Business Objective
Our client is a leading independent global automotive distributor, operating in over 40 markets with a portfolio of leading automotive brands. In recent times, a combination of market disruption, increased regulations, and dynamic customer behavior has highlighted the need for agility and personalization. So, the client embarked on an aggressive pursuit to become a data-driven organization.
However, the journey to tapping into data analytics at such a large scale started with challenges like the prevalence of legacy systems, disconnected data sources, and siloed processes.
Challenges
- Prevalence of complex legacy systems that come with multiple sources of data
- Siloed and disconnected processes to manage the current flow of data
- Lack of a strong platform to drive analytics use cases for customer growth and retention
Solution Methodology
- Established a centralized approach through discovery, analysis, development, deployment – covering data engineering and data science
- Backed by Microsoft Azure with Databricks as the preferred cloud platform, deployed a scalable data pipeline for advanced analytics and BI reporting
- Built a lake house on Azure by ingesting, enriching, and integrating data about various business operations, tightly coupled with “Data Quality” validation using open-source framework and ensured reliability of data used for Analytics
Business Impact
- Sales teams are selling the same number of vehicles but handling 40% fewer leads and driving overall higher lead conversion
- Dynamically changing prices w.r.t to market factors – leading to a 4% increase in profits for one OEM brand in a market
- Better visibility on top churners – improving customer retention rate by 15% in a market
- Governed Lakehouse solution that organizes & manages data, logs events, usage of cloud resources to track & optimize cloud costs to budgets defined
