diaper and beer reflect the huge data processing time

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As information technology continues to evolve, peopleuse information technology to process data of the large increase in capacity,more and more databases are used in business management, production control andengineering design and other areas. However, the face of ever-increasingvariety of complex data, already exists in the database query functions can nolonger meet people's needs, can extract from the data that people needinformation and knowledge is our growing concern. Traditional statisticaltechniques have been facing tremendous challenges, set of statistics,databases, knowledge discovery technology in a data mining technologies haveemerged. In recent years, data mining technology in the retail, directmarketing, manufacturing, finance finance, insurance, communications andmedical services, etc., are widely used.
  
9 X. ]1 O% ?3 [First, the basic concepts of data mining
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WXYINHIT

好顶赞，不明觉厉，不觉明厉

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(五) the use of cross-selling model to sell existing customers new products or services
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! T& p2 r3 M1 N2 I! w- Y2 cRetail and customer relationship is an ongoing, developmental, and cross-selling is the selling point to customers a new product or service process. Cross-selling is based on buyers and sellers based on the principle of mutual benefit, the customer due to get more and better services to meet their needs benefit, enterprises can also benefit from the result of sales growth. Cross-selling advantage, businesses can more easily get more customers a wealth of information. Enterprise master customer information, especially the information prior to purchase, may be decided that the customers with the next purchase of critical information. At this time reflects the role of data mining, it can help businesses find customer buying behavior that affect the information and factors.
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(四) sequential pattern mining can be used for customer loyalty analysis
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6 ?8 B! T  F! ~- \5 K; t5 H/ CSequential pattern analysis and correlation analysis of similar, but the focus is on analysis of data before and after the sequence of the relationship between. Sequential pattern mining can be used to analyze the customer's loyalty to the changes in consumption or by which the price and variety of goods to be adjusted to retain old customers and attract new customers, to guarantee a certain number of customers. Merchants from the original client but later converted to competitor's customer base, analyze its characteristics, then the results of the analysis to existing customer data to identify possible shift in customers, and then devise methods to prevent the loss of customers; also according to customer's Consumer behavior and transaction records to sort of customer loyalty, according to the level of wastage and thus with different strategies.
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(四) sequential pattern mining can be used for customer loyalty analysis
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Sequential pattern analysis and correlation analysis of similar, but the focus is on analysis of data before and after the sequence of the relationship between. Sequential pattern mining can be used to analyze the customer's loyalty to the changes in consumption or by which the price and variety of goods to be adjusted to retain old customers and attract new customers, to guarantee a certain number of customers. Merchants from the original client but later converted to competitor's customer base, analyze its characteristics, then the results of the analysis to existing customer data to identify possible shift in customers, and then devise methods to prevent the loss of customers; also according to customer's Consumer behavior and transaction records to sort of customer loyalty, according to the level of wastage and thus with different strategies.
% `0 {6 v9 s! Ahttp://b2b.itonghui.com/

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(三) The use of multi-dimensional analysis and correlation analysis to analyze the effectiveness of promotional activities
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, d) W, }" a! C; i- P& ?5 p( dThe use of multi-dimensional analysis and correlation analysis examined data from the database to analyze customer buying habits, advertising success rate, and other strategic information. By searching the database using a database of sales data in recent years, using multi-dimensional correlation analysis method, by comparing the sales volume of sales and number of transactions during the period and promotional activities before and after the situation, predictable seasonal and monthly sales, variety of goods and inventory trends analysis could also determine the bargains, and the number and operation of the decision-making. Moreover, the correlation analysis can find out which products can be used for promotional activities, to facilitate arrangements for supply of goods and improve sales.
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(二) the use of correlation analysis of information to make a purchase recommendation for mining association and commodity reference
  
: g- }5 w; i& s/ Q. }0 m+ PCorrelation analysis is the use of association rules, data mining techniques, aimed at the hidden relationships between the data found in the database form, such as .. "90% of customers in a purchasing activity to purchase A purchase of merchandise B products will also "The kind of knowledge. Sales records from the Mining Association information, you can find customers to buy a particular brand is likely to purchase other commodities. Such information can be used to form a definite buy recommendation. Businesses through advocacy to improve services to help customers choose products, increase sales and reduce inventories.
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(一) The use of multi-feature data cube for sales, customer, product, time and regional multi-dimensional analysis of
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Multidimensional data analysis is the way through the multi-dimensional analysis of the data, query and reporting. Dimension is one specific point of observation data. For example, companies considering the sale of products, usually from the customer, product, time and regional perspective of insight into the different product sales. Here customers, products, time and area is the dimension. According to different combinations of these dimensions and the study of metrics from the customer found in the basic library of different customer base, so that decision-makers according to the characteristics of the main customer base, accordingly, orders, sales and service decision-making. .. Http://www.dmresearch.net/bbs
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4, data mining technology in the retail application
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2 V5 n' S, \( ?; H5 IWith the growing rise of Web or e-commerce methods, retail CRM is the main application areas of data mining. Data mining technology can help to identify customer buying behavior, found that customer buying patterns and trends, improve service quality, achieve better customer retention and satisfaction, improve goods sales ratio, design better products transportation and distribution strategy to reduce business costs. Data Mining Application of CRM in the retail industry is mainly reflected in the following areas:

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(四) association rule mining algorithm
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Association rule mining is used to detect the correlation between attributes in the database connection algorithm. Association rule discovery is the essence of the task was found in the database, strong association rules, use of these association rules to understand customer behavior, the most typical example is market basket analysis.
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