AWS AI/ML - Dynamic Pricing Solution
A Story of Owning Change
About Entrata
Entrata, founded in 2003, is the only comprehensive property management software provider with a single-login, open-access Platform as a Service (PaaS) system. Offering a wide variety of online tools including websites, mobile apps, payments, lease signing, accounting, and resident management, Entrata® PaaS currently serves more than 20,000 apartment communities nationwide. Entrata’s open API and superior selection of third-party integrations offer management companies the freedom to choose the technology and software that best fit their needs.
With the assistance of 1Strategy and by utilizing Amazon SageMaker, Entrata can… focus on people first, instead of performing rote behind-the-scenes guessing of price recommendations.
Ryan Byrd, VP of Engineering, Entrata
The Challenge
Entrata provides property management software to the multifamily housing industry and for more Top 25 student housing properties than any other provider. For college students, housing presents challenges that students need to consider before they decide where to live each semester. Chase Harrington, President and Chief Operating Officer at Entrata said, “If moving is stressful for students, imagine how it is for onsite staff who deal with hundreds of resident move-ins.” Entrata’s clients currently rely on individual pricing decisions and lack a data-driven pricing tool that can view historical occupancy trends and/or seasonality.
Entrata’s challenge was to develop an artificial intelligence/machine learning (AI/ML) tool that is designed for the student housing industry, enabling their customers to predict occupancy levels to optimize the price to offer potential renters of student housing.
Why Amazon Web Services
Entrata was already benefiting from the use of Amazon Web Services (AWS) for various data needs. However, they were interested in determining a solution—leveraging AWS machine learning services—that integrated with their existing AWS infrastructure and would be flexible enough to address Entrata’s need to deliver accurate forecasting to maximize profits for their customers while minimizing unrented units.
To address this, Entrata engaged with 1Strategy, an AWS Premier Consulting Partner, to develop an AI/ML solution on AWS which will enable their customers to have a dynamic pricing engine for their application.
“Entrata partnered with 1Strategy due to their AI/ML knowledge and expertise within the AWS ecosystem,” said Ryan Byrd, VP of Engineering, Entrata. “With the assistance of 1Strategy, we were able to develop an ML solution utilizing Amazon SageMaker that will have a real impact upon both the student and conventional property industries.”
The Benefits
By leveraging the AWS Partner Proof of Concept (POC) program and Amazon SageMaker, 1Strategy developed the first-ever pricing platform designed specifically for the student housing industry for Entrata. The Entrata Student Pricing platform is the first AI-powered yield management system which utilizes an inference model built in SageMaker that factors multiple data sets and a user-driven strategy to predict occupancy rates. AWS Machine Learning will train the pricing model on various data-driven relationships and the learned output will serve as the primary driver of price recommendations.
Amazon SageMaker is a managed machine learning service that allows Entrata to quickly build and train ML models and deploy them at any scale directly into a hosted environment. 1Strategy’s engagement consisted of building an ETL (extract, transform, load) and ML forecasting engine on AWS to provide dynamic pricing recommendations for customers (student housing properties). The ML forecasting engine was designed using Amazon SageMaker, Amazon API Gateway, Amazon Relational Database Service (RDS), AWS Lambda, Amazon S3, and AWS Glue.
In the preceding figure, AWS Glue, a fully managed ETL service, extracts historical data from Amazon RDS into Amazon S3. This data is consumed within Amazon SageMaker and forecasts are written to an output bucket in Amazon S3. Entrata’s applications consumes this data request via API Gateway which triggers Lambdas to deliver the most relevant forecast for a given customer property.
Entrata Student Pricing is also designed to work seamlessly with the company’s product for conventional apartment homes, Entrata Pricing, enabling apartment operators with both student and conventional properties to easily utilize both products. Entrata is now on track to beta test the Entrata Student Pricing platform with several student housing properties with the intent to make the platform generally available by early Q3.
"The impact is far ranging—and positive; automating AI/ML back-office functions frees property management to focus on people first, instead of performing rote behind-the-scenes guessing of price recommendations."
“With the assistance of 1Strategy and by utilizing Amazon SageMaker, Entrata can streamline the flow of reliable competitive information, deepening our revenue-optimization offerings to our base of more than 20,000 apartment communities nationwide,” said Byrd. “The impact is far ranging—and positive; automating AI/ML back-office functions frees property management to focus on people first, instead of performing rote behind-the-scenes guessing of price recommendations.”
Now, Entrata employs an ML-driven model that utilizes historical occupancy and seasonality trends to accurately forecast occupancy, allowing for more optimize pricing.
The work described in this engagement was originally completed by 1Strategy, a TEKsystems Global Services company acquired in 2019. As of June 2023, 1Strategy has fully integrated with TEKsystems Global Services to continue to deliver AWS expertise to customers. Learn more about our AWS solutions.
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