the demographics of the country.
• Social media platform will facilitate in understanding the needs of the consumers and their opinion about the brand. The identification of the image of the organization among the consumers is essential for understanding the effectiveness of the branding strategies(facebook.com, 2018).
• The New Zealand Data Portal will also provide information about the demographics of the country such as the composition of gender and the population of the country(New Zealand Government, 2018).
• The official website of Fonterra Co-operative Group Limited will provide effective information about the sales of the organization in the past decades and the annual reports can be retrieved to get data about the sales of the products in the past decades, fluctuations in sales volumes and products can categorized using the BCG matrix(fonterra.com, 2018).

In this present study, the study will use the deductive approach for conducting both quantitative and qualitative data research (Sekaran & Bougie, (2016)). This study is a mixed method research where both data will be analysed quantitatively and qualitatively. The research tools used in the study are regression analysis, Quasi Experimental Research and survey.

A survey is conducted to gather quantitative data from a large population sample using a close ended questionnaire. As the study consist of both quantitative and qualitative data analysis, open ended questions will also be used in the survey for gathering both types of data (Moser & Kalton, 2017).). The questionnaire will be developed using the google online forms and will be sent to the consumers through emails. The links of the questionnaire will be provided to the consumers and the participants have been expected to provide suitable response to the given questions. The data collected in the study will be used for conducting inferential statistical analysis consisting of methods such as regression analysis. This data collected will facilitate will evaluated based on the dependent variable and the independent variable chosen for the data set.

The major aim of using the quasi experimental method is prediction and will be used in the study as it provides reliable predictions by comparing two variables. This means that quasi experimental research will not only describe the behavioral patterns but will also predict the causal relationship between the variables (Campbell & Stanley, (2015)). The causal relationship is one of the major aspect of the study and two groups of data will be used to develop the causal relationship between two variables. The comparative analysis among the data set in the study can be analyzed effectively using the quasi experimental method.  The quasi experimental research design will be used in the study for the following analysis:

• The prices of the different products will be compared with the sales volumes of that particular product. This data will be gathered from the annual report of the company to identify the relationship between prices of products and sales volumes.
• The sales volumes will also be compared with the demographic data to evaluate where the demographics of the population affects the purchasing behavior and sales volumes. This data will be gathered from the primary data collected through the online survey.
• The perception of the consumers about the products and brand will be compared with the sales volumes and profit.
• The current trends in the market will be compared with the sales volumes to provide insights on the current needs of the consumers.

Regression analysis is a statistical technique of analyzing the degree and nature pf relationship between the dependent variable and the independent variable.  The independent variable is the explanatory variable in this scenario and aims to explain the characteristics of the dependent variable (Draper & Smith, (2014)). The effectiveness of the regression model depends on the explaining capability of the independent variable about the dependent variable characteristics. The different types of regression analysis methods are linear regression, multiple linear regression and logistics regression.  The equation of a general linear regression is  y_i= mx_i + c+ ?_i (Chatterjee & Hadi, (2015))_.

Methodology

In this equation, y is the dependent variable, x is the independent variable, ? is the error term and i is the observation. The current study will use the regression analysis to identify the relationship between sales volumes and the other variables such as product types, price and location. This will enable to understand the nature and association between the variables. This will enable to develop strategy based on the relationship (Darlington & Hayes, (2016)). The data collected from the online survey will also be subjected to regression analysis where consumer perception about the products will be analyzed with the product preferences. The product choice will also be analyzed with the gender category to check whether choice of product is dependent on gender or not. The study will conduct other regression analyses based on the quality and amount of data gathered.  

The data collection will consist of gathering data by suing the primary data collection method and the secondary data collection method. The secondary collection sources have already been explained in the information sources section. The primary data will be collected by conducting an online survey to all the consumers via email (Palinkas, et al., (2015)). The online survey will consist of quantitative questions and few qualitative questions to develop analysis. The questionnaire will be sent to all the existing consumers of the organization. The questionnaire is designed as such that authentic answered can be obtained and none of the questions are leading.  The different data variables in the questionnaire will be used as dependent and independent variable based on the responses and needs of the research.  Online survey is one of the most effective methods of collecting data for Fonterra Co-operative Group Limited as conducting physical survey takes more amount of time and resources. The respondents are at their ease and can take the survey at their free time.

In this current study, the research will use the simple random sampling method for selecting the population sample. In probabilistic sampling methods, randomization is the basis of selecting the sample population for the research (Nardi, (2018)). The data collected from the primary sources will be randomly selected as it is difficult to analyze data for all the consumer and it is expensive and time consuming. Simple random sampling will randomly select respondents from the collected data so that all respondents have equal opportunity of being selecting and bias in the study can be eliminated. The data collected from online sources will be randomly selected so that reliability and validity of the data can be maintained.

Data Collection

Non-probabilistic sampling method are used for population sample less than 35 and in this study the secondary data will be selected based on the non-probabilistic sampling method. Convenience sampling will be used in the study to select the data from annual reports, web articles, government websites and statistical websites based on their relevance (Etikan, Musa, & Alkassim, 2016).  This will keep the data collected for secondary analysis significant and aligned to the objectives of the study.

