Correlation Between Sales And Brand Value Marketing Essay

In the marketing concept, brand differentiates a product and services from its competitors. Brand affects consumers not only because of the knowledge systems that consumers know about the brands but it is also part of psycho-social-cultural context (Esch et al., 2006). Hence, it is very important to build a strong brand as it act as one of the contributing factor in sustaining company’s performance of which the value of a company relies on its current earnings that potentially will develop its future financial performance. For instance, the powerful global companies take advantage on its brand as a contribution factor to their continuing success (Davis, 2002).

Brand is classified as an important asset to the company as it helps in the generation of cash. Moreover, it has an impact to the company as the business is worth more due to its position of the brand in the market. The value of the brand is a reflection of the brand worth in regards to current and future income, reputation and market value. It is vital to understand the meaning of the brand value as it serves as a tool in determining the marketing strategy in each segment or target market. According to Gabay et al. (2009), brand value is related on how a brand is influence in the marketing mix as well as the impact of the brand name to the other features in the marketing concept. When a brand is managed well consistently, the brand value will appreciate over time that allows company to charge a premium over competitive offering leadings to a higher profit margin (Davis, 2002).

A company’s brand is directly related to the consumers as they are the one who decides on the purchase of a product. Brands that manage to segment its products appropriately in the competitive market will enable the company to attract consumers as well as maintaining the brand value that stands as a key point to compete in the future market. Each company would want to have a stable growth in its profitability and the key point to determine the success of the company will rely on its sales figures. As companies noticed the importance of a brand in its financial performance, huge investment has been made to ensure that its brand has a high brand value. For example, Coca-Cola is consistently investing in its brand to develop an emotional connection with the consumers.

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Consumer’s perceptions on a brand do play an important factor in the selection of the best brand for a particular product. It is important to build and have a brand value as it involve consumers’ understanding on what they are getting compared to what they are giving. There is a linkage between consumer loyalty and brand value. For example, if a particular brand maintains a significantly higher perception of value to a consumer than any other brand in the category, that consumer will consistently purchase that brand and consistently recommend that brand to others. As a result, consumers are confident in the product and directly will have an impact to the company’s sales performance.

According to the top 100 grocery brands in the United Kingdom (UK) report, it was noted that the sales pattern is related to consumer’s perception on the brands. Brands that have a high brand value have performed well in terms of its sales. Therefore, it seems that there is a relationship between sales and brand value. However, there is still uncertainty on the strength between the two variables. In view of this, it is viable to do a statistical analysis for further analysis on the said matter.

1.2 Previous work that has been done

Brand is seen as a very important concept in the marketing perspective especially brand value which have a relationship between quality and price. High brand value is the most valuable asset for a company as it brings higher margins both short and long term (Esch et al., 2006) and host of other benefits (Oslon, 2008). By identifying the factors driving the brand values, it allows company to increase its brand’s performance which will result to an increase in revenue, larger market share and higher profits. Wood (2000) indicates that by using brand value as a performance measure, it creates a long term focus of the company.

Research findings indicate that consumer buying behaviour is based on perception on a brand name (Gabay et al., 2009). Therefore, brand is seen as a contract with the consumers that reduce uncertainty which allows consumers to purchase uncertainty reduction or trust that leads to the increase of value (www.sdrnet.com,2010). Meanwhile according to Oslon (2008), brand creates value by generating demand and reducing risk through securing future earnings for the business which will result to creation of value for companies to its brands.

Penrose and Moorhouse (1989) suggest that one important factor determining the value of the brand is its profitability. By knowing the brand value, it allows the company on how is the brand performing in the market. It is related to the element of acceptability and the strength of the brand as it is link to the consumer’s decision in buying a product. Blackett (1991) comment that there is a relationship between a brand’s strength and its ability to command future income. Therefore, the stronger the brand, company would be able to predict its future income conversely the weaker the brand, the less certain is its future. This indicates that the brand value will provide a company a clear idea of profitability from its various brands. A research was done against the most expensive leading global products and the findings indicate that each brand invest time and energy to manage its brand accordingly (Gabay et al., 2009). This shows an indication on how companies foresee the importance of brand value.

With a good brand, consumers will be prepared to pay a premium for the products and leads to a brand loyalty which will have value if the brand was ever sold. Research conducted earlier has found a relationship between sales and brand value (Gabay et al., 2009). Moreover, one of the factors determining the brand value is the strong brand acceptance in the market which is dependent on consumers. Research indicates that brand has the power to attract consumers and provide a guarantee of sales through premium price that provide a higher margin from the sale of the products (Blackett, 1991).

