A Mid-Tier Regional Bank hires DecisivEdge to deliver a comprehensive end-to-end assessment of converting an existing but “data siloed” warehouse to a fully integrated and marketing analytics oriented solution.
Key challenges encountered throughout the integrated data warehouse study included issues with poor data quality, lack of historical data, and missing operational data to drive performance metrics. The following list of key business objectives were established in order to meet project expectations and deliver a comprehensive assessment for the client:
- Gain an understanding of the customer base including key demographics, product distribution, product usage, and wallet share
- Ability to identify and implement strategies to attract millennials
- Increase wallet share in terms of number of products through the implementation of enhanced cross-selling strategies
- Analyze results of cross-selling activities and refine strategies, focusing on customer segments, to target customers and optimize interactions resulting in increased wallet share
- Create customer segmentation definitions and track changes in segmentation over time
- Ability to identify all customer relationships in a single data source
Following confirmation of the business objectives, the following project goals were developed:
- Document the list of questions and key performance indicators to be provided by the information in the data warehouse.
- Identify the source systems that will provide the data to be compiled in the data warehouse, including the availability and process for obtaining updates from these systems as well as the method for how the updates will be captured.
- Complete the data quality assessment of key fields from source systems. The fields were identified by the business stakeholders and results of the analysis provided.
- Evaluate existing data management governance policies and make recommendations related to the enhancement and implementation of stewardship and governance policies to ensure the on-going integrity of the data warehouse.
- Document security requirements as it relates to the information available in the data warehouse and what roles are needed to ensure each user (group of users) only have access to the information they need to perform their job functions.
The DecisivEdge data warehouse team applied its extensive business process and design expertise to deliver a comprehensive “marketing-centric” assessment of both prospective and current customer behavioral attributes. The recommendations fell into the following four categories:
- Decisioning – Behavioral segmentation, flight plan for segments, develop micro-segments, implement customer level strategies, enhance propensity models
- Develop Base Insights – Test and control strategies, new customer acquisition, customer value maximization, develop propensity models, implement model governance, test and validate propensity models, supplement real-time operational intelligence
- Analytics Development – Time series based learning, product level usage views, engagement channel overlay, know the customer (segmentation), develop and refine use cases, develop/implement business metrics
- Analytic Foundation – Scalable analytic infrastructure, operational data capture, data cleanliness, metadata management, data governance, adapt culture to data driven
DecisivEdge presented the client with the assessment along with a roadmap and high-level project plan including suggested action steps and conversion of the current state data warehouse structure with concisely outlined recommendations to build specific requirements into a new enterprise solution for the client. The client is in the process of developing action plans to deliver the changes recommended by DecisivEdge.
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