With Startups And Big Data, Airbnb Hosts Take The Human Out Of Pricing

Travel planning can be time consuming and frustrating. With constantly fluctuating prices, securing the cheapest flights and hotels seems more like an urban myth.

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But it’s not just big providers that may struggle with setting the right price. Airbnb hosts face the same uncertainty in how to set flexible listing prices in response to changing market demands. The fancy economic term for this dilemma is “dynamic pricing,” and several startups, along with Airbnb itself, have tapped into the market.

Startups Thrive As Pricing Gets Confusing

One of the startups working to bring dynamic pricing to the masses, Wheelhouse, builds its pricing model on “over two dozen factors,” according to its help page. These attributes include records of local rental markets, hotel prices, and recent events, as well as past performances of hosts’ listings, listed photos, additional fees, and amenities of specific properties.

“We calculate the fair price of a given property on a given day, and that is the price for everyone,” Wheelhouse’s CEO Andrew Kitchell wrote in an email to Crunchbase News.

Additionally, Wheelhouse allows hosts to adjust last minute discounts and customize seasonal pricing. It also partners with PredictHQ, a service which indexes and offers predictive analytics on event types like public holidays, sports events, conferences.

In February, Wheelhouse raised a $15.5 million Series A, and it is expanding its pricing algorithm to cover more vacation rental regions.

Among Wheelhouse’s competitors is Beyond Pricing. The CEO of Beyond Pricing, Ian McHenry, explained to Crunchbase News that his company’s machine learning algorithm builds its model on pricing projects it has done in the past for its customers, which amounts to over 150,000 listings so far.

Last year, the company acquired Smart Host, a smaller pricing startup, to consolidate data resources and enhance its pricing algorithm. According to McHenry, Beyond Pricing has tripled in size every year since its launch in 2014.

“We price based on demand,” Beyond Pricing’s McHenry wrote in an email. “No matter where that demand is coming from.”

These pricing startups primarily target hosts on Airbnb, and some claim that its platform has “integrations” with latter. However, Airbnb spokesperson Tim Rathschmidt noted in an email to Crunchbase News that Airbnb does not grant API access to any pricing optimization startups. Rathschmidt also clarified that Airbnb’s own pricing algorithm tool, Smart Pricing, does not take personal data of guests into account. Beyond Pricing and Wheelhouse also made similar statements.

But that doesn’t make Smart Pricing any less of an inconvenience to startups.

Airbnb’s Own Pricing Tool

Airbnb started to develop its own intelligent pricing algorithm in 2012. The service is currently offered to hosts free of charge. When hosts turn the Smart Pricing option on, their listing prices will be updated automatically.

According to Airbnb’s website, Smart Pricing bases their algorithm on over 70 factors. Higher prices are generated when the listings are viewed more frequently, when more searches appear in the neighborhoods, or when the listings receive more positive reviews.

Interestingly, on the Airbnb community center, many hosts recall their experience with Smart Pricing as being not so pleasant. Some mentioned that Smart Pricing consistently suggests them to lower their listing prices, while they feel that their listings are underestimated by the suggestions.

However, this may be just the result of the agenda that Smart Pricing is following. As Rathschmidt pointed out: “The main aim of Smart Pricing is to get hosts booked.”

Nevertheless, Rathschmidt emphasizes that hosts are always the ultimate decision makers regarding their listing prices.

“Hosts always have control,” Rathschmidt told Crunchbase News. “So even if Smart Pricing suggests a lower price, they can charge whatever they want.”

Data Stored Today Could Be Used Tomorrow

While Airbnb and the startups built around the platform do not use personal data for the purposes of dynamic pricing, there are potential concerns about how far these models will go.

For instance, Uber has used machine learning to charge riders based on the routes they are taking. Business Insider reported “that the new pricing seems to target people who are well-off and already willing to pay pricier UberX fares.” It has also been reported that Uber has a new algorithm that can determine users’ intoxication level. Some worry that this new function will enable Uber to take advantage of drunk passengers and charge them with higher prices.

For now, however, developing a more personalized pricing algorithm is hampered in some countries by government regulations and societal norms. Regardless, with the advent of AI and big data, the boundary between demand specific dynamic pricing and a user-behavior based pricing is thin. How long can startups and rental sites alike hold out before leveraging this technology to further inform their pricing strategy remains to be seen.