Customer relationship management
Customer relationship management has to do with any methods, policies, and procedures that are utilized by a company to provide a high level of customer care to existing clientele, orient new customers to the products and services offered by the business, and encourage general customer retention. Sometimes referred to as CRM, customer relationship management is a subject that is covered in a number of training manuals, inn house training, and continuing education seminars that are aimed at helping companies develop healthy relationships with the client base
Generally, competent customer relationship management involves providing customer assistance on a variety of levels. These levels are usually classified into three main categories, usually referred to as operational, collaborative, and analytical. Companies of just about every size will incorporate elements of each classification into the business strategy, helping to ensure an ongoing rapport with the customer base.
The operational aspects of customer relationship management involve processes that provide for direct interaction between the client and a customer care specialist. Many of these processes are time honored methods, such as on site visits with the customer, contacts by telephone, and letters and other printed matter that is exchanged between the client and the customer support staff. Today, such vital means of communication as email, audio and video conferencing, and instant messaging also provide this direct link between customer and support specialist.
Collaborative methods of customer relationship management allow for direct contact between the client and the company, but do not include the presence of customer support staff. These methods may include automated online access of the customer to his or her account information; the ability to order new products of services online, and to submit changes to account information using automated tools provided by the vendor. Generally, these tools are available for use around the clock, making it possible for a customer to manage the relationship in his or her own time.
The analytical aspect of customer relationship management has to do with the systematic analysis of customer data. This is an internal process, and does not initially involve interaction with the customer. Instead, historical data on the purchasing patterns of the customer, including which goods or services are purchased and at what intervals, is used to determine if there is some sort of new product or service that the vendor can develop and offer to the customer. Analyzing past usage of the client base in general can also help the company develop new strategies to educate existing customers about other products that may be of interest, which can translate into additional ties of loyalty between supplier and customer
http://www.onlinerelationshipcoach.blogspot.com
Generally, competent customer relationship management involves providing customer assistance on a variety of levels. These levels are usually classified into three main categories, usually referred to as operational, collaborative, and analytical. Companies of just about every size will incorporate elements of each classification into the business strategy, helping to ensure an ongoing rapport with the customer base.
The operational aspects of customer relationship management involve processes that provide for direct interaction between the client and a customer care specialist. Many of these processes are time honored methods, such as on site visits with the customer, contacts by telephone, and letters and other printed matter that is exchanged between the client and the customer support staff. Today, such vital means of communication as email, audio and video conferencing, and instant messaging also provide this direct link between customer and support specialist.
Collaborative methods of customer relationship management allow for direct contact between the client and the company, but do not include the presence of customer support staff. These methods may include automated online access of the customer to his or her account information; the ability to order new products of services online, and to submit changes to account information using automated tools provided by the vendor. Generally, these tools are available for use around the clock, making it possible for a customer to manage the relationship in his or her own time.
The analytical aspect of customer relationship management has to do with the systematic analysis of customer data. This is an internal process, and does not initially involve interaction with the customer. Instead, historical data on the purchasing patterns of the customer, including which goods or services are purchased and at what intervals, is used to determine if there is some sort of new product or service that the vendor can develop and offer to the customer. Analyzing past usage of the client base in general can also help the company develop new strategies to educate existing customers about other products that may be of interest, which can translate into additional ties of loyalty between supplier and customer
http://www.onlinerelationshipcoach.blogspot.com
Customer relationship analysis
Customer relationship analysis (CRA), sometimes termed customer relationship analytics, is the processing of data about customers and their relationship with the enterprise in order to improve the enterprise's future sales and service and lower cost. This term is generally a synonym for CRM analytics.
Customer relationship analysis can be considered a form of online analytical processing (OLAP) and may employ data mining. As Web sites have added a new and often faster way to interact with customers, the opportunity and the need to turn data collected about customers into useful information has become generally apparent. As a result, a number of software companies have developed products that do customer data analysis.
According to an article in InfoWorld, customer relationship analysis can provide customer segmentation groupings (for example, at its simplest, dividing customers into those most and least likely to repurchase a product); profitability analysis (which customers lead to the most profit over time); personalization (the ability to market to individual customers based on the data collected about them); event monitoring (for example, when a customer reaches a certain dollar volume of purchases); what-if scenarios (how likely is a customer or customer category that bought one product to buy a similar one); and predictive modeling (for example, comparing various product development plans in terms of likely future success given the customer knowledge base). Data collection and analysis are viewed as a continuing and iterative process and ideally over time business decisions are refined based on feedback from earlier analysis and consequent decisions.
Benefits of customer relationship analysis are said to lead not only to better and more productive customer relations in terms of sales and service but also to improvement in supply chain management (lower inventory and speedier delivery) and thus lower costs and more competitive pricing.
One of the major challenges implicit in customer relationship analysis is how to integrate the analytical software with existing legacy systems as well as with other new systems.
A new area of application and data collection has to do with Web site customer usage.
Customer relationship analysis can be considered a form of online analytical processing (OLAP) and may employ data mining. As Web sites have added a new and often faster way to interact with customers, the opportunity and the need to turn data collected about customers into useful information has become generally apparent. As a result, a number of software companies have developed products that do customer data analysis.
According to an article in InfoWorld, customer relationship analysis can provide customer segmentation groupings (for example, at its simplest, dividing customers into those most and least likely to repurchase a product); profitability analysis (which customers lead to the most profit over time); personalization (the ability to market to individual customers based on the data collected about them); event monitoring (for example, when a customer reaches a certain dollar volume of purchases); what-if scenarios (how likely is a customer or customer category that bought one product to buy a similar one); and predictive modeling (for example, comparing various product development plans in terms of likely future success given the customer knowledge base). Data collection and analysis are viewed as a continuing and iterative process and ideally over time business decisions are refined based on feedback from earlier analysis and consequent decisions.
Benefits of customer relationship analysis are said to lead not only to better and more productive customer relations in terms of sales and service but also to improvement in supply chain management (lower inventory and speedier delivery) and thus lower costs and more competitive pricing.
One of the major challenges implicit in customer relationship analysis is how to integrate the analytical software with existing legacy systems as well as with other new systems.
A new area of application and data collection has to do with Web site customer usage.
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