Challenges: Sub-Optimal Implementation Limits Analytics Capabilities
The credit card division of a leading global financial services enterprise sought stronger insight into its online business operations, including its corporate credit card program. Like many companies, the bank wanted to better understand how well it performed in new customer acquisition (from referral to approval or decline) and overall customer management (from approval to registration to log-in). That objective required gaining clear visibility into the source of customer referrals, across channels, from offline advertising, bank kiosks and other sources. Further, it wanted to track results by individual accounts, segment and industry.
To meet its goals, the company made a significant investment in a full-featured analytics platform. However, due to sub-optimal implementation, the company was not realizing the expected performance gains and cost savings after deployment. In fact, costs had risen due to configurations that led to unnecessary server calls. Additionally, business stakeholders lacked confidence in the information due to the complexity of reports and poor data collection practices.
Results: Clear Path to Effective Analytics, Higher Technology ROI
The Infinitive Analytics team drafted a comprehensive set of business requirements and specific action steps that would serve as a roadmap to stronger analytics capabilities, increased technology ROI and, ultimately, better business decision making. A combination of suite architecture changes, metric and variable standards, page and channel naming conventions, and event analysis, would allow the bank to achieve much greater value from their technology implementation.
A total of 37 recommendations were organized by phases to ensure both incremental improvement in the short term and a longer-term vision for ongoing improvement through a best practices-based analytics program. Other specific enhancements included:
- Re-architecture of the reporting suite for easier readability of both high-level and granular viewpoints of data sets
- Increased use of data analysis modules
- Streamlined data feeds and the application of data standards for higher consistency, quality and accuracy
- Improved campaign tracking
- The use of alerts and notifications to track significant shifts in traffic patterns
- Stronger data governance models
- Enhanced forms management capabilities
- Organizational model with detailed job descriptions and roles and responsibilities