Market Analysis : Market Basket Analysis

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Market Basket Analysis
Market Basket Analysis, also known as affinity analysis, is a technique to identify items likely to be purchased together. Market basket analysis is only one of the various possible functions that data mining tools can perform. This type of analysis connects to the findings of the retail sales data to allow the user to draw conclusions as to the relations between the products that are irrelevant at the first sight. Implementations of such decisions can lead to a major rise in sales and profits for the retailers. This can be done, for example by laying four products that are related in the nearly-located aisles, or by putting special offers for, let us say, soap on then packs of diapers. For instance, if you are in an
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A classic example is toothpaste and tuna. It seems that people who eat tuna are more prone to brush their teeth right after finishing their meal. (Market Basket Analysis, n.d.) Market basket analysis is a product of data mining. The indication for it is confined in the very definitions of each term. Data mining is process of efficient discovery of not observable valuable patterns from a large gathering of data, whereas market basket analysis is focused at discovering the if this then that relationships, which associate events in a database. For example the association between purchased items at a supermarket.
Association rules of the market basket analysis are closely related with overall correlation rules. Correlation is a beneficial tool for concluding if bonds exist between securities. A correlation coefficient is the outcome of the exact comparison of how tightly related two variables are. The connection between two variables is said to be very correlated if a movement in one variable develops or takes place at a similar time as the same movement in another variable. There can be clearly seen that association rules are based on analyzing how one product is sold in relation to the other. The aim of market basket analysis is to show that whenever A occurs, B also tends to occur: A > B. (Market basket analysis: identifying products and content that go well together, 2012)
A beneficial feature of correlation analysis is the possibility to foresee the movement in one
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