Radiant1 Founder and CEO Apichai Sakulsureeyadej
Before the COVID-19 pandemic outbreak, hotelier Apichai Sakulsureeyadej stepped in to help his family oversee the hotel business and understand the lack of data usage in crucial decision-making processes. A serial entrepreneur who spent the last two decades in big data, Sakulsureeyadej quickly realised that hotels, like the airline industry, might earn more revenue with dynamic pricing.
“A hotel’s core revenue source is room bookings. I experimented with the use of multiple data sets to influence room pricing. This led to a visible uplift in the business’s revenue,” he shares.
That motivated him to start Radiant1.
Also Read: Radiant1 raises funding for its AI solution that helps hotels maximise revenue
Incorporated in Singapore in 2019, Radiant1 has developed an AI-powered SaaS solution that assists hotels in maximising revenue. The tool uses machine learning algorithms to analyse factors, including real-time demand, types of properties, and travel behaviour, to provide optimised room rate pricing on a real-time basis and maximise total revenue for the customer. It leverages both external and internal data and analyses it multi-dimensional.
“Many factors influence the hotel industry, such as seasons, events, holidays, economy, etc. Radiant1 automates the ability to understand how each factor affects demand. As a result, it can decide which combinations would be most effective to determine the right price,” he adds.
Estimates show that the Asian hotel market is nearly US$200 billion annually in transaction volume. On average, each hotel faces an opportunity loss of more than 30 per cent when not using revenue management.
“Nearly 90 per cent of hotels in Southeast Asia don’t use any form of revenue management. They believe in having basic operational technology, such as reservation/check-in management, and working with online distribution. They have generally not yet digitised their operation, unlike the airlines,” he reveals.
“On the other hand, chain-managed hotels in the West widely use revenue management, yielding higher revenues. Radiant1 believes that every hotel should have revenue management as a mandatory tool,” he remarks.
According to Sakulsureeyadej, Radiant1’s USP lies in its ability to synthesise multiple datasets and turn those into actionable recommendations and automated action to set pricing and recommend the channels for sales of room nights. This helps in automating how hotels are priced and distributed.
The startup has introduced a flexible pricing scheme with monthly fixed fees and variable charging models based on the customer’s needs.
The company says it has assisted all types of properties to optimise their revenues while keeping an eye on their bottom line. Its customers include hotels with global chain brands, independent and boutique hotel chains, hotel management companies, and short-stay operators.
Post-pandemic, Radiant1 claims to have seen robust growth; the business has grown manifold since mid-2022, coinciding with the widespread reopening of borders. In addition to its presence in Thailand, it expanded its footprint into Malaysia and Indonesia.
The startup recently raised an undisclosed sum in a pre-Series A round anchored by Monkʼs Hill Ventures to double down in the existing markets, expand into new Asian countries, hire additional tech resources, and expand the product suite.
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“We plan to further penetrate into our existing markets, such as Indonesia, Malaysia, and Thailand, by growing the sales team and growing the cities we target in each country,” he adds.
Radiant1 has also begun experimenting with Generative AI to hyper-personalise customer engagement. “We strongly believe that a much deeper understanding of customer behaviour to build personalised offerings can lead to higher revenues. It is equally important to understand demand. Often, they go hand in hand. Radiant1 is on a mission to build technology that obtains and uses these relevant data to optimise different parts of the hotel, eventually leading to better revenue,” he notes.
While Generative AI is the future, he believes that Generative AI needs to be regulated by ethical standards. “We need to adhere to the guidelines of the Personal Data Protection Act. It is a good start while combining it with a more comprehensive approach.”
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Image Credit: Radiant1.
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