Have you ever continued a promotion or pricing strategy just because it's always been done that way?

Status quo bias refers to our natural tendency to resist change and stick with what's familiar, even when better options are available. In the context of hotel revenue management, this bias manifests when hoteliers continue to rely on traditional pricing models and marketing strategies because "that's how it's always been done," despite shifts in market conditions or consumer behaviors that would justify a change. To combat this bias, hoteliers should regularly challenge their existing practices by reviewing their current strategies and actively seeking new data. Engaging with industry trends and adopting innovative technologies can help shift perspectives and encourage more dynamic approaches to pricing and policy-making.

Imagine the scenario where you become the revenue manager at a luxury property that’s never run discounting or promotions before.  During your onboarding, the GM tells you that they believe discounting will hurt the brand and therefore they’ve never run offers.  By sticking with what’s always been done at the property, this GM is forgoing a massive opportunity to bring guests in during need periods and drive targeted demand.

Have you ever based your pricing on a competitor's rate?

Anchoring bias occurs when the first piece of information we receive unduly influences our decisions moving forward. For hoteliers, this often means that initial pricing structures or the rates set when the hotel first opened continue to anchor subsequent pricing decisions, regardless of changes in the competitive landscape or market demand. To avoid the pitfalls of anchoring bias, hotel managers should regularly update their competitive analysis and market studies, ensuring that their pricing decisions are based on the most current and relevant data, not just historical figures.

Consider the scenario where your 100-key hotel undergoes a massive $5M rooms renovation.  You might be hesitant to raise prices if you were previously at parity with your compset for fear of a drop in occupancy.  After all, who would stay at your hotel for 30% more than a longstanding local competitor?  The reality is that by being anchored on your competitor’s rate strategy, you are holding back your property.  Many times a revenue manager might increase rates by 15% when in reality they could command a 30% premium leaving critical RevPAR and NOI on the table.

When was the last time you revised your demand forecast model?

Confirmation bias leads individuals to favor information that confirms their pre-existing beliefs, disregarding evidence that contradicts them. In hotel revenue management, this can result in sticking to a particular pricing strategy or marketing approach that the hotelier believes to be optimal, ignoring signs or data that suggest otherwise. To address this bias, hoteliers need to foster a culture of critical evaluation, actively seeking out and considering information that challenges their current beliefs. This might involve detailed analyses of customer feedback, occupancy rates, and revenue data to objectively assess the effectiveness of existing strategies.

Confirmation bias can trap hoteliers into favoring information that supports existing policies, such as sticking to a no-refund policy. Poor booking policies like no refunds might restrict occupancy rate unknowingly.  By challenging this bias and implementing a more flexible cancellation policy, your hotel could better meet customer needs, increasing occupancy and boosting revenue. Adapting to consumer preferences is key to attracting more guests and enhancing revenue.  Clearly, consumers want flexibility in our post-COVID world but confirmation bias might lead you to flinch when you hear the word “cancellation” based on what you were taught in hotel school 10-15 years ago.

Does your industry experience ever lead you to rely on intuition over new data or tools?

Overconfidence bias in hotel revenue management can lead to overly optimistic evaluations of demand forecasting, rate setting, and the effectiveness of marketing strategies, often resulting in inefficient resource use, missed revenue opportunities, and reduced competitiveness. To mitigate this bias, managers should adopt data-driven decision-making practices, seek external feedback, encourage continuous learning and adaptation, and foster a collaborative environment that welcomes team input. By grounding decisions in robust data and diverse perspectives, hotel revenue managers can better align their strategies with market realities and enhance overall financial performance.

Perhaps you used (and enjoyed) a revenue management system vendor at your previous employer that ran a portfolio of 10+ luxury properties  with 500+ rooms each. Since the vendor worked really hard, you decide to use them at your new company which is an upstart hostel brand with 2 30-room hostels that’s looking to scale to 100+ hostels within the next 5-years. You decide not to run a proper vendor selection process.  Overconfidence bias leads you to believe that this vendor would be highly effective at your new company when in reality that vendor may not be nearly as effective for small hostels as large luxury hotels.

