Driving Data-Driven Decision Making with Salesforce Data Cloud​Finance

The client is a leading financial services company offering a wide range of products, including banking, insurance, and investment services.

With a vast customer base spread across various demographics, the client faced challenges in understanding customer needs, preferences, and behaviors in real-time. The lack of a unified data management solution hindered their ability to make data-driven decisions and deliver personalized experiences to their customers.


  • Data Quality Issues The client encountered inconsistencies and inaccuracies in their data, leading to doubts about its reliability and usability for decision-making.​
  • Limited Data Accessibility The client had challenges in accessing critical data for certain departments or individuals, hindering collaboration and decision-making across the organization.​
  • Inefficient Data Processing Manual data processing and manipulation tasks were time-consuming and error-prone, slowing down analysis and decision-making processes.​


  • Seamless Data Integration Our team seamlessly integrated Data cloud consolidating data from multiple sources which ensured a unified view of customer data across the organization, eliminating data silos and enabling seamless data access and sharing.​
  • Data Quality Enrichment Using the AI-driven algorithms the data was enriched with additional attributes, to provide deeper insights into customer preferences and behaviors.​
  • Real-Time Analytics With interactive dashboards and predictive modeling tools, business users could identify opportunities for cross-selling, upselling, and customer retention, driving revenue growth and profitability.​
  • Techstack: Data cloud, CPQ


  • Improved Operational Efficiency The automated data synchronization between CRM, ERP, and transactional databases eliminated manual data entry and reconciliation tasks, saving 20 hours/week.​
  • Enhanced Customer Insights Enriched customer profiles and real-time analytics enabled identifying the unrecognized trends, leading to 20% increase in customer engagements.​
  • Revenue Boost The personalized engagement approach led to a 25% increase in cross-selling and upselling opportunities, driving the revenue boost by 15%.​
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