Correlation 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.
(三) The use of multi-dimensional analysis and correlation analysis to analyze the effectiveness of promotional activities
The 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.
(四) sequential pattern mining can be used for customer loyalty analysis
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.
http://b2b.itonghui.com/
(四) sequential pattern mining can be used for customer loyalty analysis
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.
http://b2b.itonghui.com/
(五) the use of cross-selling model to sell existing customers new products or services
Retail 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.
好顶赞，不明觉厉，不觉明厉
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