Another research has found that there is strong correlation between strong brand value and its benefits of pricing, customer loyalty, market leadership and overall financial performance (Leiser, 2004). Moreover, Leiser (2004) and Davis (2002) also point out that there is relationship between customer loyalty with brand value and profitability as findings from a research indicate that 5% increase in customer loyalty could elevate profits by as much as 100%. Meanwhile, based on a study conducted in the hotel industry, it suggest a positive correlation between brand value and a firm’s performance in terms of profits and long-term cashflows (Kim, Kim and An, 2003).

Based on the above, it can be summarise that there is relationship between brand and financial performance.

1.3 What would expect to discover

For a product to be successful, it must have a good brand name. Once this has been establish in the market, it creates a powerful and lasting connection between consumers that leads to a positive effect of the product and simultaneously has an effect to the company’s sales performance. Sales figure meanwhile definitely have several attributes to the company such as gaining market share and acceptability in the market. As a result of a positive trend in the sales figures, it helps the company to build its brand value in the market. Brands with high values are related to strong market share as it allows the company to bargain more effectively in terms of pricing and quality. Moreover, with the high market share, the brands have an advantage in economy of scales that leads to high sales figures.

However in the year 2008, a number of discounted retailers entered the UK grocery market with their home brand at a low cost price. With the effect from the economic crisis, consumer’s buying trend has slightly shifted from high value brands to home brands which have low brand values. Although the current economy condition does have an impact across the sector, especially in the growth of own-label products, premium brands have still continue to perform well. From this report, it would like to see the relationship between sales and brand values as it is interrelated wherein with high brand value; the product has a control in the market and will lead to better sales in the future.

2.0 Description of data

For the purpose of this report, the dependent and independent variables are sales and brand value respectively. Details of the data are attached in Appendix 1. The data is based on the top 100 grocery brands in the United Kingdom (UK) for the year 2008. However, for the purpose of this report, only top 78 grocery brands are used as the sample size due to lack of information of certain brands. The histograms for each variable are given in figure 1 and 2 respectively. The histogram for sales and brand value indicate that the most recorded value is £168.7 million and £174.07 million respectively. Meanwhile, the mean values are £162 million and £152.04 million for sales and brand value respectively. Based on the median for sale of £162 million, the 95% confidence interval is between £135 million to £188 million while brand value is between £121 million and £184 million. It was noted that the distribution for both variables are positively skewed of which the long tail in on the right.

Figure 1: Histogram for sales

Figure 2: Histogram for brand value

Figure 3: Normal distribution for sales

The inference about the population mean is based on the following computation:

95% confidence interval = 162 ± (1.96 x 127)

= (-86.92 to 410.92)

Therefore, it believes that the population mean lies between -£86.92 million and 410.92 million. There is a 95% chance that this is true.

2.1 Source of data

The brand value data was extracted from the report titled ‘The UK’s most valuable grocery brand 2008’ prepared by www.intangible bussines.com. Meanwhile, the data for the sales value was obtained from the market research company, The Nielsen Company (2008) of which the data was recorded via checkout scanners at all major grocery chains totalling about 74,000 in the UK.

The calculation of the brand value is computed based on its forecast sales, royalty and discount rate.

Brand value

Components:

Sum of future royalty income

Testing and benchmarking

Discounted

Components:

Risk analysis

Tax deduction

Royalty rate

Components

Brand strength

Royalty rate range

Future sales

Components:

Historical sales

Adjusted Compound Annual Growth Rate (CAGR)

X , =

Source: The top 100 grocery brands in the UK

The future sale is based on the adjusted Compound Annual Growth Rate (CAGR) to reflect the brand’s long term ability for growth. The royalty rate is based on scoring of measurements i.e. preference, relevancy, heritage, perception and awareness that resulted to the brand strength for each brand. Meanwhile, discounted rate is computed by multiplying the royalty rate and reduced at the relevant tax rate. The discount rate reflects the time value and risk assessment based on 9% with the basis of the brands existence in a stable economic environment. Finally, results are tested and verified by to ensure the correct figures are used for the ranking purposes to avoid biasness.

