India-based Oyo Hotels & Homes has acquired Danamica to leverage the Copenhagen-based data science company’s machine learning and business intelligence capabilities, particularly in dynamic pricing, in its expansion of business in Europe.
Earlier in August, the company had invested €300 million (US$330 million) in the vacation homes business in Europe, with a special focus on strengthening the relationship with homeowners and enabling them with the resources, including technology investments, required to deliver chic hospitality experiences.
With the acquisition of Danamica, Oyo says it will be able to drive top-line growth by leveraging dynamic pricing across all its brands – Oyo Home, Belvilla and DanCenter. Additionally, Oyo and its real estate partners around the world will benefit using data sciences for improved yield. Starting with Europe, Danamica’s technology innovations will benefit Oyo’s global vacation homes business.
Maninder Gulati, global head, Oyo Vacation and Urban Homes, & chief strategy officer, Oyo Hotels & Homes, said that the Danamica acquisition “will help us be more accurate with pricing, leading to higher efficiencies and yield for our real estate owners and value for money for our millions of global guests”.
He added: “Data sciences across pricing, AI, and imaging sciences have been a cornerstone of Oyo’s proprietary revenue enhancement technology. It is also a huge missing piece in the way traditional vacation rentals industry is run. We are glad to have found Danamica, which has built expertise in these areas.”
With the implementation of Danamica’s machine learning-enabled pricing and revenue management, customers will be able to book a vacation home at the best price.
Similar to airlines and ride-sharing companies, Oyo has introduced dynamic pricing in the hospitality industry to create a level-playing ground even for an independent or small hotelier or homeowner. Oyo’s pricing, inventory allocation and revenue management are driven by a machine learning-based algorithm for prediction and dynamic pricing.
The algorithm analyses 144,000 data points every hour and makes 60 million price changes every day with a prediction accuracy of 97 per cent. It allows each hotel to drive max RevPAR based on its micro-location.
It allows pricing to adjust dynamically to supply and demand. In peak times, pricing adjusts to deliver high RevPAR, and in low times, it goes down to allow for maximum customers to experience the product while increasing overall yield for owners.
