OperationsMarketingPricing in a Social World

Pricing in a Social World

The advent of online travel agencies (OTAs) ushered in an era of price transparency on a broad scale. Revenue managers suddenly had to pay close attention to their price position relative to the competitive set, adding another variable to complex pricing decisions.

Enter social media. Now that reviews (unstructured text) and ratings (aggregate scores, usually 1 to 5) are available at the point of purchase, there is another element that could potentially interact with price and influence consumers’ purchase behavior. Revenue managers need to know how they should account for user-generated content in their pricing and positioning decisions.

We set out to understand just how complex these changing market conditions and technologies have made revenue managers’ jobs in a recent research collaboration between software solution and services provider SAS and Pennsylvania State University.

Academic research tells us that perceptions of quality and value are the primary drivers of likelihood to purchase. If we could understand how user-generated content and price act together on these drivers, we would understand their impact on consumer purchase behavior. To test this, we built a research scenario based on an online purchase of a hotel for a weekend leisure trip to a U.S. city center. We told our participants that four-star hotels in their preferred location were priced at an average of $235 per room. We then showed them a description of a hotel and asked them to evaluate it. We varied the price low ($175) or high ($295) relative to the established reference price, varied the aggregate user rating low or high (2.8 to 4.8 out of 5 respectively), and showed a set of 10 reviews that were either mostly positive or mostly negative. This gave us eight different variations of our scenario.

We deployed this online survey to a representative sample of the U.S. population. Our demographic results indicated a good spread of ages, incomes, gender, and education. The majority of participants indicated that they often use the Internet to book hotel rooms and that they are influenced by user-generated content.

Perceived Quality
Figure 2 shows the average quality perceptions by scenario, sorted highest to lowest. The average quality scores are very similar between the high and the low price scenarios for each same rating and review level (for instance, LHP and HHP). Statistical testing indicated no significant difference in quality between the low price and the high price scenarios at each same level of reviews and ratings. This means that in the minds of consumers, price has no impact on perceptions of quality. Consumers are looking to other cues to determine the quality of their purchase. This is great news for revenue managers, because it means that they can vary price to suit demand patterns (with a reasonable boundary), without damaging the consumers’ quality perceptions.

The four scenarios with the positive reviews have the highest quality ratings. Statistical testing indicated that, while aggregate ratings did influence quality perceptions somewhat, reviews had by far a stronger relationship with consumers’ perceptions of the quality of the hotel purchase.

Perceived Value
Value is defined as the trade-off between what you give (price) for what you get (purchase), so we would expect price to be on the consumers’ minds as they evaluate value. Figure 3 shows the average value perceptions by scenario. Interestingly, while we might have expected that the lower price would always represent higher value for consumers (in which case all four blue bars would be lined up first), some of the high price scenarios have a higher perceived value than some of the low price scenarios do.

In order to investigate this effect more closely, we split the low price and high price scenarios (see Figure 4). Statistical analysis indicated that for the high price scenarios, consumers looked to the reviews to determine the value of their purchase—ratings did not make any significant difference. For the low price scenarios, it was the ratings that made the difference, but only when the reviews were positive. Positive reviews and high ratings drove higher value perceptions than positive reviews and low ratings, suggesting that the high rating acted as a confirmatory signal for consumers that they were really getting a good deal on the hotel.

Looking at the worst-case scenario for each price level, when the reviews were negative and the ratings were low (the bars on the far right), there is no statistical or practical difference in value perceptions between low price and high price. This seems to indicate that lowering the price of a poorly rated property will not create any additional value in the minds of the consumers. Hotels would be better off leaving the higher price and just taking what they can get. Frankly, in this case, the hotel really should forget about playing around with price and instead figure out how to fix its problems and improve performance.

What Does it All Mean?
Consumers do not treat price as a quality indicator, so revenue managers can feel free to play around with price (within reason) and not worry about impact to quality perceptions. However, consumers do treat price as an economic sacrifice, and they will always prefer to pay a lower price—all things being equal.

With that said, competing on the basis of price alone is no longer a winning strategy for hotel properties. Consumers pay attention to user-generated content, and they will use it to evaluate the quality and value of their hotel purchase. Revenue managers must pay attention to not only their price position relative to that of the competitors but also their social position relative to that of the competitors.

The results of the study overwhelmingly indicated that consumers rely on reviews when evaluating a hotel purchase. Reviews were much more significantly related to quality and value perceptions than ratings, and when review sentiment conflicted with ratings (as in the LP and HN scenarios), consumers would rely on the sentiment of the review, ignoring the ratings. Quantitative ratings might be convenient to analyze, but they are not going to give you the full story.

There is much more to learn about how consumers make trade-offs between price, quality, and value perceptions. What is clear is that the presence of user-generated content has moved us from price transparency to value transparency. With reviews and ratings at the point of purchase, consumers have the opportunity to easily evaluate the value of their purchase, and they are definitely taking advantage of it.

Kelly A. McGuire is executive director of the Hospitality and Travel Global Practice for SAS and has a PhD in revenue management from the Cornell School of Hotel Administration. Breffni Noone is an assistant professor at the Pennsylvania State University School of Hospitality Management (hhdev.psu.edu/shm) and has a PhD from Cornell University. This article is based on Noone and McGuire’s “Effects of Price and User-Generated Content on Consumers’ Pre-purchase Evaluations of Variably Priced Services,” recently published in the Journal of Hospitality and Tourism Research.