Interpreting Market Trends
Data on various market factors will need to be collected for identification of their effect on demand of vehicles in the Australian market. Those factors are summarized as follows
Disposable income is the level of income that households can spend for their consumer purposes. It is the income after taxation whose level determines the income that consumers have at their disposal. In that respect, it is determined by employment level within an economy.
Purchasing power: Price index/inflation:
Purchasing power refers to the ability that the income held has in buying goods and services. The change in purchasing power determines the quantity of goods that a given amount can afford. Inflation and price index is a crucial determiner of consumers’ purchasing power.
Income distribution
Income distribution refers to the share of an economy’s total disposable income. In that respect, the data is useful in classifying income groups that define customer segments by their income.
Population distribution:
It refers to how the population is distributed across the country. In that respect, it is a crucial aspect of defining population location.
Market reach: Digital media coverage:
Markets reach within a geographic region in determining the ability to reach people with information. Thus, the level of market reach for different communication channels is crucial data for marketers.
Understanding the level of the disposable income within the market is crucial in determining the level of demand that consumers are likely to afford the product. In that respect, high level of disposable income that is reflected by high employment or low unemployment rate would be an indication of potential high demand and vice versa.
Purchasing power: Price index:
An understanding of the market’s purchasing power trend over time would be suitable for marketers in determining the trend for demand. That is because the increase in purchasing power represented by decreasing inflation would have an effect of increasing demand while a reduction in the purchasing power represented by increase in inflation would reflect a possible reduction in demand.
Income distribution:
The data is crucial for identification of the proportion of the segment of the population that the BMW’s premium brands targets. In that respect, identification of the segment’s share of income and its trend is crucial in marketing planning. (Porter, 1980)
Population distribution
Population distribution’s identification is crucial for marketers for the purpose of planning for distribution and promotion activities. In that respect, correct population location identification guides correct distribution channels and promotion channels audience targeting.
Market reach: Digital media coverage:
The level of market reach by various channels is an indication of the share of the market that the company can reach with the channel. In that respect, the data on media coverage on the Australian population would be useful in determining the ability to reach the right market segments.
- Data
The following is the list of the type of data that will be collected considering the various marketing aspects that have been described.
- Employment rate
- Price index
- Income distribution
- Population distribution
- Digital media coverage:
- Source
The different types of data will be sourced through secondary and primary methods described as follows.
- Employment rate, Inflation data can be accessed through secondary data collection method from economic databases including the Trading economics.
- Income distribution and population distribution data will be collected by secondary data collection methods from the government websites including the Australian Bureau of Statistics.
- Digital media coverage information will be collected through primary research where questionnaires will be used to collects data from digital media channels.
- Research method
The data collection and analysis will apply quantitative research method. In that respect, there will be an application of basic mathematics and statistical methods in identifying trends and relationship between the variables and the sale of the BMW vehicles. Thus, use of change rates in the variables and correlation will be used analyse the changes in the past and forecast future trends in the variables and the vehicles sales.
- Research Summary
The research will be undertaken beginning January 2015 to July 2016 and the relevant aspects of costs and timing are summarized on the following chart.
Presenting data using three different presentation techniques appropriate for the data with Justification of the choice of techniques
The following are data presentation techniques with the use of three of the five identified data that will be. The presentation shows inflation, the employment rate and market coverage with the use of charts, graphs and diagrams as follows.
Presentation of the data using a bar chart is suitable for clear identification of the inflation change over time and identification of the trend over time. (McCabe & Moore, 2006)
Use of the line chart to present the rate of unemployment is suitable as it clearly sets out the trend in the rate change over time. (McCabe & Moore, 2006)
Source: Australian Bureau, 2014.
Use of comparative bar chart for the income distribution is suitable as it enhances comparison of the income between the different groups as well as comparison of the group’s income share change over time. (McCabe & Moore, 2006)
Where: X represent the sales of passenger vehicles, and Y represent the Reserve Bank of Australia’s Target Cash Interest Rate.
- Calculating the correlation coefficient between passenger car sales and the RBA’s target cash interest rate.
