The unprecedented impact of the coronavirus pandemic has been deeply felt by the global hotel industry.

NB: This is an article from Fornova

Travel restrictions resulted in the biggest drops in occupancy on record across all regions and recovery is proving to be slow.

But even before COVID-19, the emergence of giant technology companies as travel & hospitality players, from Google to Airbnb and the OTAs, had already been presenting hotels with a unique series of challenges; hotels have been dealing with altered guest expectations, while revenue optimization professionals specifically are having to decide which new technologies can give them the edge against their comp set and, until the market recovers from the effects of the pandemic, help them gain a bigger piece of a smaller pie.

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While many academics and thought leaders had been advocating it for years, it has taken the COVID-19 crisis for the revenue practice to start evolving from the traditional rooms-revenue model towards a total revenue management approach. Independent hotels and chains alike have been attempting to optimize their revenue with day-use services and some have even opened the hotel to local guests for ancillary services. It makes sense; with international tourist arrivals having been reduced to zero and in some cases even nationals forbidden to venture out of their city due to travel restrictions, hotels need to cater to a different kind of clientele, e.g. people who live close by and who are maybe interested in booking a room only for a few hours during the day to use it as their home office, or are wanting to use one of the hotel services without staying overnight (e.g. the parking, the gym or the spa, etc).

Improvements in business intelligence and data analytics have equipped tech-savvy revenue managers with tools that connect property management, central reservation, F&B and other – formerly siloed – systems and provide a unified view, a single version of truth in other words. By integrating all revenue generating functions into easy to read dashboards, the revenue manager can process information in real time, share this information with other departments, tailor reports and crucially produce better forecasts.

The latest advances in AI and machine learning are also driving revenue management’s evolution from tactical (deciding static room rates) to strategic (generating demand and helping the whole organization manage its revenues). On the one hand, by integrating multiple data sources beyond just the historic data that resides in a hotel’s property management system, and by using advanced algorithms to process all that data, the most advanced revenue management solutions can now more accurately forecast demand. On the other hand, these systems are also enabling dynamic pricing, which contrary to static rates, allows hotels to capture incremental revenue by adjusting rates on a daily or even hourly basis if up-to-the-minute market information reveals the need for these changes. Hence revenue managers can offer the right room at the right price to the right customer.

As the majority of RMS can make these data-driven pricing decisions 365 days in advance, and automatically update those rates multiple times a day, revenue managers who use them do not need to spend the majority of their time number crunching on excel spreadsheets; they can instead focus on coming up with new strategies for optimizing revenue and increasing profit.

Another trend worth mentioning is the convergence of revenue management and digital marketing. Up until recently, it was the responsibility of marketing to generate demand by using promotions to create awareness and drive traffic to the hotel’s preferred distribution channel. Revenue management would intervene at a later stage and use pricing and availability as mechanisms to convert said traffic into bookings. Nowadays, it is accepted that revenue management can stimulate or restrict demand way further up the funnel, because revenue managers can use the data they have available to understand which consumer segments are more likely to book rooms at any given time, and help the marketing team divert its efforts and budget to target those segments in the first place.

Looking back, 2020 was the year when revenue management was reduced to revenue survival. As demand collapsed from the spring onwards, many hotels were forced to close and thousands of revenue optimization professionals were furloughed or made redundant. In many cases, revenue management became a centralised function, or whereas in the past each property in a chain would have a dedicated revenue manager, now hotels were grouped into clusters with one revenue manager responsible for multiple properties or even a whole region. These efficiencies in scale would not have been possible without all the technology that we have been mentioning so far.

Going forward, as hotels and chains are having to operate with leaner teams, we expect the best revenue managers to utilize even more of these intelligent solutions to build commercial strategies that align their plans and KPIs with those of the distribution, sales and marketing teams, hence generating demand and maximizing revenue opportunities during the market recovery. In uncertain times and with the whole industry in the midst of its worst crisis in its history, data-driven and tech-enabled revenue management can provide a strategic competitive advantage to hotels. By the time COVIOD-19 is a distant memory, revenue managers will be assuming greater importance within the organization and those who successfully navigated the crisis, e.g. by increasing revenue per guest and performing better than their comp set, will end up being considered indispensable by any owner/operator.

Action list:

(for Revenue Managers wishing to transform into revenue strategists):

  • Leverage modern technology to optimize rates and stay one step ahead of the competition (e.g. by using next generation rate shopper, such as FornovaCI)
  • Use dynamic pricing instead of setting static rates
  • Use distribution data & pick up to inform digital marketing
  • Segment guests and offer them customization options, but make sure those promotions run on the right channels
  • Help the marketing team personalise retargeting
  • Identify new feeder markets
  • Help the distribution team preserve rate integrity
  • Practice total revenue management and increase ancillary revenue (e.g. food & beverage, spa)
  • target non-guest segments (e.g. restaurant delivery, use rooms as office space)
  • Advocate/push your hotel or chain to move to from CPC advertising to commission-based Pay Per Stay model (e.g. Google PPS), and be the decision maker on commissions by calculating cashflow benefit, estimating and quantifying risk of cancelations, etc.

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