Special Report on
Predictive Customer Lifecycle Management
Predictive Customer Lifecycle Management - Trends
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The purpose of Customer Life-cycle Management (CLM) is to maximize both customer retention and profit. CLM differs from CRM in the sense it emphasizes time-varying nature of customer management. CLM process starts with marketing research analysis and customer acquisition followed by conversions, up-selling, re-selling, cross-selling, and more importantly churn management. It attempts to maximize utilization of customer potentials which is the most important resources in business. Predictive modeling and rule-based expert systems are most important areas of Artificial Intelligence (AI). Predictive modeling takes past ...
i.e., mapping the discrepancies between the people, processes and technologies that you have currently and those needed to achieve your marketing goals. If you’ve done the “homework”, you now know what you need but not how to get to what you need or how long it will take and what the junctures are. Many companies I’ve worked with have a pretty good view of the end game – a usable, efficient marketing automation solution – but haven’t created realistic milestones to reach it. They have no Marketing Automation Roadmap. Would you leave Boston to drive to San Francisco without a map, ... Read More
SURVEY RESULTS FOR
PREDICTIVE CUSTOMER LIFECYCLE MANAGEMENT
The IT Architecture of Connected Decisions
Application Lifecycle Management
- Microsoft PowerPoint - Blaze Advisor Webinar - BPM - Sep 2009
- Alterian June 2009 Webinar Addressing Retail Trends Through An ...