Basic Structure of Electronic CRM
The adoption of electronic customer relationship management (eCRM) has grown because people spend more time on the internet. In the eCRM strategy, customers are connected to the operational CRM and collaborative CRM. The analytical CRM supports the operational CRM and collaborative CRM. A data warehouse is a place where varieties of data are stored to help companies make decisions. The importance of data warehouse in CRM are: It can integrate information from multiple sources, It helps with the storage of click stream data, It helps with campaign management, It allows for real-time personalisation of data. Data mining is a technique used to carry out knowledge discovery in databases. It turns data into information, and then to knowledge. The steps in the knowledge discovery in databases process are:
Selection of data, Pre-processing of target data, Transformation of pre-processed data, Data mining of transformed data, Interpretation of mined data. The five major classifications of data mining tasks are:
Classification, Regression, Link analysis, Segmentation, Deviation detection.
The important modules of eCRM are: Campaign management | Sales Management module | Customer feedback module
The features of the campaign management module in eCRM are:
Workflow, Segmentation, Personalisation, Execution, Response management
Response modelling. The steps in the sales process are: Prospecting/lead generation, Initiating contact, Identifying needs, Presenting offer, Manage objections, Close a sale. The features of customers service setup in CRM are: Multiple channel access, Solutions knowledge-based platform, Request management platform, Contract and warranty status
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