3.0 Analysis

3.1 Scattergram and Correlation

Before proceeding with the correlation between the two variables i.e. sales and brand value, a scattergram was applied to explore the relationship between the said variables. Scattergram is used as a preliminary step in investigating the existence of a relationship between two variables. In figure 4, the variables indicate a linear positive relationship which is suitable for the correlation analysis. Based on the said scattergram, it was observed that there are two values which are higher than the other values. After checking the values, it was discovered that the said variables have a very high value in sales compared to other brands. The main reason is because the two brands have a strong brand identity in the global market and is one of most respected brands in the market. Moreover, the small sample size might contribute to the finding of a number of outlying residuals. In considering the outliers, it was decided to maintain the variables as it does not have much impact to the r value if the same are removed.

r= 0.948

Figure 4: Scattergrams and value of r

In order to provide a precise measurement of the degree of correlation, the correlation coefficient is used to produce a mathematical measurement (Cohen and Holliday, 1996:80). The correlation analysis is applied to check the quantifiable relationship between two variables in terms of both the strength and direction. Based on figure 4 above, there is a large correlation i.e.0.95 between the two variables (above 0.5) which indicate a quite strong relationship between sales and brand value. Therefore, this result is interpreted in the manner that the amount of sale directly affects the brand value wherein the more sales take place, the higher the brand value. In order to decide the amount of association between the two variables justifies the sales to brand value, hypothesis testing is conducted.

Null hypothesis Ho: p= 0, there is no association between sales and brand value.

Alternative hypothesis H1=p≠0. There is an association between sales and brand value.

Critical value: 5% (87-2) = 0.183

Test statistics = 0.948

The test statistics exceeds the critical value and therefore to reject the null hypothesis and conclude that there is significant association between sales and brand value.

Inference about the population value of the correlation coefficient based on the sample is calculated using the FISHER function in EXCEL which is as follows:

w= FISHER (0.95) = 1.83 (the mean for the normal distribution)

the standard deviation is 1/ = 0.11

The 95% confidence interval for w is 1.83 ± (1.96 x 0.11) = 1.62 to 2.05

By using the FISHERINV formula in Excel, the 95% confidence interval for the population correlation is from 0.92 to 0.97. The narrow confidence interval indicates that adequate sample size is used for the correlation and the variables have a reasonable control in detecting the estimate of the effect.

3.2 Regression analysis

Regression analysis is a technique used in analysing variables which focus on the relationship between dependent variable and independent variables. It will assist in understanding how a change in the value of the dependant variable has a direct effect to the independent variables. Clearly, the said analysis could be used to infer causal relationship between independent and dependant variables.

Regression Statistics

Multiple R

0.948091

R Square

0.898876

Adjusted R Square

0.897687

Standard Error

40.49166

Observations

87

Figure 5: Regression model and statistics

A simple linear regression was performed on the 87 sample size to determine if there is a significant relationship between sales and brand value. Based on the regression statistic in figure 5, the Multiple R value is 0.95 and the R square is 0.89 or 89% which both indicate a liner model wherein the two predictors fits the data well and the confidence interval for the slope is wholly positive. R2 tells that 89% of the variation in the sales in associated with variations in the brand value.

ANOVA

df

SS

MS

F

Significance F

Regression

1

1238788

1238788

755.5547

4.62162E-44

Residual

85

139363.8

1639.575

Total

86

1378152

Coefficients

Standard Error

t Stat

P-value

Lower 95%

Upper 95%

Intercept

38.81685

6.231001

6.229634

1.72E-08

26.42795

51.20575

Brand value

0.806217

0.02933

27.48735

4.62E-44

0.747901

0.864534

Figure 6:Regression statistic summary output

With reference to figure 6 above, the intercept is given as 38.816 and the coefficient of brand value is 0.806. From this figures, the regression equation is constructed as y=38.817 + 0.806x. A significance relationship indicates that an increase in sales will have an effect to the brand value to increase between 0.75 to 0.86.

The significance of the coefficients is indicated by the p-values. In figure 6, the p-value for brand value is 4.62E-44 (very small value), indicating that this variable in the population is very unlikely to be zero as the smaller the p-value, the greater significance it has. Based on the ANOVA results, the figure headed Significance F could also be used to assess the overall strength of the linear regression equation. From the regression statistic output, the value for the Significance F is 4.62162E-44 (very small value), so it can be concluded that there is a highly significant linear relationship between sales and brand value.

Overall, it appears that there is a strong relationship between sales and brand value and the equation could reasonably be used to obtain predictions for sales in other brands given information about brand value. Based on the analysis above, it was noted that there is significance positive correlation between sales and brand value.

