1Strategy, a Premier Consulting Partner in the Amazon Web Services (AWS) Partner Network (APN), announces that they have developed the first pricing platforms designed specifically for the student-housing industry for Entrata, Inc., one of the multifamily housing industry’s most comprehensive technology providers. Entrata turned to 1Strategy to develop Entrata Student Pricing, an artificial intelligence/machine learning (AI/ML) solution on AWS to determine the optimal pricing for renters of student housing to maximize profits and minimize unrented units (learn more about Entrata’s Student Pricing here).
“Entrata partnered with 1Strategy due to their AI/ML knowledge and expertise within AWS,” 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.”
By leveraging Amazon SageMaker and ML solutions on AWS, 1Strategy designed the Entrata Student Pricing platform as the first AI-powered yield management systems, which utilizes a proprietary algorithm that factors multiple data sets – including historical occupancy and seasonality trends – to accurately forecast occupancy, allowing for more optimized pricing. Entrata announced the product in a recent press release and discussed it in February’s National Apartment Association CampusConnex conference in Orlando, Florida.
The company is 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 2019.
“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.”