Global automotive distributor Inchcape achieves data-driven digitalization with Azure

Headquartered in London, automotive distributor Inchcape partners with the world’s most popular brands like BMW, Land Rover, and Toyota. Inchcape distributes and markets vehicles to over 40 countries across six continents. “As a distributor, we do the national marketing, choose what cars to bring in, run the logistics and manage the retail network of dealerships and service centers for brands in a particular market,” says Alex Capewell, Director of Global Data & Analytics at Inchcape. “At our core, we focus on logistics, product planning, sales and marketing.” 

Over the last few years, market changes in the automotive sector have created a growing value gap between manufacturers and consumers. Inchcape needed to remedy this by adapting swiftly to industry disruptions such as changing customer digital behavior, stricter ESG regulations, and the boom in demand for electric and hybrid vehicles. In 2020, Inchcape’s new Chief Executive Officer and Chief Digital Officer recognized the need for digital solutions and established the company’s new digital transformation strategy called ‘Accelerate.’ 

“Data and analytics are at the heart of our ‘Accelerate’ digital strategy to set our business up for success over the next five to six years,” says Ram Thilak, Global Head of Data Science at Inchcape. “Our leaders empowered us to build a central analytics team and pursue a modern analytical architecture that provides real-time and event-driven business intelligence and predictive analytics insights.”   

Setting the foundation for analytics success

With the full support of the leadership team, Inchcape’s next step was to find the right partner to help build its data and analytics capabilities. They believe the key lies in seamless omni-channel transformation to create the optimum customer experience. The company needed a partner with extensive experience in pricing and customer analytics, use case development, and cloud-based solutions. “Tiger Analytics ticked all of those boxes for us,” recalls Capewell. “They were part of every important decision we made in setting up the foundations for our data digitalization.”  

Inchcape’s data and analytics subject matter experts also began evaluating cloud computing options to form the basis for its analytical architecture. After considering the ‘big three’ cloud providers and consulting with implementation partners, they arrived at a conclusion. “Azure was the platform of choice for our needs as Inchcape had a lot of SQL-based systems, and we were already familiar with Microsoft’s products, integrations, and business,” explains Thilak. “Azure also had some valuable features such as Databricks and Data Factory, which are very efficient in transforming data.” Additionally, because most of Inchcape’s legacy systems were SQL-based, migration and deployment were faster and more agile with Azure compared to the other platforms considered.  

The company developed initial use cases for its data models, seeing them as tools for making better business decisions. “We centered our initial use cases around three key products,” says Capewell. “We sell new and used cars, offer service warranties for the cars we sell, and sell parts to dealership networks and independent shops.” 

The first use case was centered around car sales. The team created a lead scoring tool for customers with a score determined by their ‘digital body language’ based on website interactions, showroom visits and sales history. The second use case was after-sales churn prediction, which was tied to service warranties. By analyzing warranty and car servicing data, Inchcape can engage with customers proactively before they decide to leave. The third use case was parts pricing optimization and profit maximization, which are tied to transactions with dealerships and shops. By evaluating parts transaction data, Inchcape can determine better opportunities to maximize product price elasticity. 

On the road to data-driven digitalization

Together with Tiger Analytics, Inchcape built a data analytics center of excellence, achieving a centralized approach to harnessing the power of data. From this, the company developed a new global analytics and business intelligence platform that integrates data from across the company. The platform now serves as a single source of truth for business decision-making. In 12 months, data was examined from over 40 global markets. Having centralized data resulted in 75 percent improvement in data accessibility across the organization, which fed into day-to-day decision-making. Furthermore, the implementation of Azure Purview helped Inchcape manage metadata, eliminate KPI discrepancies, and support the end-to-end data pipeline for advanced analytics and reporting. Inchcape analysts can now do more with the data they have, drawing insights that were previously inaccessible. "Effective use of Microsoft products, helped accelerate delivery and future proof Inchcape's data management strategy,” says Lakshmi Vaideeswaran, VP and Client Partner for Inchcape.

Azure also provided Inchcape with visibility over cloud use and costs so the company could be proactive in scaling up or down as needed. “The usage visibility makes it easier for us to show the ROI for our data tools,” says Thilak. “Plus, it is more cost effective with 2.5 to 3 times the delivery capacity for the same expenditure.”

Gaining better results with data

With the change, Inchcape achieved a 12x increase in price update efficiency in the Chilean market. Instead of yearly updates on the pricing model, the company can now undertake monthly price updates. Instead of setting a buffer and evaluating the margin a year later, Inchcape’s new system enabled local decision-makers to see real-time data insights and respond more quickly to market changes. This has led to greater cost-efficiency and profitability and it is a model that can be replicated in other markets.

For the Hong Kong market, A/B testing on data models was applied to lead scoring as a way to improve the return conversion rate. Inchcape’s team used an algorithm-based approach instead of a traditional rule-based approach to assign a score to leads, resulting in a 2.5 percent increase in conversion. “Lead scoring is a remarkable milestone for Inchcape as we have deployed real-time machine learning technology into the business,” shares Capewell. “This solution was built in-house using our Azure Databricks (AI) and sets the template for how we can transform our business with data in 2022 and beyond.”

Meanwhile, the company was also able to reduce churn with existing customers, the second use case. Implementing the new analytics model led to a 20 percent retention rate in the Australian market for high-churn risk customers. By using data to identify high-churn risk customers and running A/B tests, the company developed improved customer engagement strategies that enhanced the overall customer experience and led to improved customer retention. 

Driving future growth with analytics

Inchcape's data-driven digitalization is now ramping up as the company is taking big steps to expand its analytics capabilities company wide. From 2021 to 2022, the company’s central analytics team grew from 20 to 150 employees globally. “Our team is now able to manage the data platform, data science, business intelligence, and automation tasks,” says Capewell. “We’re gradually transitioning towards our team managing all of our data capabilities, and Tiger Analytics is very supportive of that.” 

Learning from the initial use cases, Inchcape is now evaluating 20 more possible use cases. It has also established a long-term analytics roadmap to drive its data strategy well into the future. “Predictive algorithms like real-time lead scoring, churn prediction and parts pricing optimization helped us understand our customers better, run our business more efficiently, and enabled us to unlock the true value of our data,” says Thilak. “Through new use cases, we aim to establish how to use data to fuel every important business decision we make.” 

The secret to Inchcape’s success is a targeted approach to digitalization. “Rather than letting data and infrastructure take the lead, we were careful to focus on use cases that were short time-to-value and easy to implement,” shares Capewell. Thilak echoes his sentiments, “We took a more business-centric approach and tried to build use cases that can accelerate value to the business, which is one reason why we were able to achieve 30 implementations in less than nine months.”