Role of Data Mining in retail sector

G. Saravanan | August 12,2013 11:17 am IST

Abstract
Retail industry collects large amount of data on sales and customer shopping history. The quantity of data collected continues to expand rapidly, especially due to the increasing ease, availability and popularity of the business conducted on web, or e-commerce.

Retail industry provides a rich source for data mining. Retail data mining can help identify customer behavior, discover customer shopping patterns and trends, improve the quality of customer service, achieve better customer retention and satisfaction, enhance goods consumption ratios design more effective goods transportation and distribution policies and reduce the cost of business.
 

Introduction: Data Mining
Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases.
 

Continuous Innovation
Although data mining is a relatively new term, the technology is not. Companies have used powerful computers to sift through volumes of supermarket scanner data and analyze market research reports for years. However, continuous innovations in computer processing power, disk storage, and statistical software are dramatically increasing the accuracy of analysis while driving down the cost.

Data mining in Retail Industry
The retail industry is realizing gain a competitive advantage utilizing data mining. Retailers have been collecting enormous amounts of data throughout the years, just like the banking industry, and now have the tool needed to sort through this data and find useful pieces of information. For retailers, data mining can be used to provide information on product sales trends, customer buying habits and preferences, supplier lead times and delivery performance, seasonal variations, customer peak traffic periods, and similar predictive data for making proactive decisions. Here are some examples of how the retail industry has been utilizing data mining effectively.
 

Why Data mining in CRM?
“CRM is about acquiring and retaining customers, improving customer loyalty, gaining customer insight, and implementing customer-focused strategies. A true customer-centric enterprise helps your company drive new growth, maintain competitive agility, and attain operational excellence.” SAP
 

Customer Relationship Management (CRM) is a business philosophy involving identifying, understanding and better providing for your customers while building a relationship with each customer to improve customer satisfaction and maximize profits. It’s about understanding, anticipating and responding to customers’ needs.
 

To manage the relationship with the customer a business needs to collect the right information about its customers and organize that information for proper analysis and action. It needs to keep that information up-to-date, make it accessible to employees, and provide the knowhow for employees to convert that data into products better matched to customers’ needs.
 

The secret to an effective CRM package is not just in what data is collected but in the organizing and interpretation of that data. Computers can’t, of course, transform the relationship you have with your customer. That does take a cross-department, top to bottom, corporate desire to build better relationships. But computers and a good computer based CRM solution, can increase sales by as much as 40-50%.
 

Market Basket Analysis
It is used to study natural affinities between products. One of the classic examples of market basket analysis is the beer-diaper affinity, which states that men who buy diapers are also likely to buy beer. This is an example of 'two-product affinity'. But in real life, market basket analysis can get extremely complex resulting in hitherto unknown affinities between a number of products. This analysis has various uses in the retail organization. One very common use is for in-store product placement. Another popular use is product bundling, i.e. grouping products to be sold in a single package deal. Other uses include designing the company's e-commerce web site and product catalogs.
 

Customer Acquisition and Retention
Data mining can also help in acquiring and retaining customers in the retail industry. The retail industry deals with high levels of competition, and can use data mining to better understand customers’ needs. Retailer can study customers’ past purchasing histories and know with what kinds of promotions and incentives to target customers. Also, if a store has seen a number of people leave and go to competitors, data mining can be used to study their past purchasing histories, and use this information to keep other customers from doing likewise.
 

Major Problems of the Retail Industry

  • Employee Turnover
  • Auditing
  • Economic Challenges
  • Technology

Data mining for every retailer:
Almost any retailer could gain some value from analyzing their data. The main driver for whether or not to do so will be the scale potential benefits and return on investment (ROI) compared to the cost of collecting, storing, and analyzing the data. Thus a specialist retailer, with very few products and customers, may gain little insight from data mining over and above their own knowledge of their business.
 

Data mining application areas

  • Medical / Pharma
  • Insurance and Health Care
  • Banking / Finance
  • Retail / Marketing
  • Telecommunication
  • Software and system engineering
  • Manufacturing

Retail / Marketing

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G.Saravanan has done B.E.,MBA.,MCA. He is currently doing his research program in SRMV college of arts and science, Coimbatore, India. He has 4 years of experience in retail sector and at present working as an outlet manager in Trends In Vogue Pvt. Ltd., A cavinkare group company with 3 years of experience....