Data Mining & Analysis in Decision Making
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Date
2019
Authors
Nassar, Adham
Quzmar, Yaqop
Aker, Mohammed
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Abstract
The main purpose of this project is to solve some issues that the supermarket face, the Returns rate for an example, where we've learnt the pattern and the behavior of the customers and then predict which customer is likely to return their order and what product they may return using RapidMiner.
Another main goal is to establish a method to understand the customer needs, wants and behavior in order to build a recommendation system for the Superstore top management, using RFM technique which gave us the possibility to apply a segmentation on the customers and then come up with business decisions each related and focused to every segment to make sure the current customer is satisfied and the potential customer is motivated enough to stick around and of course make specific arrangements for each segment, for example give motivational gifts for the Champion customer to make sure they will keep their current behavior.
In addition, we've used market basket analysis technique to discover hidden patterns from the customers, like what product goes with other product and what type of products is the most likely to be bought from a specific customers' segment.
Finally, in order to provide all the important data to the top management, we've used Tableau dash boarding program where we displayed the data in charts and reports so it will be easier for the decision makers to see all the differences that could happen once any change may occur on any field.
Not to forget, that before doing any analysis, we've applied a series of preoperational steps on the acquired data, from cleaning, integration, transformation, reduction and discretization data.
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Keywords
Data,Mining,Analysis,Decision,Decisions Making,RFM,Decision tree,Automation,Association