Problem Statement

Despite being a major retailer, the client struggled with outdated and fragmented data systems. These systems prevented them from having a unified view of their operations across the board, leading to several significant challenges.

Key Challenges

• Inventory Discrepancies

  A lack of visibility into inventory levels resulted in frequent stockouts and overstocking, which impacted product availability and sales.

• Delayed Reporting

  Their legacy analytics infrastructure was slow to process data, meaning that decision-makers did not have access to timely insights needed for strategic actions.

• Missed Sales Opportunities

  Without real-time customer insights, the client was unable to effectively target their marketing efforts, leading to suboptimal customer engagement and missed revenue opportunities.

• Scalability Issues

  As the volume of data grew with the expansion of their business, their existing systems were unable to scale effectively, making it difficult to process large amounts of data in real time.

Solution Implemented

We implemented Databricks’ Lakehouse Platform to unify the client’s data, enabling seamless integration, real-time analytics, and actionable insights. The solution included:

• Real-Time Analytics Dashboards: Credencys created interactive dashboards that provided the client with immediate insights into sales, inventory, and customer behavior. This enabled quicker decision-making and improved operational efficiency.

• AI-Driven Demand Forecasting: Machine learning models were developed to optimize inventory levels by predicting demand more accurately. This helped reduce stockouts and overstocking, ensuring the right products were available at the right time.

• Personalized Marketing Campaigns: By analyzing customer behavior in real time, Credencys helped the client deliver targeted marketing campaigns, increasing customer engagement and boosting conversion rates.

• Scalable Data Infrastructure: Databricks’ platform provided a scalable architecture that could handle growing data volumes, ensuring the client’s analytics system remained future-ready.

Business Impact

• Improvement in Demand Forecast Accuracy:

  Improved inventory management, reducing stockouts and overstocking.

• Increase in Conversion Rates

  Real-time insights drove targeted marketing campaigns.

• Reduction in Manual Reporting Efforts

  Automation allowed staff to focus on strategic initiatives.