Closing deals with better customer insights
Increase in lead-to-customer conversion ratio
As India’s real estate market continues to explode with a seismic rise in wealth and the rapid adoption of technology, Xanadu Realty has positioned itself at the forefront of this transformative wave with a dedicated workforce of over 700 professionals managing real estate inventory across India. Due to the lack of a central data platform, Xanadu struggled with data fragmentation, preventing a unified view of customer information needed for efficient data processing and analysis. Additionally, remote sales teams lacked the capabilities to extract valuable insights from the data, impacting the quality and consistency of customer interactions. To address these issues, Xanadu built a more data-centric strategy around the Databricks Data Intelligence Platform — putting them in a prime position to optimize operational processes and redefine the landscape of real estate sales and marketing.
Data silos block the delivery of actionable insights to sales
The Indian real estate market has evolved over the years as rapid technological advancements and shifting consumer preferences have transformed the industry as a whole. Xanadu’s mission is to revolutionize real estate sales and marketing by leveraging cutting-edge technology to resolve a pressing issue — the growing complexity of data management and the need for informed decision-making in a dynamic market environment. However, with an environment of fractured data sources and applications, the goal of centralizing data to extract meaningful insights from customer interactions was out of reach, causing Xanadu to struggle with gaining the comprehensive insights needed to deliver a consistent experience across various touchpoints.
With vast amounts of unstructured data generated from customer interactions, Xanadu’s sales teams spent substantial time on leads that might not have led to successful conversions. The absence of a structured approach to data management further exacerbated this issue. "Our key objective was to empower our sales managers with better insights, improving our conversion ratio from customer visits to bookings," explained Vijay Kumar, the CTO at Xanadu. "But our isolated data repositories fragmented information and prevented us from achieving a unified view of our customer data."
Xanadu’s urgent need to overcome data silos and extract insights from unstructured data required a modern data platform that centralizes all data into a single view, streamlines data management and empowers the sales teams with data-driven decision-making capabilities to better support customers and drive more sales.
Achieving a lofty vision through the lakehouse architecture
In an effort to empower their sales managers with more informed conversations and gain a deeper understanding of customer needs, Xanadu embarked on a greenfield effort to bring their vision to life. They partnered with Exponentia.ai to develop a custom application called Xanadu Decision Engine (XDE)™. This application was designed to facilitate conversational analytics, performance management and AI-driven virtual assistance for the sales team. To help them overcome their data-related challenges and drive meaningful transformation, the expert team at Exponentia.ai recommended that the Databricks Data Intelligence Platform serve as XDE’s underlying infrastructure, which would simplify data integration and access, and also accelerate analytics and AI innovations.
"Central to Xanadu’s strategy was consolidating information from various sources, including multiple sites and customer interactions, into one centralized repository," said Kumar. "With Databricks Data Intelligence Platform, we are able to unlock comprehensive analytics that support a range of customer-related use cases."
Delta Lake has been instrumental in providing data consistency and integrity across various stages of the data pipeline. The feature store has streamlined feature sharing and reuse, enhancing productivity by eliminating the need to recreate features for different models. As Xanadu continues to delve into AI, MLflow has played a crucial role in managing the machine learning lifecycle — allowing them to gain a significant edge in a highly competitive real estate market through improved lead scoring and enhanced customer interactions.
Lastly, Xanadu is able to feed data directly to Power BI — providing comprehensive visibility into sales performance, customer interactions and marketing campaign effectiveness through reports and interactive dashboards. "With Databricks powering XDE, we have a seamless integration across our various data sources and systems," explained Kumar. "Now data flows smoothly between systems, enabling efficient data processing and the ability to harness analytics and AI."
Paving the way to a better real estate experience
Xanadu’s journey with the Databricks Data Intelligence Platform has led to significantly improved conversion ratios, enhancing lead scoring and customer propensity to buy. The lakehouse architecture has provided several advantages over traditional data warehouses: It provides a holistic customer view, optimizes lead qualification and scoring in near real-time, facilitates data-driven decision-making and has given Xanadu the means to explore AI-centric use cases from recommendation engines to LLM-powered chatbots.
Since implementing the Databricks Data Intelligence Platform, Xanadu has seen a 25% increase in conversion ratios — streamlining their sales operations through conversational analytics, lead prioritization and AI-driven insights. With a more comprehensive view of customer interactions, they’ve seen a jump in customer engagement and satisfaction. With an eye on the future, Xanadu’s roadmap includes the development of new ML models focused on expanding their conversational analytics capabilities and increasing their reliance on generative AI. "With Databricks Data Intelligence Platform, we’re poised for further growth as we roll out deeper insights and new solutions to improve customer experiences," concluded Kumar.