Have you ever prioritized memorable customer interactions or reviews over long-term data when adjusting rates?

Availability bias affects decision-making by giving undue weight to recent or highly memorable events. For example, if a hotel recently received a few complaints about a rate increase, the manager might be hesitant to implement further necessary adjustments, even though the broader data supports such an increase. Hoteliers can mitigate this bias by ensuring that decisions are based on comprehensive, long-term data rather than reactive responses to isolated incidents. Regular review of extensive data sets and trend analyses can provide a more accurate picture of the hotel's performance and guide more informed pricing strategies.

Availability bias might lead a hotelier to avoid raising prices due to the impact of a handful of recent negative reviews. Imagine 5 consecutive bad reviews about your hotel being overpriced.  You might flinch at the idea of increasing prices; however, what the reviews may not show is that all of those 5 guests purchased a Groupon promotion and are not representative of your typical customer base so by not raising price, availability bias is negatively impacting revenue and profitability.

Have you delayed the adoption of new technology or services out of concern for their initial impact on your business?

Risk aversion is the inclination to avoid risks, even when there is a potential for significant reward. In hotel revenue management, this often translates into hesitation toward implementing new pricing strategies or marketing campaigns due to fear of negative outcomes. To overcome this bias, hoteliers should consider small-scale experiments to test the waters with new ideas, evaluating their effectiveness on a limited scale before a full rollout. This approach allows for careful assessment of potential risks and rewards, enabling more confident decision-making when considering larger strategic shifts.

Risk aversion can cause hoteliers to miss out on opportunities during market recoveries. A 100-key hotel keeping its rates at $100 due to fear of negative reactions might see a 75% occupancy, earning $225,000. But in a price inelastic market climate, adjusting rates to $120  might only result in a 3% drop in occupancy which means revenue would jump to $259,200 and profit to $34,200.  Let’s assume this hotel has $157,000 in costs.  In the first case,  NOI was $68,000 meaning that eliminating risk aversion would have grown NOI by 50%.  This scenario illustrates that taking calculated risks backed by data can significantly enhance a hotel’s revenue and profitability.

Data and Technology are the Keys to Revealing and Eliminating Bias

Cognitive biases originated as evolutionary mechanisms that allowed our ancestors to make quick, life-saving decisions with limited information. While these mental shortcuts were beneficial in prehistoric environments, they are often detrimental in modern, complex fields such as hotel revenue management.

Today, relying on these ingrained biases can lead to misjudgments and errors in a data-rich, fast-paced industry. Leveraging advanced tools like Smartpricing revenue management software (RMS) is essential in counteracting these biases. Revenue management software utilizes extensive data analysis to provide objective, consistent decision-making support, free from the emotional or subjective influences that can affect human judgment. By implementing an RMS, hoteliers can challenge their instincts with hard data, allowing for better-informed decisions that maximize revenue potential. By integrating technology that complements our human capabilities, hotel revenue managers can enhance their strategies and ensure their decisions are both profitable and data-driven, steering clear of the pitfalls presented by cognitive biases.

Revenue Management Software plays a crucial role in preventing hotel revenue managers from being overly influenced by initial pricing strategies or historical rates. By aggregating a diverse array of data sources, including competitor pricing, market demand, and economic conditions, RMS ensures that pricing decisions are based on the most current and relevant information. This continuous recalibration allows managers to respond effectively to real-time market conditions, liberating them from outdated benchmarks that might otherwise anchor their decision-making processes.

Another significant advantage of an RMS is its capability to conduct scenario analyses, which empower revenue managers to test various pricing strategies and see potential outcomes without actual risk. This feature is invaluable for reducing the natural risk aversion that can prevent managers from adopting innovative strategies due to fear of negative outcomes. By simulating different scenarios, an RMS provides a safe environment for experimentation, enhancing decision-making confidence with insights on the likely impacts of new approaches.

If you’d like to learn more about cognitive behavioral biases we highly recommend reading the work of the late Charlie Munger or Thinking Fast and Slow by Daniel Kahneman.

This article was created collaboratively by HotelTechReport and Smartpricing