Shivanand R Koppalkar BIAM 530 Week 7 Lowes BI and Data Mining Assignment

Topics: Credit card, Lowe's Pages: 9 (2088 words) Published: September 8, 2015


Shivanand R Koppalkar
Week 7 Assignment – Lowes – BI and Data Mining
Keller Graduate School of Management of Devry University
BIAM 530 – Developing and Managing Databases for Business Intelligence Dr. Darlene Gail Ringhand
21st June 2015

Table of Contents
Introduction3
References9

Introduction
MyLowes is a loyalty card offered by Lowe’s, the second largest home improvement retailer in the world. This card tracks historical transactions, aids in managing home improvement projects, and manages wish lists for future projects. This is not a revolutionary idea most retail stores now offer rewards programs associated with membership cards to better understand loyal customers and encourage spending through unique savings offers. Fred Meyer and Safeway each have well known rewards memberships where you swipe your card at the register and receive discounts at the fuel pump. They have even gone as far as including clipping free coupons where you go online and load additional manufacture coupons to your card for ease of use at the register. MyLowes loyalty card has many advantages and disadvantages for customers in the type of data it collects. The major advantages come from the offers and rewards that can be given when Lowes can look into wish lists and determine what items will yield the highest return by volume sales. The types of projects being managed can also be key to determining how and which departments to expand within the store. According to a press release from Lowe’s Companies regarding the new MyLowes loyalty card, “it will revolutionize the customer experience with home improvement, allowing all purchases, in-store and online, to be tracked automatically and stored on their customer profile online” (Lowe’s Companies 2014). By understanding your customer and the needs through usable data can turn into usable information for business decisions and maximize shareholders profits. Another major advantage for customers using the MyLowes loyalty card is the tracking of purchased items. This tracking allows for returns without receipts because the company is tracking the data necessarily for returns. It offers less worry for customers and can improve customer loyalty to purchase a possibly more expensive product than competitors if customer service is improved and ease of returns if necessary. Another aspect offered is the access to warranties of purchased items and user manuals online for easy access. Any type of competitive edge is worth publicizing. And according to the SWOT analysis “MyLowe’s will enable our customers to track and manage their homes all in one place, and it will allow Lowe’s employees to be better equipped to help meet the needs of our customers” (Lowes Companies 2014). This is the major advantage and push for most loyalty memberships which track all purchases and then can be segregated or grouped into location, type of housing, and anticipate the future needs of its customers. MyLowes loyalty card also has disadvantages for customers since it pulls personal information. As we have seen security issues with Lowes competitor Home Depot. Security is on the minds of the consumers with debit and credit card information being compromised at Home Depot as well as the Target security breach. The further information Lowes requests for loyalty membership will deter customers from joining. Data must be protected to keep customer trust and maintain its place in the industry. One article from Businessweek argues that while “Companies measure customer commitment by their transactions… that often has little to do with how people genuinely feel about the business” (McKee 2007). While the data collected from the MyLowes loyalty card will provide more data about the customers it is important to understand it only represents a portion of the total customer base. The large volume of new data can bog down and confuse businesses if not handled properly. Our assignment...

References: Choudhary, A., Harding, J., Lin, H., Tiwari, M., & Shankar, R. (2011). Knowledge Discovery
and Data Mining Integrated (KOATING) Moderators for collaborative projects
Coco, C. T., Jamison, F., & Black, H. (2011). Connecting People Investments and Business
Outcomes at Lowe 's: Using Value Linkage Analytics to Link Employee Engagement to Business Performance
Coronel, C., Morris, S., & Rob, P. (2012). Database Systems: Design, Implementation, and Management, 10e, 10th Edition. [VitalSource Bookshelf version]. Retrieved June 15,
2015 from website: http://devry.vitalsource.com/books/9781285028231
Koch, R. (2015). From Business Intelligence to Predictive Analytics. Strategic Finance, 97(1),
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Milliken, A. L. (2014). Transforming Big Data into Supply Chain Analytics. Journal of Business
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Morio, J. (2014). Linking Business Intelligence to Strategy. Financial Executive, 30(4), 66-69,
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