Correlation coefficients usually range from -1 to +1 with -1 being an indication of a perfectly negative correlation which defines the relationship of variables that moves equally to the opposite direction. On the other hand, the correlation of +1 is perfect correlation with the variables moving equally in the same direction. Finally, correlation of zero means that there is no relationship between the variables under study. For the sales of vehicles and the rate, the correlation coefficient is calculated as follows
Thus, substituting the values in the equation gives a correlation of -0.75 same as the correlation coefficient calculated with excel.
Interpreting the correlation co-efficient
With a correlation coefficient of -0.75, there is an indication of negative correlation between the two variables. In that respect, an increase in the rate results to reduced sales and vice versa. In addition, the size of the correlation being 0.75 is an indication of a strong relationship between the two variables as it is close to one. Thus, it can be said that a change in the rate has a significant effect on the sales in the opposite direction.
- Manually or using spreadsheet/statistical programme:
- Calculating the least square/regression line to the sales figures time series.
Regression lines are the best line of fit that are used for estimating the endogenous variables given the exogenous variables. In that respect, the equation is useful in estimating the level of the dependent variable when the determining variable is known. In that view, estimation of the regression line showing the relationship between the sales and the rate is done as shown below.
Slope represents the amount of change in the endogenous variable with a unit change in the independent variable. On the other hand, the intercept provides the amount of the endogenous variable that does not depend on the independent variable. In this case, the slope shows the change in sales with a unit change in the rate while the intercept shows the sales that do not depend on the rate. (Montgomery, Vining & Peck, 2001)
The regression line has been estimated following the following steps
- Calculating ΣX, ΣY, ΣXY and ΣX2 given a population (n) of 15.
Where:
N = 15
ΣX = 101.75
ΣY = 789964
ΣXY = 5356378
ΣX2 = 692.44
ΣXΣY = 80378837
- Substituting the values
Slope (b) = (NΣXY - (ΣX) (ΣY)) / (NΣX2 - (ΣX) 2)
Slope (b) = (15(5356378)-(101.75) (789964))/ (-(101.75)2)
Slope (b) = -990.1
Intercept (a) = (ΣY - b (ΣX)) / N
Intercept (a) = (789964 -990.1(101.75))/15
Intercept (a) = 59380
- Substituting the slope and intercept in the regression equation
Y = a + By
Y = 59380 – 990.1 X
Sales = 59380 – 990.1*(Rate)
In view of the equation, 59380 of sales are not dependent on the rate, and they would be achieved even if the rate were zero. On the other hand, a unit change in the rate would result to 990.1 changes in sales in the opposite direction. That means that an increase of 1 in the rate would reduce sales by 990.1(Montgomery et al., 2001)
- Using the trend line to forecast sales for the next three months.
Using the estimated regression line, the passenger vehicles sales for the next three months of 2008 are forecasted by substituting the rate in the equation as follows.
Y[t] = + 59380.2 -990.06X[t] + e[t]
Sales = 59380 – 990.1*(Rate)
August:
Sales = 59380 – 990.1*(7.25)
Sales = 52201.98
September:
Sales = 59380 – 990.1*(7)
Sales = 52449.5
October:
Sales = 59380 – 990.1*(6)
Sales = 53439.6
In view of the forecasting, it is clear that the decrease in the cash rate over the next three months considered in forecasting will result to an increase in sales as indicated by the increasing forecasted sales.
Data Interpretation and Recommendations Report
BMW Dealership in Australia
Executive Summary
In a bid to enhance marketing decision making, correct market information and interpretation is essential to marketers. In that respect, marketing research focusing of relevant market aspects is crucial. In that respect, the need for BMW to enhance its marketing of its Australian Dealership brands should be met through a comprehensive market research. That involves identification of the relationship between various market factors and the sale of vehicles in the market. In addition, identification of those factors trends is crucial for marketing decision making involving product positioning, pricing, distribution and promotion. (Porter, 1980)
In that view, a market research is proposed to analyze the effects unemployment. Inflation, income distribution, media coverage and population distribution on vehicles sales and possible future effects. Thus, the study will have an objective of identifying the factors relationship with vehicles sales hence the ability to forecast sales given the factors trends. In that view, quantitative analysis will be applied with basic math and regression analysis being applied. Further, the analysis will involve the use of both primary and secondary data collection on the variables. That will involve secondary data collection method for inflation, unemployment, and income as well as population distribution while media coverage data will be collected through primary method of questionnaire.
