Question

What is Correlation Analysis, give an example of how it can be used in marketing. Cite and reference any sources.

Answer 1

Correlation analysis

The method of statistical evaluation used to know the strength of a relationship between two variables is called as Correlation analysis. Using Correlation analysis, the degree and direction of linear relationship of two given variables of interest can be measured.

Uses in Marketing

One of the methods of Correlation is sales forecasting. It is essential for marketers to know the predictable relationship between sales and factors such as advertising, weather, consumer income etc. In the domain of marketing finding out the most interesting correlations among different items or variables is very essential to solving many marketing problems. For example, recommending the kind of items based on the purchases made by customers, arranging the store shelf to boost sales, segmenting the social networks into different advertising communities for successful marketing campaigns, targeting the sort of individuals in order boost sales, etc.

Correlation is normally measured with the help of a scatter diagram, on which data points are plotted. E.g., it is possible to ascertain on a data point the number of customer inquiries that are generated per month (x-axis) against the total amount spent on advertising (y-axis).

Use Cases of Correlation Analysis

The essence of correlation analysis is to define dependent correlation points that make sense in the target market.

Correlation between Social Media and Website Visits: Digital publishers would like to enhance their understanding of the possible relationship between social media activity and website visits. For example, the digital publisher finds the correlation report between daily Twitter mentions and visits for a 2 week period. The correlation is found to be r = 0.27, which means a medium, positive relationship between Twitter mentions and visits to their website.

Optimization for E-retailers: The target of E-retailers is in driving increased revenues. For example, an e-retailer would like to compare monthly web revenue with a number of secondary success events like internal search click-throughs, file downloads, product detail page views, etc. They can easily identify internal search click-throughs as having the highest correlation (r = 0.45), which may point out a region for optimization.