The backbone of any customer strategy initiative is customer data. When managed well, customer insight helps companies provide personal service, more relevant communication, and a better experience—all while allowing the organization to increase wallet share and boost the ROI of their customer-focused initiatives. The Managed Analytics team will help you develop a Data Strategy that aims to provide a comprehensive set of recommendations to reach the ideal state of data ownership and quality required for customer analytics. We offer an array of services to enable data collection and management to best position your business to turn customer data into dollars. Our solutions include:
The Data Audit Service includes a review of the existing data structure. We work with your IT team to understand existing stored information about customers, how employees gain access to that information, and opportunities to share data across business units without extensive changes to the technology infrastructure. Our Managed Analytics team also develops recommendations on existing data systems and capabilities to facilitate one-to-one relationships that deepen customer loyalty and grow customer value.
Data Cleansing is a process of discovering, correcting, or removing incomplete or inaccurate data from a database. Data Cleansing capabilities allow organizations to make more informed decisions based on complete and accurate data while optimizing the IT investments made in database technology. We help our clients lay the foundation for their CRM initiative with a centralized, accurate customer data warehouse. Managed Analytics' data cleansing process includes: data warehouse/data mart/database cleansing, data profiling, data standardization, data parsing, data de-duplication, data enrichment and augmentation and data quality control, identification of customer reporting/analysis needs by different business departments, identification of ideal data structure for business needs, data audit for CDE on availability and quality, identification of gaps and development of data collection and sharing plan to close those gaps.
The result is one integrated and comprehensive source of customer information for all business analysis needs. This means consistency for analysis by different departments, synergy from knowledge-sharing across business units and less delays due to coordination with multiple units.
Data Warehouse Modeling
Data Warehouse Modeling is a process of producing abstract data models for one or more database components of the data warehouse. Data Warehouse Modeling includes data warehouse architecture, design, and construction. Managed Analytics helps clients gather, analyze, validate, and model data.
We also call Data Mining knowledge discovery. Our Managed Analytics Team uses the latest and most innovative analytical tools to extract interesting (non-trivial, implicit, previously unknown and potentially useful) information or patterns from data in large databases.
Along with these core solutions, Managed Analytics also provides Integrated Customer Data Design and Common Terminology; Customer Data Collection Strategy; Customer Data Quality Improvement Strategy; Data Transformation and Processing; Customer Analysis and Marketing Data Mart Design; Customer OLAP Design; and more.