Further, the market research is scheduled to begin in January 2015 with activities involving recruitment of research personnel, training, data collection, data analysis, results review and implementation. Finally, recommendations are made for enhancing the study’s effectiveness through cost management, recruitment of qualified personnel, suitable data representation and relevance to the dealership marketing.
- Introduction
Market research is crucial for those involved in planning and implementing marketing strategies. That is because the identification of market trends and variables relationships helps in formulating strategies suitable for the market situation and the forecasted future. In addition, marketing decisions made on the basis of correct market analysis have a beer chance of success than strategies based on incorrect or no market research. In that view, this report represents a proposal for a market research for BMW dealership in Australia outlining the necessary research and datasets as well as their relevance. In addition, the report contains the explanation of the link between the data analysis and marketing decisions. Finally, the schedule is provided proposing the timeframe and estimating possible costs of a market study of the BMW brand in Australia.
- Research objective
The research will be seeking to identify the relationship between market variables and demand/sales of vehicles in the Australia market. In that respect, the analysis will involve identifying relationships between variables and their strength. That will be used as a guide for suitable marketing mix for BMW brand in Australia. (Sengupta, 2005)
- Research method
Data collection
The study will apply two different data collection methods. That will include primary and secondary data collection. In that respect, the primary method will entail reliance on published information on the markets and relevant variables including the Australian Bureau of Statistics database. On the other hand, primary sources will involve methods like questionnaires to the market seeking to identify customers’ aspects such as level of disposable income and digital media coverage. (Moore, 2007)
Data analysis
In data analysis, the study will apply quantitative analysis of the market data. That will involve the application of regression analysis and basic arithmetic that will be suitable in identifying the relationship between market variables and sales performance as well as identifying the market trend. The data and analysis results will be presented in graphical form for the purpose of easier identification of the trends and relationships. That will be useful for marketing planning as trends will help the planners in forecasting future market demand and variables change. (Makridakis & Wheelwright, 2008)
- Relevance to marketing
In respect to the data sets and their information’s relevance to marketing decision making, the following is a summary of the use that the marketers can put the analysis to enhance the dealership’s sales performance. That owes to the ability to position the brand through suitable marketing mix of product, pricing, distribution and promotion guided by the market nature and trends. That covers the already analyzed data and the proposed data analysis.
- Cash rate
Cash rate determines the cost of borrowing in the market. In that respect, its effect on sales could be through effect of funds availability to consumers. In that view, the nature of the relationship between the cash rate and the vehicles sales is useful in establishing the expected sales trend with the rate change. That can be demonstrated by the regression analysis done on the rate and the sales for the year 2007 and 2008. The analysis has provided a regression equation Sales = 59380 – 990.1*(Rate). The equation’s interpretation is that 59380 of the vehicles sales is independent of the cash rate and is explained by other factors. In addition, the slope value of -990.1 indicates that a unit change in the rate would result to sales decrease by 990.1. Thus, marketers can use the information to adjust pricing efficiently to feature the forecasted change in the rate. That could involve lowering prices when the rate is high to cater for the increased cost of borrowing. (Montgomery, Vining & Peck, 2001)
- Inflation
Analysis of inflation rate trend in the market will help in identifying the trend in consumers’ purchasing power. That will be useful to markets for pricing purpose to address different levels of purchasing power over different periods. That can be addressed through price-based promotion programs like discounts.
- Employment
Employment level analysis will be suitable in identifying the level and trend of disposable income in the market because it affects demand. Thus, establishing the trend will help marketers forecast future sales trend. That will be useful in managing the vehicles distribution in a bid to ensure that the right distribution quantity is made to cater for market demand without unnecessary oversupply or under-stocking of BMW vehicles in Australia.