It is recognised that there are four different reasons for the relationship to exist:

sales indeed cause brand value. If sales increase certainly the reason is because consumers purchase more on the brand which leads to a good brand name and image. Thus, it increases the brand value.

however, the results might be just a chance as it is based on sampling. If more observations and sample of the population are correctly and repeatedly done, there is tendency for the correlation becomes very unlikely (the more the test is conducted, the less likely that the results occur by chance).

there may be some other factor which was not taken into consideration which produces the variation between sales and brand value and which might be the real cause of the correlation.

there might be a causal connection that represents the effect of the correlation but might have put it in the other way round. It can be concluded from the high correlation between sales and brand value based on consumer’s purchasing power which causes the increase in sales. However, it might be the case that sales are caused by something else such as current economic condition and lifestyle.

4.0 Conclusion

Prior to discussing the findings in detail and highlighting its contribution to the current literature and marketing practices, it is essential to provide an overview of this report and summing-up the findings. In summary the aim of the report is to test the relationship between sales and brand value. Based on the analysis conducted above in section 3.0, it is noted that sales have a positive effect on brand value. There is a strong relationship between sales and brand value. This is supported from the finding of Kim, Kim and An (2003) which indicate a positive correlation between brand value and a firm’s performance in terms of profits and long-term cashflows.

Both variables complement each other to ensure the profitability of the company. Brand has always been an important identification in differentiating its products with its customers. Indeed brands with high brand value have established its existence in the market by anchoring a large sum of market share. Moreover, companies have identified the importance of the brand value and several steps have been taken up to ensure that the company will continue to perform better in its financial performance.

Customer’s perception on a brand is related to the brand value computation as it contributes in terms of loyalty. If consumers are happy and satisfied with the product, eventually it built loyalty by consumer to the product itself. Clear example is the Coca-Cola brand, which is a global brand that is accepted by most of the consumers and this has lead to the contribution to the high brand value. It was reported that the sales of Coca-Cola has increased tremendously as it has manage to build a good brand image among its target market as well as a good positioning in the usage in sports and family gathering (www.businessihub.com). This is consistent with Leiser (2004) and Davis (2002) findings which indicate that 5% increase in customer loyalty will elevate profits of the company to the extent of 100%.

According to Blackett (1991), there is a relationship between a brand’s strength and its ability to command future income. Based on the analysis conducted, the strong relationship between sales and brand value indicates the contribution in the aspect of company’s financial performance. Therefore, companies is required to provide a wealth of information in regards to its brand value which as a result will enhance and improve both in terms of brand’s name and business performance. Based on the findings, companies should stimulate sales by means of promotion and advertisement. Current business environment is characterized by stiff competition and in order to survive a company has to have a well planned strategy to compete in the market.

However based on the result obtained, it is not sufficient to focus only on these two variables to determine the company’s performance especially when brands are supposed to last forever (Esch et al., 2006). For the long term prospect of the brand value, other variables such as brand trust and satisfaction do act as factors driving to consumer buying behavior. Therefore, continuous analyzing different indicators that have an impact to the business in some way can assist companies to interpret the result and make corresponding decision.

Despite the above observation, it is hoped that the findings of the analysis could create greater interest in the subject and hopefully engender further in dept analysis which could contribute further understanding to the readers.

5.0 Reflection

The analysis done through correlation and regression is able to assist company to engage into forecasting. For instance, a company introduces a new brand in the market and within the next few months its sales has increase tremendously as well as the income. By undertaking further research on how to sustain its sales, the correlation and regression analysis will assists in building up a model that can help the company to forecast its future income. Indeed, correlation is an important tool of statistics which can be used in the business decision making.

It is vital to gasp the point of the correlation as even though there is strong correlation, it does not provide an immediate conclusion on the causation as it could indicate a relationship that is based on cause and effect (Taylor, 2007). For this particular example, a high correlation was seen between sales and brand value and some prediction could be made based on the factors such market share but it should be aware that the correlation itself has no proof of these assertions. As a result, correlation could not be solely used as a proof of causation. Some other statistical test should be used to support the result of the correlation. For example, if sales caused brand value, then it seen that there is correlation between the two variables as any changes in sales will cause changes in brand value. The reverse, it is not necessarily true because if sales and brand value is correlated, it could not automatically assume that sales is the cause of brand value.

Linear regression using one independent variable i.e. brand value might not reflect the accurate result of the prediction for dependent variable i.e. sales. Therefore, multiple linear regressions with the use of additional independent variables could help better in explaining or predicting the dependent variables. In addition to this, the sample size used in this study only represents part of the entire population that could lead to bias and generalisbility (Saunders et al., 2007). Therefore the outcome obtained from the study may not reflect the whole population as whole and further analysis of the general population would be of value. Analysis of the population of other brands from different industry can be done to confirm, compare and expand on the results obtained earlier.