• Population Specification Error:  This type of error occurs in cases when the target population for the study is not clear as they consumer purchasing the products are not the one consuming it(Neale & Pomès, 2016). This is quite prevalent in dairy products as the parents may purchase the product but the family members especially the kids are consuming it.  In this current, it has been assumed that the buyer of the products are the consumers using the products.
• Sampling Error: This sampling error occurs when the population size for the study is too small and it does not effectively represent the overall target population. In order to avoid this type of error in the study, a large of sample population has been considered initially and then sampling has been used to randomly select elements from the population to make the data reliable, valid and free from bias(Liu & Minnett, 2016).
• Sample Frame Error: This type of errors occurs when the population sample for the study is wrongly chosen which means that the target population cannot make significant contribution to the study. in order to avoid this type of error, the consumers of Fonterra Co-operative Group Limited have been chosen for the study and the consumers that make frequent purchase has been taken into consideration(Andrle & Crassidis, 2016). This will facilitate in reducing the possibility of occurrence of sampling frame error.
• Selection Error: This error occurs when the participants decide without any prior intimation whether they want to take part in the survey or not.  This error can be providing the consumers with information sheet and consent form(Klausch, Hox, & Schouten, 2015 ). The information sheet will have all the relevant data regarding the purpose of conducting the survey and the consent will make sure that they respondents have taken part on their own and also will facilitate in understanding the respondents that will take part in the survey.

• Estimation Error: This type of error occurs when the actual parameters are not represented aptly by the estimation used in the data analysis(Onatski, 2015). This error can be reduced by including two types of data sets, one from the consumers and another from the producers.
• Response Error: This error occurs when the data is not recorded effectively due to wrong submission or random submissions made by the participants(Kim & Tamborini, 2014). The pretest questionnaire is a method of identifying these types of errors.
• Analysis Error: The analysis error occurs due to the use of inappropriate analysis tool while conducting the analysis(Onatski, 2015). The research analysis section has been well designed and examined to identify the appropriateness of the tool.
• Non-Response Error: This type of error occurs due to the incompletely response from the respondents or blank survey response(Kim & Tamborini, 2014). The online survey is a method of overcoming this error as the questionnaire can only be submitted after all the questions have been addressed.

The pretest questionnaire has been developed for pilot testing. Pilot testing has been conducted to check the validity of the questionnaire. Initially, this questionnaire will be distributed among 10 respondents to check the appropriateness, tone and relevancy of the questions. The questionnaire is used to check both divergent and convergent validity in the study. The question five’s validity is checked by using the question number four and validity of the question number 1 is checked by the question numbered two. This measures the convergent validity of the questionnaire. The question three is used to check the divergent validity of the question number one. This shows that pilot testing is conducted to develop the final survey question as it improves the validity and reliability of the study.

The summary of the data variables is given below which depicts the measurement scale of the variables used in the survey.

References

Andrle, M., & Crassidis, J. L. (2016). Attitude estimation employing common frame error representations. . In AIAA Guidance, Navigation, and Control Conference, (p. 0625).

Campbell, D. T., & Stanley, J. C. ((2015)). Experimental and quasi-experimental designs for research . Ravenio Books.

Chatterjee, S., & Hadi, A. S. ( (2015)). Regression analysis by example. John Wiley & Sons.

Darlington, R. B., & Hayes, A. F. ((2016)). Regression analysis and linear models: Concepts, applications, and implementation. Guilford Publications.

Draper, N. R., & Smith, H. ((2014)). Applied regression analysis (Vol. 326). John Wiley & Sons.

Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1-4.

facebook.com. (2018, 10 09). Fonterra. Retrieved from Facebook: https://www.facebook.com/Fonterra/

fonterra.com. (2018, 10 09). fonterra.com. Retrieved from https://www.fonterra.com/nz/en.html

Kim, C., & Tamborini, C. R. (2014). Response error in earnings: An analysis of the Survey of Income and Program Participation matched with administrative data. Sociological Methods & Research, , 43(1), 39-72.

Klausch, T., Hox, J., & Schouten, B. (2015 ). Selection error in single?and mixed mode surveys of the Dutch general population. Journal of the Royal Statistical Society: Series A (Statistics in Society, 178(4), 945-961.

Liu, Y., & Minnett, P. J. (2016). Sampling errors in satellite-derived infrared sea-surface temperatures. Part I: Global and regional MODIS fields. Remote sensing of environment, 177, 48-64.

LOUISSON, S. (2018, 02 09). Fonterra a failure in concept and in practice. Retrieved from The Standard: https://thestandard.org.nz/fonterra-a-failure-in-concept-and-in-practice/

Moser, C. A., & Kalton, G. (2017).). Survey methods in social investigation. Routledge.

Nardi, P. M. ((2018)). Doing survey research: A guide to quantitative methods. . Routledge.

Neale, C., & Pomès, R. (2016). Sampling errors in free energy simulations of small molecules in lipid bilayers. Biochimica et Biophysica Acta (BBA)-Biomembranes, 1858(10), 2539-2548.

New Zealand Government. (2018, September 1). Population & Society. Retrieved from data.govt.nz: www.data.govt.nz

New Zealand Government. (2018, September 1). Regions-nz. Retrieved from New Zeland Now: www.newzealandnow.govt.nz

Onatski, A. (2015). Asymptotic analysis of the squared estimation error in misspecified factor models. Journal of Econometrics , 186(2), 388-406.

Palinkas, L. A., Horwitz, S. M., Green, C. A., Wisdom, J. P., Duan, N., & Hoagwood, K. ( (2015)). Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. . Administration and Policy in Mental Health and Mental Health Services Research, 42(5), 533-544.

Sekaran , U., & Bougie, R. ((2016)). Research methods for business: A skill building approach. . John Wiley & Sons.

Order an Essay Now & Get These Features For Free:

Turnitin Report

Formatting

Title Page

Citation

Outline

Place an Order