- Media coverage
An analysis of the media channels reaches the market is suitable as it provides information on the suitability of a channels ability to reach the right target segment. In addition, identifying the number of market reach is useful in establishing suitable promotion strategies with more efficient marketing communication strategies. (Fill, 2011)
- Population distribution
The analysis on population distribution will be useful in identifying the geographical locations that the marketing activities like advertising should target. In that respect, the highly populated areas forms better target than the less populated regions. In addition, the population distribution will determine the regions that the business should focus its distribution channels.
- Income distribution
Income distribution identification and related trend will be useful for the business in the identification of the level of income that the high-income segment has and the trend in that income share. Thus, the identification will help in establishing whether the market has a significant high-income class that can sustain the BMW’s premium priced brands. (Sengupta, 2005)
- Conclusions and recommendations
It is clear that correct market information is necessary for effective marketing planning. In that respect, data analysis of various factors that have potential to affect the market demand for BMW’s premium brands needs to be analyzed. In addition, the analysis needs to be correct to present the correct information. That involves use of correct analysis models. In that view, the recommendations for enhancing the market research are summarized as follows
Data relevance:
The research should focus on the listed data sets that narrow down the market factors to the most relevance variables. In addition, there should be use of credible sources as well as representative samples.
Analysis efficiency:
Data collection should be done by qualified personnel for purpose of collection of right information. In addition, qualified personnel will be useful in enhancing data analysis and results presentation.
Marketing decision making:
In view of the research results, marketers should make decisions that seek to address those factors in a manner that increases potential for buying the company’s premium brands. That needs suitable mix of pricing, product positioning, distribution and promotion.
List of talking notes
The report presents a proposal of market research on key aspects that are relevant to BMW’s Australian dealership marketing.
Thus, the research will involve the analysis of the relationship between vehicles sales and factors including inflation, unemployment, income distribution, population distribution and media coverage. Those factors have been identified as crucial in determining the marketing mix strategies that a business should apply to attract and retain customers.
That will be through identification of the factors that have the greatest effect on sales as well as their trends that will act as a guide for demand forecasting. With the trend analysis, the marketing teams can make decisions on the marketing that suits the market factors and trends to enhance sales.
In that view, the market research will apply quantitative analysis including regression and correlation analysis that will be used to identify the relationship between factors and the strength of that relationship. In addition, there will be use of different data and results presentation methods for precise identification of relationships and trends.
In respect to the study schedule, the market research is proposed to begin in January 2015 extending to September 2015. Then, the research findings will have been reviewed, and the suitable marketing mix put in place for implementation.
Reference list
Australian Bureau of Statistics. 2012. Household Income and Income Distribution. [Online]
Available at<http://www.ausstats.abs.gov.au/ausstats/subscriber.nsf/0/B0530ECF7A48B909CA257BC80016E4D3/$File/65230_2011-12.pdf> [Accessed 17 October 2014]
Fill, C., 2011. Essentials of Marketing Communications. New Jersey: Prentice Hall. Makridakis, S. & Wheelwright, S., 2008. Forecasting Methods and applications. 3rd Ed.
New Delhi: Wiley India Pvt. Ltd.
McCabe, G. & Moore, D. 2006. Introduction to the Practice of Statistics. 5th ed. New York,
New York: Freeman and Company.
Montgomery, D., Vining, G. & Peck, E. 2001. Introduction to Linear Regression
Analysis. 3rd Ed. New York: John Wiley & Sons.
Moore, D., 2007. The Basic Practice of Statistics. 4th ed. New York: Freeman and Company.
Porter, M., 1980. Competitive strategy: Techniques for analyzing industry and
competitors. New York: Free press.
RBA. 2014. Cash Rate Target. [Online] Available at
<http://www.rba.gov.au/statistics/cash-rate/> [Accessed 17 October 2014]
Sengupta, S., 2005. Brand Positioning: Strategies for competitive advantage.
Lake Town: Tata McGraw-Hill Publishers.
Trading Economics. 2014a. Australian Unemployment. [Online] Available at
<http://www.tradingeconomics.com/australia/unemployment-rate> [Accessed 17 October 2014]
Trading Economics. 2014b. Australian Inflation. [Online] Available at
<http://www.tradingeconomics.com/australia/inflation-cpi> [Accessed 17 October 2014]
