{"id":2052,"date":"2018-08-11T11:09:48","date_gmt":"2018-08-11T11:09:48","guid":{"rendered":"https:\/\/www.enginius.biz\/?page_id=2052"},"modified":"2019-05-30T11:02:19","modified_gmt":"2019-05-30T11:02:19","slug":"customer-relationship-management-crm","status":"publish","type":"page","link":"https:\/\/www.enginius.biz\/index.php\/instructors\/teaching\/customer-relationship-management-crm\/","title":{"rendered":"Customer relationship management (CRM)"},"content":{"rendered":"\t\t
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Teaching customer relationship management (CRM)<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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In a world where big data and business analytics make the headlines daily, it is useful to remind students that 90% of data collected by companies is indeed marketing data. Customer relationship management (CRM) is an approach to optimize a company\u2019s interactions with its current and prospective customers. It extensively uses data analysis about customers\u2019 history with a company to improve business operations, specifically focusing on customer retention and sales growth. The Enginius models best suited for a CRM course are therefore those relying on sales or behavioral data tracked and stored in companies\u2019 customer databases.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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If you are teaching customer relationship management<\/strong><\/br>\nthese are the Enginius models and case studies we recommend for you\u2026<\/h4>\n

Not familiar with Enginius yet? Click here<\/a> to discover<\/br>\nhow Enginus can boost your teaching.<\/h4>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Predictive modeling<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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The predictive module in Enginius is a powerful and versatile regression model that helps managers predict a variety of outcomes, such as loyalty, brand choice, response to an offer, expected revenues, or click-through rate, based on a set of available predictors in the customer database. Most customer databases contain a treasure trove of data to perform predictive analytics, so covering this in a customer relationship management course should be a no-brainer. One of the most appropriate case studies for your course is the Hope Foundation (predictive modeling) case study, where a charity uses past donation data to identify their most promising contacts in their donor database.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Customer lifetime value<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Looking at how customers transition from one segment to another over time, and how each segment is valued to the company, it is possible to estimate the expected value of a customer over its entire lifetime, and allocate company resources accordingly. Case studies like SyPhone or Northern Aero drive these points home.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Segmentation<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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In the magma of a customer database, customers are described by so many variables, it is often hard to make sense of them. Segmentation analysis helps a company group customers into clusters based on their similarities, and therefore identify behavioral patterns.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Questions? Need help?<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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If you are planning a course or need our help, please feel free to\u2026<\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Teaching customer relationship management (CRM) In a world where big data and business analytics make the headlines daily, it is useful to remind students that 90% of data collected by companies is indeed marketing data. Customer relationship management (CRM) is an approach to optimize a company\u2019s interactions with its current and prospective customers. It extensively … <\/p>\n

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