H2O.ai Case Studies Increasing Effectiveness of Real Estate Marketing with H2O.ai

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	Increasing Effectiveness of Real Estate Marketing with H2O.ai H2O.ai

Increasing Effectiveness of Real Estate Marketing with H2O.ai

H2O.ai

Technology Category	Analytics & Modeling - Machine Learning Analytics & Modeling - Predictive Analytics Application Infrastructure & Middleware - Data Exchange & Integration
Applicable Functions	Sales & Marketing
Use Cases	Predictive Maintenance
Services	Data Science Services System Integration
Challenge	G5, Inc., a leading marketing optimization company for the real estate industry, was facing a challenge with its lead generation process. The company found that only 14% of its call leads were productive, resulting in low job satisfaction, high turnover for leasing agents, and low conversion numbers. G5 wanted to solve this by using machine learning to identify stronger leads that would more likely result in sales. However, the company didn’t have dedicated data science resources to create the needed machine learning models. The implementation of machine learning could prove to be time consuming, expensive, and a barrier to innovation. Read More
About Customer	G5, Inc. is a leading marketing optimization company for the real estate industry. Through its Intelligent Marketing Cloud, G5 helps customers optimize advertising and lead management to increase marketing efficiency and effectiveness. G5 works with more than 7,000 properties in the United States and Canada. Its customers are leasing companies for large apartments, senior living, and self storage complexes. G5 employs leasing agents who follow up on leads through phone calls. The company's goal is to increase the productivity of these leads and improve the efficiency of their leasing agents. Read More
Solution	G5 found that H2O Driverless AI addressed its challenges with identifying the difference between a productive lead and a dead end. The company built data sets consisting of 100,000 lead call transcripts and their scores, stored these data sets on Amazon S3, and powered its machine learning with the compute capacities of Amazon EC2. G5 then used H2O Word2Vec to analyze the data sets and generate a table of features to serve as the underpinnings of the emerging machine learning model. Having a preliminary matrix of the model, G5 used H2O Driverless AI to further engineer the model’s features, and train it using the existing data sets. As a result, the model identified high-quality leads with increasing accuracy. Lastly, G5 needed to make its results production-ready and usable by leasing agents. To do so, the company ran the modelling results on AWS Lambda and passed them through H2O Driverless AI’s automatic scoring pipelines. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Analytics & Modeling - Predictive Analytics

Application Infrastructure & Middleware - Data Exchange & Integration

Applicable Functions

Sales & Marketing

Use Cases

Predictive Maintenance

Services

Data Science Services

System Integration

Challenge

G5, Inc., a leading marketing optimization company for the real estate industry, was facing a challenge with its lead generation process. The company found that only 14% of its call leads were productive, resulting in low job satisfaction, high turnover for leasing agents, and low conversion numbers. G5 wanted to solve this by using machine learning to identify stronger leads that would more likely result in sales. However, the company didn’t have dedicated data science resources to create the needed machine learning models. The implementation of machine learning could prove to be time consuming, expensive, and a barrier to innovation.

About Customer

G5, Inc. is a leading marketing optimization company for the real estate industry. Through its Intelligent Marketing Cloud, G5 helps customers optimize advertising and lead management to increase marketing efficiency and effectiveness. G5 works with more than 7,000 properties in the United States and Canada. Its customers are leasing companies for large apartments, senior living, and self storage complexes. G5 employs leasing agents who follow up on leads through phone calls. The company's goal is to increase the productivity of these leads and improve the efficiency of their leasing agents.

Solution

G5 found that H2O Driverless AI addressed its challenges with identifying the difference between a productive lead and a dead end. The company built data sets consisting of 100,000 lead call transcripts and their scores, stored these data sets on Amazon S3, and powered its machine learning with the compute capacities of Amazon EC2. G5 then used H2O Word2Vec to analyze the data sets and generate a table of features to serve as the underpinnings of the emerging machine learning model. Having a preliminary matrix of the model, G5 used H2O Driverless AI to further engineer the model’s features, and train it using the existing data sets. As a result, the model identified high-quality leads with increasing accuracy. Lastly, G5 needed to make its results production-ready and usable by leasing agents. To do so, the company ran the modelling results on AWS Lambda and passed them through H2O Driverless AI’s automatic scoring pipelines.

Impact #1	Model development time reduced by 80% using H2O Driverless AI.
Impact #2	The G5 team was able to deliver the work of two additional senior technical employees without any dedicated data science or deployment resources.
Impact #3	Leasing agents are better equipped to meet their sales quotas, leading to significant positive impact on job satisfaction and reducing agent turnover.

Impact #1

Model development time reduced by 80% using H2O Driverless AI.

Impact #2

The G5 team was able to deliver the work of two additional senior technical employees without any dedicated data science or deployment resources.

Impact #3

Leasing agents are better equipped to meet their sales quotas, leading to significant positive impact on job satisfaction and reducing agent turnover.

Benefit #1	Increased the accuracy of lead scoring to over 95%.
Benefit #2	Leasing agents connect with qualified leads 85% of the time, a substantial improvement from the previous 14% benchmark.
Benefit #3	Customers are saving $1.5M/month.

Benefit #1

Increased the accuracy of lead scoring to over 95%.

Benefit #2

Leasing agents connect with qualified leads 85% of the time, a substantial improvement from the previous 14% benchmark.

Benefit #3

Customers are saving $1.5M/month.

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Overview

Increasing Effectiveness of Real Estate Marketing with H2O.ai

Operational Impact

Quantitative Benefit