As hotel demand becomes increasingly dynamic, technology is helping revenue teams move beyond seasonal pricing and historical data to make faster, more informed decisions on rates, inventory and profitability
Hotel room pricing in India is changing. The traditional practice of setting rates around peak, shoulder and off peak seasons is increasingly giving way to a more dynamic approach, as domestic travel becomes more spontaneous, booking windows become shorter and demand can shift quickly around long weekends, events and holidays. For hotels, the challenge is no longer simply to decide what rate to sell a room at, but to understand how demand is building and respond before the opportunity is lost.
Vijeta Soni, Co Founder and CEO, Sciative Solutions, believes this change is already well underway. “The Indian hospitality sector is undergoing a massive shift as domestic travel becomes mobile first and last minute. Rigid seasonal bands are completely obsolete,” she says. According to her, one of the biggest shortcomings of traditional revenue management is the speed at which decisions are made. “Human revenue managers updating rates once or twice a day simply cannot react to sudden demand surges. By the time a surge reflects in standard PMS pickup reports, inventory has already sold out at low, sub optimal rates.”
The problem is also linked to the way hotels have traditionally used historical data. Revenue teams have long relied on previous year performance and booking curves to understand how a particular period may behave. While that data continues to have value, Soni believes it cannot be the only basis for pricing decisions in a market that is changing rapidly. “Legacy tools rely on historical year over year pickup curves. In today’s market, shaped by shifting corporate travel, long weekends and event shifts, looking backward guarantees missed revenue,” she says.
This is where the growing use of AI and real time data is beginning to change the revenue management process. Instead of waiting for bookings to accumulate before identifying a demand spike, technology can bring together a wider set of signals that indicate where demand may be heading. Soni describes this as moving from reactive forecasting towards what she calls real time “nowcasting”.
“Predicting demand isn’t about guessing; it’s about listening to live market intent before reservations ever reach a hotel’s Property Management System,” she says. Sciative’s ZettaRMS, according to Soni, looks at several forward looking indicators, including flight and railway search activity, booking pace, local events, holidays, competitor pricing and guest sentiment.
Travel intent can offer an early indication of where demand is likely to emerge. “We track spikes in regional flight and train searches because these signals can emerge before the actual hotel reservation,” says Soni. Once bookings begin to come in, their pace becomes another important indicator. “ZettaRMS tracks how fast reservations are coming in across OTAs and direct channels and automatically suggests or adjusts prices when booking momentum speeds up.”
Events are another major factor, particularly in cities where hotel demand can change sharply over a few days. Concerts, sporting events, festivals, holidays and weddings can create a sudden compression in demand, making historical patterns less useful. The ability to identify such events in advance can give hotels more room to manage their inventory and rates rather than responding after most of the available rooms have already been sold.
Interestingly, Soni also believes a hotel’s reputation can influence its pricing power. “Higher guest review scores increase a hotel’s pricing power. ZettaRMS factors in review ratings and guest sentiment so you can confidently charge more when your brand reputation is strong,” she says.
The larger shift, however, is perhaps in the way hotels look at occupancy. For years, occupancy has remained one of the most closely watched performance indicators, but a full hotel does not necessarily mean a more profitable hotel. Selling the last rooms at heavily discounted rates may push occupancy higher while leaving the property with less room revenue than it could have generated.
“High occupancy is often a vanity metric. Running at 95% occupancy at discounted rates increases operational wear and tear, laundry and staffing costs, often leading to lower GOPPAR than an 80% occupied property with a premium ADR strategy,” Soni says.
For revenue teams, this means the focus is gradually moving from filling every room to improving the quality of revenue generated from each available room. During periods of strong demand, for example, a hotel can increase its rate as inventory reduces instead of continuing to sell rooms at the same price. It can also use minimum length of stay restrictions to protect inventory for higher value bookings.
“ZettaRMS identifies high intent booking segments and automatically elevates ADR on remaining inventory to maximise pure margin,” says Soni. She adds that the system also considers distribution costs when making pricing recommendations. “ZettaRMS factors channel distribution costs into its pricing recommendations, helping hotels drive bottom line margin rather than just surface level top line numbers.”
The opportunity is particularly relevant during periods when demand accelerates quickly. Soni cites Hotel Tech Report benchmarks which indicate that hotels adopting automated revenue management software achieve an average RevPAR increase of 10% to 15%. While technology alone cannot guarantee such an outcome for every hotel, the broader point is that revenue management is increasingly being measured by the quality of the revenue generated rather than occupancy in isolation.
