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Title
Helping more people find their next dream home
…o Login Contact Us Try Databricks Customer Stories / Housing-com CUSTOMER STORY Helping more people find their next dream home 10%–15% Reduction in time to insight 20% Increase in team productivity 50% Lowe…
Description
Housing.com, a real estate platform, moved from a cloud data warehouse to the Databricks Data + AI Platform, using Delta Lake and MLflow to train and deploy machine learning models for personalized property recommendations and fraud detection; additional ML models for pricing prediction and demand forecasting are currently under development. The fraud detection ML model lowered fraudulent credit card transactions by 0.05%, the recommendation engine drove a 5.5% increase in prospect-to-lead conversion, and the company cut total cost of ownership by 50% while reducing ML and pipeline deployment time by 10-15%.
…L deployment now takes one less week of manual work. Speaking of ML deployment, the ML model that Housing.com created to detect fraudulent credit card transactions lowered such instances by 0.05%, increasing customer satisfaction and protecting the company’s brand image. Aside from more efficient ML deployments, the real estate business has also obs…
Company
Housing.com
…ech innovations, the amount of data has become more of a hindrance than a help. Since Housing.com wanted to continue to be the first choice of their consumers and partners in renting, buying, selling or financing a home, the company had to rethink their approach to data and bring it up to par with…
Problem
Data silos across teams threatened accuracy, and Housing.com struggled with pricing accuracy, demand forecasting, personalization and fraud detection as data volumes scaled; moving away from a cloud data warehouse, the cost of computing was proving far more expensive than storage.
…e amount of data and touchpoints expanded exponentially. To make matters worse, certain Housing.com teams were creating isolated data in silos that did not correspond to the data other teams were producing, posing a threat to data accuracy. This hindered the company’s productivity, innovation and scalability. Pricing a…
Solution
Housing.com moved from its cloud data warehouse to the Databricks Data + AI Platform (paired with AWS), using Delta Lake as the foundational storage layer, MLflow to train and deploy ML models, Unity Catalog for governance, and Tableau for BI/reporting, to power a property recommendation engine and fraud detection; ML models for pricing prediction and demand forecasting are still under development.
…ze their data and insights with partners to grow their collaborative ecosystem. They also used Unity Catalog to form a central point of access across all of Housing.com’s workspaces, helping maintain governance of the Databricks Data + AI Platform and its open source integrations. As a final cherry on top, Databricks’ integration with Tableau — a data visuali…
Business value
Housing.com cut total cost of ownership by 50%, reduced pipeline/ML deployment time by 10-15% (saving one week of manual ML deployment work), increased team productivity/collaboration speed by 20%, lowered fraudulent credit card transactions by 0.05%, and increased the prospect-to-lead conversion rate by 5.5% via the recommendation engine.
…L models. Due to the improvement of their data storage, sharing and activation, Housing.com also decreased the deployment time of pipelines, reports and ML models by 10% to 15%. For example, ML deployment now takes one less week of manual work. Speaking of…
Industry
Real Estate
…erty and homeowner/renter information to data about finances, taxes and trends. As real estate continues to mature digitally with PropTech innovations, the amount of data has become more of a hindrance than a help. Since Housing.c…
Technology
Delta Lake, Unity Catalog, MLflow, Delta Sharing, Tableau
…here to support Housing.com however it can. Share this post Details Cloud : AWS Product : Delta Lake , Unity Catalog Ready to get started? Try Databricks for free Learn more about our product Talk…
…, leveraging MLflow to train and deploy new innovative ML models to production. The forward-thinking brand also planned to use Delta Sharing to democratize their data and insights with partners to grow their collaborative ecosystem. They also use…
…Data + AI Platform and its open source integrations. As a final cherry on top, Databricks’ integration with Tableau — a data visualization solution Housing.com had previously implemented — would handle business intelligence and reporting, using the new ML models dep…
Use case type
Personalisation
…re time on market analysis, business strategy and customer engagement. In fact, part of Housing.com’s engagement strategy includes improved personalization around the company’s recommendation engine that suggests properties, and with improved data accuracy and business intelligence, the real estate com…
Headline outcome
…eam home 10%–15% Reduction in time to insight 20% Increase in team productivity 50% Lower TCO compared to cloud data warehouse Even before “big data,” data had always been important in real estate, encompas…
AI capabilities
Fraud & Anomaly Detection, Recommendation & Personalization
…L deployment now takes one less week of manual work. Speaking of ML deployment, the ML model that Housing.com created to detect fraudulent credit card transactions lowered such instances by 0.05%, increasing customer satisfaction and protectin…
Deployment model
cloud
…g.com began to evaluate new data solutions and ML platform options. Ultimately, the real estate company decided on the Databricks Data + AI Platform — which also paired well with AWS — as an all-in-one solution to accommodate their diverse teams of technical and…
Deployment options
cloud
…g.com began to evaluate new data solutions and ML platform options. Ultimately, the real estate company decided on the Databricks Data + AI Platform — which also paired well with AWS — as an all-in-one solution to accommodate their diverse teams of technical and…
