Intelligent Use of Data Intelligence Solutions

– Hotelier India


Rakesh Ramchandani, VP and Head-Travel & Hospitality, Cybage

Hoteliers need to leverage technology to accurately predict upcoming demand and maintain a competitive and profitable business in light of changing trends

Seamless and accurate predictions have been a desideratum of the travel and hospitality industry for a very long time. The only reliable way to get accurate predictions is through data. But the high volume of data generation across multiple systems within the industry makes it a classic analytical problem.

According to Rakesh Ramchandani, VP and Head-Travel & Hospitality, Cybage, the industry can expect good insights on travel trends if they combine the current analytical points with macro-economic factors that drive the local economy. Advanced technology can play a crucial role in overcoming such challenges.

He explains how with cloud (Azure, AWS, and GCP) adapting to warehousing, analytics and graphical presentation of data have become faster, easier, and cost-effective. Opting to integrate with various data sources and effectively using the analytics infrastructure can enable the industry to maximise the impact of their digital or even legacy promotional campaigns.

There is a lot of uncertainty associated with analysing historical performance analysis given how COVID-19 upended all predictions. How can hotels get real-time metrics to better determine future market demand projections?

Every organisation has an oasis of data specific to their businesses that are constantly processed and analysed to create a roadmap for the future. COVID created an unforeseen challenge for the hospitality and travel industry wherein the data oasis went dry. The data available in bits and pieces creates a new problem like Data Rich Insight Poor (DRIP).

A new forecasting framework is essential to overcome such challenges, investigate the new traveller behaviour and adapt to a post-pandemic travel era. Apart from the legacy data like booking, travel behaviour, and events, this framework should consider unforeseen travel patterns to anticipate the demand. For example, travel patterns observed during epidemiological factors like COVID-19 and macroeconomics factors like travel bans, new outbreaks, infection rates, and global vaccination progress per capita population.

OTAs, GDSs, airlines and meta review sites are some of the top funnel sources for hotel companies. However, aggregating data from such a myriad range can be time consuming and complex. How can this be simplified so hotels have a better grip on a traveller’s intent and can monitor the industry’s recovery by city and region?

As per a recent Phocuswright report, travel will not be identical in the post-COVID era. It indicates that hotels have to look into new data points and reprioritise their distribution strategies. Bookings distribution among channels has changed with more travellers calling hotels directly to book, inquire about hygiene protocols and understand reservation and cancellation policies. Hence, direct channel bookings grew by 3% and represented 45% of total room revenue.

At present, travellers are making reservations promptly within the days of arrival, making it almost unimaginable for revenue managers to use just on-the-books data to predict demand. Revenue managers are scanning through new data sets, attempting to get a grip on expected demand.

Rather than being reactive, revenue managers are now looking higher up in the explorer funnel, endeavouring to understand traveller intent way before a confirmed booking. These higher-funnel data sets like behaviour patterns and flight bookings help them get better insights into traveller intent.

Hotels today can subscribe to data and reports offered by organisations at the top of the funnel, providing daily insights into traveller intent and the evolving travel conditions regionally. Alternately, hotel groups can integrate with various data sources and build a solution that can help predict demand more effectively. Along with the human decision capabilities, these solutions should have the flavour of Machine Learning and Artificial Intelligence to automate the price configurations in a controlled manner.

Direct channel bookings grew by 3% and represented 45% of total room revenue.

How can hoteliers build intuitive tech capabilities to instantly identify any new market opportunities before the time window to effectively respond is missed?

A leading market report suggests that more than 70% of consumers in 39 nations have changed travel behaviours since the onset of the pandemic. Even though travellers are researching well in advance, booking timelines have shrunk. They're changing brands, platforms and selecting travel places depending on the prevailing conditions.

This change forced the B2C business, which is leading the pandemic recovery path, to emphasize understanding travelers at a far more granular level. An opportunity window now exists in the pre-booking lifecycle and during the stay at the property. It increases the importance of engaging the traveler effectively during the discovery phase and the visit. Tools like GMS, DAM, CRS, PMS, etc., along with analytical tools (backed by historical and forward-looking data), should be used to engage guests during the pre-booking process.

Effective property solutions like self-checking, in-property mobile apps, POS solutions, Beacons, etc., need to be utilised for guest satisfaction and revenue generation via cross-selling and upselling opportunities. These technologies can equip hotels with effective digital strategies and help fill in the gaps during various stages of a guest journey. The B2B companies can extend these learning from B2C as businesses gear up to travel and meet face to face in the near future.

How can these initiatives help hoteliers adjust their business strategies to ensure enhanced revenue opportunities, irrespective of the prevalent conditions?

Today's current global situation is a unique challenge the hospitality industry is facing, and hoteliers are vying to attract travellers. Effective use of GMS applications will help hotels reach the traveller at the right time, place, and product/package. Additionally, it can help hotels optimize the cost of distribution and support in effectively targeting travellers looking out for leisure.

Irrespective of the current circumstances, there will be a sense of awareness and consciousness about safety amongst the travellers. They will look out for hotels that emphasise sanitisation and cleanliness, contactless services, self-check-in kiosks or digital keys, free cancellations, etc. Appropriate showcasing of digital assets related to initiatives taken for traveler safety through appropriate DAM tools will determine how hotels position themselves in the market to reach out to such customers.

Digitisation and use of analytics backed by historical and forward-looking data points and coupled with the capabilities of AI and ML will be a long-term business strategy for the hotel industry, and it will not only serve the current need but also help them to be on their toes for any unpredicted events or situations.

Hotels will have to use the in-property effectively and in-room solutions, e.g., POS integrated with PMS, mobile apps for in-room services, integrations with partner service providers, and many more. It will help hotels see a steep up-trending line on their non-room revenue graph.

Property solutions like self-checking, in-property mobile apps, POS solutions, beacons, etc., need to be utilised for guest satisfaction and revenue generation via cross-selling and upselling opportunities

How can such forward-looking data tools help them successfully navigate their business depending on the prevalent market conditions?

By large, hotels rely on their historical data and their competitor’s data to fine-tune the rates and maximise revenue. Recent advancements in revenue management tools now include the forward-looking data points relevant to rates and occupancy levels.

While this has helped hoteliers further maximise revenue, the data vacuum created by the pandemic made it irrelevant. There was a rise in short-term historical data and forward-looking data captured along with long-term data points. Additionally, new forward-looking parameters related to external macroeconomics factors have also become part of the system. It continues to help hotels consider both exogenous and endogenous attributes for rate optimisation and revenue maximisation.

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