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Creating a unified customer view across 200+ brands


Higher automotive sales


Decrease in loss sale opportunity and inventory holding cost


Faster time-to-insight

CLOUD: Azure

“Databricks Data Intelligence Platform allows every division in our organization — from automotive to retail — to gain a unified view of our customer across businesses. With these insights, we can optimize everything from forecasting and supply chain, to powering our loyalty program through personalized marketing campaigns, cross-sell strategies and offers.”

— Dmitriy Dovgan, Head of Data Science at Al-Futtaim Group

As a driving force for economic growth in the Middle East, Al-Futtaim impacts the lives of millions of people across the region through the distribution and operations of global brands like Toyota, IKEA, Ace Hardware, and Marks & Spencer. With a wealth of data such as demographics and transaction history being generated across these varied brands, Al-Futtaim’s focus is to harness their data to improve all areas of the business, from streamlining the supply chain to optimizing marketing strategies. But with the brands capturing such a wide variety of data, its legacy systems struggled to provide a single view into their customer due to data silos and the inability to scale efficiently to meet their analytical needs. Business intelligence was slow in terms of new dashboard development, forecasting was not scalable and was limited to classical algorithms, and customer insights were too generalized to affect outcomes faster. With Databricks Data Intelligence Platform, Al-Futtaim has transformed their data strategy and operations, allowing them to create a “golden customer record” that improves all decision-making from forecasting demand to powering their global loyalty program.

A legacy system fails to enable data teams

Whether it’s cars, finance, real estate, retail or health, Al-Futtaim takes a people-first approach to enrich the lives of consumers. As a customer-centric company, Al-Futtaim seeks to harness the power of its data to help both business units and customers make smarter decisions. Despite having data points from manufacturing and operations, as well as from buying behavior and engagement, Al-Futtaim lacked the ability to unify these disparate data sets in a way that could impact business outcomes.

Using a legacy on-premises data warehouse, every one of Al-Futtaim’s data teams was unable to maximize the promise of their data. Data engineering struggled to build scalable data pipelines due to memory and CPU constraints that limited their ability to provision consistent and reliable compute clusters. Data scientists were stifled with legacy ML approaches, outdated libraries and inflexible tooling. Data analysts had to wait four to six hours for small amounts of data to process, which slowed both time-to-insights as well as time-to-market of new ideas. Without a unified approach to data, AI and analytics, none of these teams could collaborate, data silos were huge blockers, and pipeline creation and data insights only served singular purposes.

Dmitriy Dovgan, Head of Data Science at Al-Futtaim, describes the situation: “We couldn’t scale data preparation, we didn’t have any tools or methods that could be applied outside of Python and classical ML models, and we couldn’t reuse solutions for other brands. For example, within automotive, we have several brands: Lexus, Toyota, Chrysler … but without a unified platform, each solution could only be used for that dedicated use case.” The extra time, effort and resources required to redesign, implement, test and launch data projects added unnecessary costs, created a greater divide between business units and ultimately slowed innovation.

It was clear to the data science team that they needed to modernize their infrastructure by adopting a lakehouse architecture that would democratize and unify their data for all forms of analytics and ML. On top of that, they needed the ability to easily leverage AI and ML capabilities to gather insights and analytics that could be applied throughout their 200+ brands and myriad of use cases, from supply chain optimization to advertising effectiveness.

Lakehouse architecture enables a variety of new data possibilities

Al-Futtaim modernized on Databricks Data Intelligence Platform knowing that it would support their goal of becoming AI-driven. With a single source of truth across their data, divisions across Al-Futtaim are starting to reap the benefits. For example, the automotive division has been able to quickly build ETL pipelines with Delta Lake to fast-track the development of 10 to 15 use cases designed to improve customer engagement and sales. And with Databricks SQL, a wider range of team members can start manipulating and visualizing the data. UdayKumarReddy Srinatham, Data Platform Lead at Al-Futtaim, explains, “The data engineering team is now able to use Databricks SQL to write their own SQL queries, analyze the data, and extract insights that can be applied to customer segmentation use cases for more accurate ML model building. These models are then used to enable targeted marketing campaigns.” User-friendly tooling empowers users to become more autonomous in their data projects, increases adoption to support an AI-centric culture, and allows highly skilled data science teams to focus without distraction. Currently, Al-Futtaim has 50+ Databricks users across data teams and the number is growing quickly.

With a common data layer in Delta Lake, Al-Futtaim is now able to create a single customer view for each of its customers for all divisions to leverage. UdayKumarReddy says, “It’s one of the most important use cases we have from the engineering side. We built the entire customer unification algorithm in Databricks Data Intelligence Platform using different sources from different brands and business units across the organization. And Delta Lake helps to pull it all together for us.” Many use cases will utilize this single view of the customer for contactability, marketing, segmentation, and personalization.

For business stakeholders that need to understand how to shape the business, they are able to access visual dashboards via Power BI to make smarter decisions. Not only do they get a less obstructed view of the entire organization and within business units, but they have access to a huge archive of historical data that creates new opportunities for smarter decision-making. UdayKumarReddy says, “Using 10+ years of previously inaccessible data, analysts have discovered various data sets and joined them to uncover potential glitches in business processes. Based on those findings, auditors have recommended impactful ideas for remediation to the business.” These insights present additional opportunities to increase revenue and streamline inefficiencies.

Empowering the entire organization with data

Since moving to Databricks Data Intelligence Platform, Al-Futtaim is now quickly deploying new use cases throughout the organization, in some instances delivering insights to business stakeholders four times faster than before. The improved data sharing and collaboration enabled via Delta Sharing is a primary accelerator for this improved time-to-market. Dmitriy says, “Collaboration has increased between data divisions because it’s much easier to share customer data generated by any of our brands to create a golden record of our customer. This allows us to create cross-sell campaigns through our global loyalty program to drive more sales.” With these advances, Al-Futtaim has been able to influence supply chain efficiency, marketing and sales, and customer engagement.

For example, they recently productionized an order forecasting and inventory management model for one of their retail businesses, Marks & Spencer. Using historical ordering and inventory data, the business is now able to predict the next year’s seasonal order nine months ahead of time. Using these insights, order planning and preparation requirements are simplified, and loss sale opportunity and inventory holding cost has been reduced by 30%. Al-Futtaim is using these results to help other business units better predict demand and supply requirements based on unique product requirements, and supplier and delivery terms.

Using segmentation and personalization, the division that drives Toyota sales leveraged recommendation engines to market their new UAE automobiles to specific audiences. Taking advantage of all the data Al-Futtaim has across hundreds of business units, they were able to work with Toyota to maximize marketing resources targeting segments most likely to purchase. Throughout the sales funnel, consumer behavior and engagement were tracked to motivate consumers toward purchasing. The use of data and AI in this campaign resulted in a 10% sales increase, as well as delivered actionable takeaways that can be applied for similar results within other Al-Futtaim businesses.

Equipped with unified customer and operational data across their brands, Al-Futtaim’s business units are now able to create an unobstructed view of customer lifetime value. Utilizing this single customer view, businesses can personalize marketing, predict potential churn, increase retention, optimize service delivery, encourage interactions with “Blue,” the Al-Futtaim rewards program, and influence revenue by helping consumers make more informed buying decisions.

Moving forward, as they continue to increase adoption of Databricks Data Intelligence Platform, particularly new features like Unity Catalog for data governance, Al-Futtaim will continue to scale successful data and AI use cases throughout the organization designed to increase revenue and profitability.