Detecting the warning signs of a possible meltdown is one example of how customer analytics can divert unpleasant circumstances. Analytical programs employ predictive technology, which gives users the capacity to compare customer behavior. For example, information can be gathered as to why customers have discontinued purchasing certain products. Once this profile is constructed, customers exhibiting similar behaviors can be rescued and brought back into the fold. Analytical programs take CRM one step further, whittlings vast amounts of data into usable, relevant information.
Business objectives determine which KPIs are activated.
For example, a company can pull the most profitable customers, the most dissatisfied customers, or even pull those that prefer, say, blue to black. Use of the application and its effect on the business is under constant surveillance. Organizations are also provided with metrics regarding the usage of the tool throughout the organization, the level at which the system is being used, the optimization of the system and identification of best practices. Based on the results of analysis, users can take action, feeding new information back into the data warehouse. New information is shuttled back to the source system and is available for use by appropriate personnel.