IndiaReal estate2023 – ongoingXanadu Realty
Lead scoring and AI sales assistant for real-estate sales teams
Xanadu Realty raised its lead-to-customer conversion by 25% with machine-learning lead scoring
Problem
Xanadu Realty's customer data sat in separate repositories with no single view of each buyer. Sales teams spent time on leads that often did not convert. Remote sales staff could not easily pull insights to keep customer conversations consistent.
Approach
Xanadu consolidated data from its sites and customer interactions on the Databricks platform. With the partner Exponentia.ai it built the Xanadu Decision Engine, a custom application for sales teams. It offers conversational analytics, performance management and virtual assistance, and uses improved lead scoring models managed with MLflow.
Results
Takeaway
Ranking leads by likelihood to convert pointed sales staff at the buyers most worth their time. The company planned further models for conversational analytics, but gave no results for them.
Categories
- Industry
- Real estate
- Business function
- Marketing and sales
- Innovation type
- Process innovation
- Adoption
- Partner co-development
- Evidence
- Vendor case study
Sources
Source summaries
Databricks describes how Xanadu Realty moved fragmented sales and customer data onto its platform and built a decision engine with Exponentia.ai. The engine includes lead scoring and an AI assistant for sales teams. The page reports a 25% rise in the lead-to-customer conversion ratio.
Full details are in the original sources.
