As a follow-up to our first study, when we found a strong relationship between user-generated content, or ratings and reviews, and quality and value perceptions of hotel room purchases, Breffni Noone, associate professor at Pennsylvania State University, and I wanted to explore a bit further how consumers trade off these attributes with price. We designed a choice modeling experiment where we asked consumers to select the hotel they would buy from among a choice of three, with varying levels of attributes. By following the participants' choice patterns, the value they place on each attribute and each level of each attribute can be statistically derived. As well, the likelihood that they would pick a hotel with a specific combination of attributes can be identified.
The study design
This was a scenario-based, online study. We recruited a representative sample of the US population via an online survey recruitment company, ensuring that participants had traveled for leisure in the past, and that they had made the booking themselves, online.
We told our participants that they were taking a vacation with a friend, and were looking for a four-star hotel in a city center. We provided a selection of three hotels that met their quality and location criteria, and they were asked to indicate which they would buy. They repeated this exercise three times, and then we asked them to tell us what they were thinking about when they were making their choices.
We varied the price, the name of the hotel, the aggregate rating, the TripAdvisor rank, the sentiment of the review, the content of the review, and the language of the review for each hotel. Table 1 shows the attributes and levels that we tested.
Our first study demonstrated the power of the reviews in consumersí assessment of the quality and value of the hotel purchase, so we wanted to take the opportunity to learn more about how elements of the reviews influenced consumer decision making. In addition to the valence of the reviews (positive or negative), we tested whether what the reviewers talked about (content) and how they talked about it (language) had an influence on our participantsí choice behavior.
Results showed that the review valence (positive or negative) had the most significant impact on choice behavior, followed by price, then aggregate rating, then TripAdvisor rank. Known vs. unknown brand was marginally significant, with consumers showing a slight preference for the known brand. The content and language were not significant influencers of choice.
We think the reason review content and language were not significant is probably because consumers equally value both the service and physical property of the hotel (this was validated in the open-ended responses we collected). Further, whether the review was positive or negative appeared so important that it is likely that the impact of the language style was overshadowed.
Figure 1 below shows the utility value of each attribute level in the study. The utility is the relative value the consumers place on each change in level of the attribute. In this type of analysis, the value of the utilities themselves are less important than the direction of the impact and the magnitude relative to the other metrics.
The bars with an asterisk represent significant utilities. The red bars represent the negative impact of negative reviews and of raising the price from low to mid, and then from mid to high. The blue bars represent the positive impact on choice of raising ratings and TripAdvisor rank, as well as the positive impact of a known brand over an unknown brand.
There are two findings to note in particular on this chart. First, you can clearly see the strength of the impact of those negative reviews. It is the largest bar on the chart, even greater than raising price. Further, the relative positive impact of ratings, rank, and brand is small as compared to those negative reviews. Note that the TripAdvisor rankings have a smaller impact than the ratings.
Secondly, when you break out the individual impacts of the levels of ratings and rankings on choice, you will notice that consumers only notice a difference when comparing hotels with mid-range values to those with high-range values. They do not value a mid-range value as compared with a low-range value.
This finding adds a nuance to the recent study from the Cornell Center for Hospitality Research, which found an 11.2 percent increase in pricing power for each point increase in a ratings metric. Our study suggests that hotels will only see this benefit if they raise their ratings from a mid-level score to a high score. There will be no benefit from a lower score to mid-level score movement.
Impact of negative reviews
Choice modeling allows for a calculation of the overall value consumers place on a combination of attributes, which means we can evaluate the relative impacts of changing attribute levels on the whole picture of the consumersí likelihood to choose. Once again, the actual value of the number is less important than the values relative to each other.
Not surprisingly, the combination of attributes that maximize a consumerís likelihood to choose is positive reviews, low price, high TripAdvisor rank, high rating, and known brand. This results in a baseline overall utility of 1.95.
Notice the drop in overall utility when you change only the price to the highest price level.
Raising the price has a relatively large impact on overall utility, even when everything else is held equal. Clearly consumers prefer to pay the lowest price they can. Now, observe what happens when you hold all of the values equal, but change the reviews from positive to negative. The utility value drops to practically zero.
Even the positive impact of a lower price does not outweigh the negative impact of the negative reviews.
This study was designed to evaluate how consumers make tradeoffs between price and non-price attributes of a hotel when making a purchase decision. There are four major takeaways from this study for managers:
- Reviews and price are the most important influencers of choice. While consumers did pay attention to aggregate ratings, TripAdvisor rank and, to a lesser extent, brand, positive reviews contributed the most to consumer choice behavior followed by lower price.
- Negative reviews remove you from the choice set. Period. Lower price or higher ratings do not overcome the impact of negative reviews. Consumers simply will not choose a hotel with negative reviews. Hotels that are in this unfortunate situation should focus energies on improving their reputation.
- Consumers prefer to pay a lower price. While consumers would go for a higher-priced hotel when the reviews and ratings were better than the alternatives, all things being equal, they will look for the lowest price. Hotels need to understand their position relative to their competition both on reputation and on price in order to take advantage of any pricing power associated with positive user-generated content.
- Consumers only notice high ratings and rankings. Our results showed that consumers only notice ratings and rankings when they are high as compared to other choices. Consumers do not place any value on the comparison between low and mid-level ratings and rankings.
The bottom line is that driving revenue and share in the hospitality industry is no longer just about competing on price. Consumers are clearly turning to user-generated content to inform their purchase decisions, in particular, reviews. This means hoteliers must not only keep an eye on how they are priced relative to the market, but also on how they are positioned in terms of their reputation.
This post originally appeared in SAS's The Analytic Hospitality Executive blog.