Prioritize to Improve Life-Cycle Analytics

Conduct a calculated review of the consumer life-cycle areas and put your company’s attention on areas that will generate maximum returns. Your company’s priority will depend upon a host of factors like competitive situation, strategic goals, etc.

Improve Cross-Organizational Data Collection: When the key focus areas have been identified, collect cross-organizational data from varies internal systems. Remember, collecting proper data is just as important. Many companies have lost millions of dollars attempting to gather data that is irrelevant and low value-add for the analytics required.

Augment External Data: To improve statistics accuracy and effectiveness of marketing models, supplement internal data with external information, such as credit bureau data, demographic information, and/or sector-specific.

Analyze Data: Develop analytical models to generate precise lists, course of action, and regulations that the frontline staff should act on, e.g., retention lists and cross-sell prospect lists.

Build an Analytics Capability: To harness the complete potential of analytics across the customer life cycle and create a company-wide culture of analytics-driven decision making, your business must build significant capabilities.

Your basic framework should include a well-defined strategic imperative to create clear company-wide communication and manage change, a comprehensive data gathering and storing process, and technology to transform, clean, and link internal and external data at minimal investments. It must also have efficient and defined processes for analytics and best practice sharing, an analytical engine and a test-and-learn culture, which thrives on detailed iterative analysis, establishment of guidelines for data/model access, ongoing monitoring and refinement of the engine, and an appropriate governance and funding mechanism to ensure appropriate resources for these tasks. C-level sponsorship is critical.