abstract: This reports investigates the general day to day problems faced by small businesses, particularly small vendors, in areas of marketing and general management. Due to lack of man power, internet availability and properly documented data, small business cannot optimize their business. The aim of the research is to address and find a solution to these problems faced, in the form of a tool which utilizes data science. The tool will have features which will aid the vendor to mine their data which they record themselves and find useful information which will benefit their businesses. Since there is lack of properly documented data, One Class Classification using Support Vector Machine (SVM) is used to build a classifying model that can return positive values for audience that is likely to respond to a marketing strategy. Market basket analysis is used to choose products from the inventory in a way that patterns are found amongst them and therefore there is a higher chance of a marketing strategy to attract audience. Also, higher selling products can be used to the vendors' advantage and lesser selling products can be paired with them to have an overall profit to the business. The tool, as envisioned, meets all the requirements that it was set out to have and can be used as a stand alone application to bring the power of data mining into the hands of a small vendor. / Dissertation/Thesis / Masters Thesis Engineering 2016
| Identifer | oai:union.ndltd.org:asu.edu/item:38687 |
| Date | January 2016 |
| Contributors | Sharma, Aveesha (Author), Ghazarian, Arbi (Advisor), Gaffar, Ashraf (Committee member), Bansal, Srividya (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Masters Thesis |
| Format | 52 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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