Artificial Intelligence

Vacasa On Using AI To Put Predictability In Home Sharing

The heart of home sharing is authenticity. You occupy the homes of actual people who live in cool destinations rather than expensive, impersonal hotels that serve up sanitized versions of local life. The most visible and talked-about brand in home sharing for years has been Airbnb, with a dominant market position and high consumer awareness, making it a household name.

If Airbnb is the face of home sharing, then Vacasa is the smile. The Portland-Oregon-based company has quietly become a rainmaker in the space, raising $319 million from investors in Q4 2019 alone, bringing its private equity take to nearly $527 million to date. That far outpaces similar concepts and bestows the coveted “unicorn” valuation status. But why are VCs still backing a home-sharing concept to the tune of well over $500 million at this point?

PYMNTS spoke to Chief Operations Officer Bob Milne, who explained that key differences between Vacasa and other home-sharing platforms positions the company to profit not just from its rental activities, but from home-sharing economics more broadly.

Home Sharing Strides With AI

From the outset, Vacasa approached short-term rentals with the mindset of a large-scale property management firm. This came into sharp focus when it purchased Wyndham Vacation Rentals last year, adding over 9,000 homes and 50 destinations to its portfolio.

Vacasa has also differentiated with a strategy of opening real estate offices in major markets to line up more and better vacation home rental inventory for a roster of increasingly upmarket guests. During a talk at the 2019 Skift Global Forum, Vacasa founder Eric Breon touted his company’s 10 years of investment in a yield management booking platform and algorithm that maximizes both owner profit and guest value with a powerful artificial intelligence (AI) that calculates optimal rates.

“We’re a property management company, a vacation rentals company, a short-term rental company that really has found the ability to utilize our tech stack in order to become scalable,” Milne told PYMNTS. “Our algorithms, our rates management team and our engineering team are [on the cutting edge] in terms of how we manage rates, how we look at occupancy, how we look at all of the inventory across the Vacasa portfolio, and we’re able to price accordingly.”

Milne notes that the Vacasa platform is uniform globally, regardless of geographical location, which gives all stakeholders extraordinary transparency. “We look at demand, we look at demand velocity and all those things go into how we price,” Milne said, “and we get a better return for our owners. But you couldn’t do it without the tech.”

Beyond The Booking

Beyond the booking itself, many services must be coordinated and delivered to ensure that each home-sharing stay ends in a great experience that generates a positive review.

With property management in its DNA, Vacasa has built exacting tech tools into the backend of its platform. The AI’s predictive capabilities tell staff when a rental property requires a deep cleaning, for example, while also “learning” preferences of return users to be able to match them with ideal properties, especially in cases where first choices aren’t available.

The platform sends notifications to maintenance teams, scoring the quality of cleaning and household services so that homeowners who like the way something was done can ask for and expect a level of consistency. Owners can also access benefits like Vacasa’s popular linen and terrycloth program, review reservations and expenses, all in a unified management portal. And roughly 80 percent of payments to Vacasa homeowners are remitted via ACH direct deposit.

“We’re seeing that the demand for vacation rentals in property management is extremely high. It’s the highest I’ve ever seen it,” said Milne, noting that Vacasa’s mobile app has been engineered for a high-speed, low-friction experience. The app also handles scheduling for cleaners and contractors. Milne said that Vacasa’s AI and machine learning are being used “…to improve the lives of our employees, to increase returns for our homeowners, and then to really ensure that we’re giving guests the best possible experience.”



The How We Shop Report, a PYMNTS collaboration with PayPal, aims to understand how consumers of all ages and incomes are shifting to shopping and paying online in the midst of the COVID-19 pandemic. Our research builds on a series of studies conducted since March, surveying more than 16,000 consumers on how their shopping habits and payments preferences are changing as the crisis continues. This report focuses on our latest survey of 2,163 respondents and examines how their increased appetite for online commerce and digital touchless methods, such as QR codes, contactless cards and digital wallets, is poised to shape the post-pandemic economy.