Competitor pricing is another area where technology is changing the daily work of revenue teams. Hotels have traditionally monitored competitor rates manually or through periodic rate shopping reports. But when prices are changing throughout the day, a report that is several hours old may already be outdated. At the same time, responding to every competitor price movement can create another problem.
“Speed matters, but blindly reacting to every competitor price drop leads to a self destructive race to the bottom,” Soni says. The challenge, therefore, is not simply to know what competitors are charging, but to understand whether a particular movement represents a genuine change in market demand or is simply a temporary pricing decision.
According to Soni, ZettaRMS continuously monitors competitor pricing across OTAs and direct channels. However, she says the system is designed to work within a hotel’s own commercial strategy rather than simply undercutting competitors. “Rather than automatically undercutting a competitor who panic drops rates for a few rooms, ZettaRMS evaluates the price change against your property’s pre set strategy rules and rate parity boundaries,” she says.
The growing use of dynamic pricing also brings the question of guest trust into the conversation. Hotel rates can change quickly, but excessive or unexplained movements can affect how guests perceive value. Soni believes the answer is not to move away from dynamic pricing but to ensure that technology operates within clear boundaries.
“Guest trust is damaged by price gouging and erratic rate spikes, not by fair dynamic pricing,” she says. At Sciative, she says the approach is based on a Human in the Loop model. “The technology serves as an intelligent co pilot. The AI executes micro adjustments 24/7, but the revenue strategist remains in total command.”
Hotels can establish price floors, ceilings and limits on how sharply rates can move. “Hotel leaders set strict price floors, ceilings and maximum allowable rate jumps. ZettaRMS will never execute an unapproved or extreme price jump outside these human defined rules,” Soni says. During periods of exceptional demand, hotels can also look at value added packages instead of relying entirely on higher room rates. “Instead of pushing room rates to reputation damaging highs, ZettaRMS helps hotels yield value add packages, bundling F&B credits or spa access, to preserve guest perception.”
For revenue managers themselves, the growing use of AI is likely to change the nature of the job. Rather than replacing revenue professionals, automation can take over some of the repetitive work that consumes their time and allow them to focus on wider commercial decisions.
“AI is not replacing revenue managers. ZettaRMS transforms the role of a traditional Revenue Manager into a strategic Profit Manager,” says Soni. She cites HSMAI research indicating that unassisted revenue managers spend 50% to 60% of their weekly bandwidth on manual administrative work. According to her, automating continuous rate updates and rate shopping can eliminate up to 15 hours of repetitive work every week.
That time can then be redirected towards total revenue management, including F&B, MICE, spa and other ancillary revenue streams, as well as direct booking strategies and broader commercial planning. “This shift elevates the revenue manager into a true Profit Manager who can focus on Total Revenue Optimisation, expanding yield strategies across F&B, MICE, spa and ancillary services,” she says.
The bigger opportunity lies beyond the large hotel chains. India’s independent and regional hotel market has a substantial number of properties that may not have dedicated revenue management teams or the budgets for complex technology platforms. Soni believes the barrier is not necessarily a lack of interest in technology but the difficulty of adopting it.
“Market reports show that over 80% of India’s hotel supply consists of unorganised, independent or regional properties. The biggest bottleneck in this segment isn’t a lack of ambition, it’s technology friction and tech adoption anxiety,” she says.
For these hotels, she believes revenue technology needs to be simpler, more accessible and easier to test. “For AI to become truly accessible across India, the industry needs zero friction, risk free entry points,” she says, pointing to Sciative’s ZettaRMS Freemium offering for independent, boutique and regional hotels.
But cost should not be the only consideration for hotel owners evaluating an RMS. “Look for platforms that let you test automated dynamic pricing on your property first without locking you into expensive upfront contracts. The software must work alongside your existing setup without requiring a full IT revamp or months of staff retraining,” Soni says.
As hotel demand becomes more fluid, the future of revenue management may ultimately be less about following a fixed pricing calendar and more about continuously reading the market. The question for hotels is increasingly not simply how many rooms they can sell, but when to sell them, at what rate, through which channel and with what impact on the bottom line.
For Soni, that is the larger change AI is bringing to hotel revenue management. The technology is not simply automating rate changes; it is giving revenue teams the ability to spend less time reacting to yesterday’s numbers and more time understanding where tomorrow’s demand is coming from.
