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Pricing at hotels has changed dramatically over the last decade. First, the advent of the OTAs created an environment of price transparency, where, for the first time, consumers can easily access and compare hotel prices in a market. Consumers also have easy access to detailed opinions from their peers (i.e., reviews and ratings) at the point of purchase, through review sites, OTAs and even hotel websites, ushering in a new era of value transparency. In order to continue to price effectively, revenue managers need to understand how consumers are using this user-generated content (UGC) with price, to make a hotel purchase decision. 
To answer this, two empirical studies were conducted. 

Study 1: The Interplay Between Price, Consumer Reviews and Consumer Ratings
The first study examined the interplay between price, consumer reviews and aggregate consumer ratings to influence consumers’ quality and value perceptions. Participants were presented with one of eight scenarios based on a typical online purchase of a hotel room for leisure, in which the price (low and high relative to an established reference price), the aggregate rating (low or high out of five) and the review sentiment (mostly positive or mostly negative) varied. Participants were asked to evaluate the quality and value of the hotel in the scenario with which they were presented1.  
    In the two figures below, the red bars represent the low-priced scenarios (L), and the blue bars represent the high-priced scenarios (H). Notice that in the perceived quality chart (Figure 1), the red and blue bars are effectively the same at each level of ratings (H/L) and reviews (P/N). This means that price does not impact quality. You will also notice that the positive review scenarios (P) are the four highest average perceived quality. In the perceived value chart (Figure 2), lower price is perceived as more valuable (red bars), but there are still scenarios with low price that are perceived as less valuable than higher prices. This indicates that consumers are using the reviews and ratings in their value perceptions.

Study 2: The Power of the Negative Review
In the second study we wanted to explore how consumers make tradeoffs when forced to choose among alternative hotel properties. A choice modeling experiment was designed where consumers were asked to select the hotel they would buy from a choice of three, with varying levels of key attributes1. Table 1 shows the attributes and levels that were tested. 

    Figure 3 shows the results of the choice modeling experiment. In this type of analysis, the output is the value, or utility, that is placed on an attribute relative to the other options in the study. It gives a sense of how likely a consumer would be to choose a hotel with that attribute. In this case, the absolute value of the numbers is less important than their magnitude and direction relative to the other attributes. Attributes with an asterisk were significant predictors of choice. Red represents a negative impact. Here, we see that the negative impact of a negative review is greater than going from low to mid, or mid to high, price. The figure also shows that the positive impact of high versus mid ratings would not overcome the negative impact of raising price or of negative reviews. Note also that the ratings and TripAdvisor ranking are only significant for consumers when the move is from mid to high. They do not value improvements from a low to a midrating.      

    Choice modeling also allows comparison of the overall value of hotels with various sets of attributes, and evaluation of how guests would trade-off among options. In the study, the most valuable choice was:

Positive Review + Low Price + High TripAdvisor Rank + High Rating + Known Brand = 1.95

When you hold everything else constant and only evaluate the highest price, note the change in value.  

Positive Review + High Price + High TripAdvisor Rank + High Rating + Known Brand = 0.46

The value drops significantly with the higher price, indicating that consumers do prefer a lower price. Now notice what happens when you hold everything constant and change from positive to negative reviews.

Negative Review + Low Price + High TripAdvisor Rank + High Rating + Known Brand = 0.01

The value to the consumer drops to practically nothing. This is the power of negative reviews. (See the online blog post: http://blogs.sas.com/content/hospitality/2013/01/22/social-media-and-lodging-performance/.)
While the research supports a relationship between positive user-generated content and pricing power, revenue managers should be cautioned to pause before rushing to raise prices. Instead, revenue managers should consider their market position and their long-term business strategy and goals. Are you at the same reputation position as your competitors? Are there loyalty implications to a price change? How does the price change impact the brand strategy? Does the hotel have a market share strategy it is trying to execute? How would price increases impact plans for qualified business?

    A key takeaway from this study is that revenue managers need to have a sound understanding of their own price, demand, reputation and value proposition, and also that of the competition. Some of this information is not traditionally kept within the revenue management domain. As pricing strategy becomes more complex, revenue managers must begin to collaborate with counterparts in other departments like marketing and operations to continue to build profitable pricing strategies.  

    Driving revenue and share in the hospitality industry is no longer just about competing on price. User-generated content, particularly reviews, are being used by savvy consumers to inform their purchasing decisions. Hoteliers must keep an eye on how they are priced relative to the market, and monitor social reputation.   

Kelly McGuire leads the hospitality and travel global practice for SAS. She can be reached at Kelly.McGuire@sas.com. Breffni Noone is Associate Professor of Hospitality Management at The Pennsylvania State University. She can be reached at bmn2@psu.edu.