Price, reviews and ratings: How consumers evaluate a hotel room purchase in a social world

NB: This is a viewpoint from Kelly McGuire, PhD, Executive Director of the Hospitality and Travel Global Practice for SAS, and Breffni Noone, PhD, Assistant Professor at the Pennsylvania State University School of Hospitality Management.

Most industry insiders agree that social media impacts consumer buying behavior, particularly reviews (text descriptions of a hotel experience) and ratings (aggregated score based on individual consumers’ scores).

However, exactly which form of user generated content (UGC) influences consumer buying behavior, the degree to which it influences the decision making process, and how it interacts with the price of the hotel room has been the subject of much debate.

We set out to answer these questions in a recent research collaboration between SAS and The Pennsylvania State University. Our goal was to help hotel managers cut through the information clutter, be able to take action to improve their competitive positioning and positively influence consumer buying behavior.

The research design

Academic research tells us that perceptions of quality and value are the primary drivers of likelihood to purchase. So, understanding how UGC, and price act together on these drivers, means we can understand their ultimate influence on purchase behavior.

We designed the research context based on an online purchase of a hotel room for a weekend leisure trip to a US city center. We told our participants the average price of a four star hotel in their preferred location was $235. We then showed them a description of a hotel, and asked them to evaluate it.

Within the description, we varied the price either low or high relative to the established reference price ($175/$295), varied the aggregate user rating low or high (2.8/4.8 out of 5), and showed a set of ten reviews which were either mostly positive or mostly negative. Everything else was held constant.  This gave us eight different scenarios (Figure 1).  Each participant evaluated only one scenario.

We deployed this online survey to a representative, random sample of the US population. Our demographic results indicated a good spread of ages, incomes, gender and education.

The majority of participants indicated that they use the internet to book hotel rooms the majority of the time, and that they read, and are influenced by, UGC.

The results of the research

Perceived Quality:  We asked consumers to evaluate their perceptions of the quality of the hotel they were shown.

Figure 2 shows the average quality perceptions by scenario (Scale of 1-7 on Figure 2), sorted highest to lowest.

Note that the blue bars represent the high price scenarios and the red bars represent the low price scenarios (see Figure 1 for scenario key). There are two observations to make from this chart:

1. The four scenarios with the positive reviews have the highest quality ratings (indicated by the P). Statistical testing showed that reviews were the most significant driver of consumer quality perceptions. Ratings did have a statistically significant relationship with quality perceptions, but it was not as strong as reviews.  This means that consumers are relying primarily on the reviews as an indication of the quality of the hotel.

2. The average quality scores are very similar between the high and low price scenario for each same rating and review level (i.e. LHP and HHP). Statistical testing indicated no significant difference in quality between the low and 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.

Perceived Value:  Value is defined as the tradeoff between what you give (price) for what you get (hotel stay experience), so we would expect price to be on the consumers’ minds as they evaluate value.

Figure 3 shows the average value perceptions by scenario (Scale of 1-7).  As in the previous section, red is the low price and blue the high price.

Interestingly, while we might have expected that the lower price would always represent higher value for consumers (i.e. all four red bars would be lined up first), some high-priced scenarios have a higher perceived value than some low-priced scenarios.

This means that reviews and ratings did influence value perceptions in some way.

Statistical analysis, not surprisingly, showed a significant negative relationship between price and value (as the price increased, value perceptions decreased). However, there was also a significant interaction between price, reviews and ratings on consumer value perceptions, meaning that the UGC altered the magnitude of the negative relationship in some way.

In order to investigate this effect more closely, we split the low and high price scenarios.

The chart at the top of Figure 4 is the high-priced scenarios and the chart at the bottom is the low-priced scenarios. Statistical analysis provided three observations:

1. In the high price scenarios, consumers looked only to the reviews to determine the value of their purchase – ratings did not change any relationships.

2. In the low price scenarios, ratings mattered, but only when reviews were positive. Positive reviews/high ratings drove higher value perceptions than positive reviews/low ratings, suggesting that the high rating simply acted as a confirmatory signal for consumers that they were getting a really “good deal”.

3. Looking at the “worst case scenario” for each price level, when the reviews were negative and the ratings were low, there is no statistical or practical difference in value perceptions between low and high price (the bars on the far right of each chart).  This suggests that lowering the price of a poorly-rated property will not create any additional value in the minds of the consumers.

Our findings suggest the following takeaways:

1. Reviews are the most powerful quality and value indicator for consumers: Our research overwhelmingly indicated that consumers look to the reviews over aggregate ratings to form quality and value perceptions.

   This runs counter to some theoretical arguments that suggest that consumers are “information misers”, preferring a metric that’s easier to consume (like an aggregate rating), as opposed to the information-rich review.

   We hypothesize that the uncertainty associated with the hotel experience leads consumers to want to gather as much information as they can to mitigate this uncertainty.  Hotel managers must not only understand their review sentiment, but also that of their direct competition, in order to successfully position themselves in a highly competitive market.

2. Competing on price alone is not a winning strategy. While consumers prefer to pay the lowest price, they will look closely at your UGC, and that of the competitors, when making a purchase decision. This means hotels can’t undercut (or raise) price simply based on the price movements of the competitors. Managers must also understand how their UGC compares, evaluating consumers’ total value perception of their hotel versus the competition.

3. In the presence of reviews (and ratings), consumers do not use price as an indication of quality. This is good news for revenue managers, because it means that they can play around with price (within reasonable bounds) to generate short term demand, without impacting consumers long term quality perceptions.

4. It’s hard to overcome “bad” UGC: Our results indicated that lowering the price of a badly rated, and negatively reviewed, property drives no additional value in the minds of the consumer. If a hotel happen to be in that unfortunate position, they should keep the price up, and take what they can get – which according to our results won’t be much. Our recommendation for these properties is to focus on fixing the problems with the property instead of worrying about how it is priced!!

The results of our study confirm the hypothesis that consumers purchase behavior is heavily influenced by user generated content. This study also confirms that it is the reviews, as opposed to the aggregate ratings, that are the strongest influencer of quality, value and ultimately purchase behavior.

While this unstructured text data is more difficult to access and analyze, it is essential in understanding consumer buying behavior, and will ultimately be key in pricing and positioning strategies. Many hotel companies are making such investments, so these results should provide further proof of the importance of such investments.

There is more to learn about how consumers make tradeoffs between price, quality and value perceptions (and our research continues). What is clear is that the presence of UGC has moved us from an environment of price transparency to value transparency – and so to remain competitive, hoteliers must incorporate this content into their strategic and tactical decision making.

NB: This is a viewpoint from Kelly McGuire, PhD, Executive Director of the Hospitality and Travel Global Practice for SAS, and Breffni Noone, PhD, Assistant Professor at the Pennsylvania State University School of Hospitality Management.

NB2: Review image courtesy of Shutterstock.