Our client is a digital transformation leader with an Auto Tech division focused on modernizing automotive retail across Southeast Asia. Serving multi-brand dealerships in the Philippines and Indonesia, this business unit delivers digital solutions that enhance lead management and customer-sales engagement, ultimately helping dealerships with data-driven insights to drive sales growth and improve customer experience.
Our client offers multi-brand automotive dealerships an interactive digital application to manage the entire sales journey, from enquiry to loan approval and vehicle delivery. However, its reliance on an SQL database with data scattered across 35+ fragmented tables hindered data consolidation and calculation of KPIs to generate insights. This fragmentation limited performance tracking at branch and salesperson levels, thereby hindering visibility into achievement of sales targets and delaying identification of underperformers.
Additionally, the absence of real-time, standardized views on vehicle enquiries and sales trends obstructed clear understanding of product performance across branches. This data gap delayed decision-making and weakened sales strategies and customer engagement.
The client needed a centralized, automated solution to unify data, enable real-time KPI tracking, and provide actionable sales and product insights at all organizational levels.
We modernized the client’s data pipelines by implementing a robust ETL process in Azure Databricks. Python scripts were developed to extract, transform, and aggregate lead and sales data from the 35+ transactional tables into a single, consolidated dataset. This automated data foundation enabled the computation of all business-critical KPIs. This ensured consistent, scheduled refreshes for up-to-date reporting.
With a unified, automated data foundation, we created an integrated Sales vs. Target Performance Dashboard in Tableau, embedded in the client’s unified portal. This provided managers with real-time, consolidated insights across regions, branches and sales staff, enabling targeted monitoring through drill-down capabilities. The self-service functionality helped managers to independently set and adjust sales targets, accelerating response times and reducing dependency on data teams.
We built a Product Sales Trend Dashboard to give managers dynamic, real-time visibility into product performance across dealerships. This view offered flexible time filters for weekly and monthly comparisons, uncovering insights on top-performing and underperforming vehicle models. It also enabled granular branch- and product-level analysis, facilitating strategic actions such as inventory optimization and tailored promotions.
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