#MarketBasketanalysis #AprioriAlgorithm This playlist/video has been uploaded for educational purpose and contains selective data and analytical information.
The aim of this video is to show a little example to motivate the attendee based on the standard market basket analysis.
• Load and parse transaction data
• Calculate measures on the data
• Generate and inspect association rules
MBA and Apriori Algorithm can be used to drive business decision making by using the association results. There are a number of ways in which MBA can be used:
#Associated Aisles should be placed together on the web application platform to boost the sales and reduce the time spent in finding that Aisle. For instance, cereal, lunch meat, and Bread Aisle should be placed together, as they are highly associated.( you can generate this rule by using aisle names in transaction data-set instead of product names while preparing data for Apriori Algorithm)
Associated products such as Organic Cilantro and limes should be put close to one another, to improve the customer shopping experience and improving the store layout.Marketing can take benefit from this association relationship, for example, target customers who buy Organic Cilantro with offers of Lime, to encourage them to spend more on their shopping basket.
List of rules can be used to put recommendations on the product pages and at product cart pages.Those rules that are applicable to each product with the high lift where the product recommended has a high margin should be considered.It can drive the significant uplift in profit.
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