NB: This is a guest article by Kelly A McGuire, PhD, SAS Executive Director of Hospitality and Travel Global Practice, and Breffni M. Noone, PhD.
The advent of social media, and the popularity of consumer review sites, has changed the way that consumers buy hotel rooms.
The industry has moved from price transparency – when the OTAs made it easy to compare hotel room prices, to value transparency – where price and user generated content (UGC) is freely available at the point of purchase.
In a highly competitive market, this has put a great deal of pressure on hotels to understand how all of the price and non-price information provided at the point of purchase is being utilized in consumer decision making. Knowing the most influential information will help hotels better position themselves against their competition to drive revenue and share.
In order to help hoteliers understand how consumers weigh different attributes of the hotel room purchase we designed a research project utilizing a technique called discrete choice analysis (DCA).
[i]
In DCA, consumers are asked to pick the product or service they would buy from a set of similar products or services where certain key attributes are varied. By following the participants’ choice patterns, the value they place on each attribute, and each level of the attribute, can be statistically derived, and the probability that they would pick a hotel with a specific combination of attributes can be identified.
The study design
This was a scenario-based study, and participants were recruited online from a representative population of the US.
The participants were told they were purchasing a four star hotel in a city-center for a weekend leisure trip with friends. They were asked to pick the hotel they would stay at from among three choices with various combinations of attribute levels, and they did this three times (ie. they saw three sets of three hotels). We then asked them to tell us what they were thinking as they made their choices.
Table 1 shows the attributes and the level of the attributes that we tested.
Our
prior research clearly demonstrated the power of reviews in consumers’ assessments of the quality and value of a hotel purchase. We wanted to learn more about how consumers react to reviews, so we also tested whether what reviewers talked about (content) and how they talked about it (language) had an influence on their choice behavior.
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Table 1: Study Attributes and Levels
Attribute | Level 1 | Level 2 | Level 3 |
| Hotel Name | Known Brand | Unknown Brand | |
| Price | $195 | $235 | $295 |
| Aggregate Rating | 2.8 | 3.8 | 4.8 |
| TripAdvisor Rank (out of 217 hotels) | Low | Mid | High |
| Review Valence | Negative | Positive | |
| Review content | Physical Property | Service Level | |
| Review Language | Descriptive (e.g., the bed was comfortable) | Emotional (e.g., I loved the bed) | |
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Results showed that review valence (positive or negative) had the most influence on choice, followed by price, then aggregate rating, then TripAdvisor rank. Brand was marginally significant. Interestingly, content and language of the reviews were not significant.
The hypotheses
We hypothesized two reasons for this.
First, the overwhelming power of the review valence may have overshadowed any effect of content or language. Once consumers noted that the review was negative, they moved on, not caring what it actually said.
The other possible reason (which was backed up by the open ended responses) is that consumers care about both service and physical property equally, so they do not distinguish between the two when assessing the value of the hotel.
Table 2 shows the utility value of each attribute. The numbers themselves are not really as meaningful as the direction of the impact and their values relative to each other.
The red bars represent the negative impact of negative reviews, and the negative impact of increasing price from low to mid and from mid to high. The blue bars represent the positive impact of increasing ratings and TA rank, and the positive impact of a known brand versus and unknown brand. The significant attributes are starred.
Table 2: Utility by Attribute Level
There are a couple of things to notice on this chart:
The power of the negative reviews
Take a look at the equations that follow this paragraph, (where the utility values of each attribute are summed to form a total utility for that combination of attributes).
Not surprisingly, the best combination of attributes (with the highest total utility of 1.95) is positive reviews, low price, high rank, high rating and known brand. Changing one attribute level at a time will show the impact on overall utility of that attribute.
Notice the impact of changing the price from lowest to highest, versus changing the ratings from high to low, versus changing the review valence from positive to negative. Negative reviews clearly remove the hotel from the choice set – even lowering price cannot overcome the negative impact of negative reviews.
Positive + $195 + High Rank + 4.8 + Known Brand = 1.95
Positive +
$295 + High Rank + 4.8 + Known Brand =
0.46
Positive + $195 + High Rank +
2.8 + Known Brand =
1.45Negative + $195 + High Rank + 4.8 + Known Brand =
0.01Low-to-mid versus mid-to-high ratings and rankings
Notice also from Table 2 that for aggregate ratings and TripAdvisor ranking, even though these attributes were significant overall, only the movement from mid-to-high had a significantly positive impact on consumer utility.
Consumers did not value a movement from a low-to-mid-range score. This result provides a nuance to recent research that describes a positive performance impact from improving your ratings scores
[ii].
That performance impact will only be felt if you are already at a mid-range score and are able to move to a high score. The same is true for TripAdvisor rank. Positive impact will only be felt as the hotel moves from a mid-range ranking to a high rank.
In their own words
We also asked consumers to describe what they were thinking as they made their choices.
Their comments back to us further reinforced the study results, and gave us insight into how consumers make value judgments using price and non-price information. The majority of participants mentioned the reviews, reinforcing the importance of that attribute in decision making. Price was mentioned second most frequently followed by aggregate ratings.
A small percentage of participants mentioned the hotel location or amenities, TripAdvisor rank and brand as influencing their choice (Table 3).
Table 3: Attribute mentions
Digging a bit deeper into the data, we saw that for some participants, only one information source was foremost in their thoughts as they made their choices, while for others, a combination of information sources dominated - 37.4 percent solely mentioned reviews (Table 4). For example, one respondent said “Customer reviews are paramount in making my decision to stay at a hotel”. Another commented “I chose the rooms that had the best reviews, which is what I always do”.
Reviews were also mentioned in combination with other non-price information sources by 8.4 percent of the respondents, with aggregate ratings and reviews mentioned by 3.4 percent (Table 4).
Typically respondents were describing tradeoffs they made between information sources: “Customer feedback played more of a role than consumer ratings provided since the ratings only tell half the story and are not as detailed as feedback.”, and “Recent negatives for me will outweigh a high customer rating, since that tells where the hotel currently ‘sits’”.
While about 23 percent of respondents focused solely on price (“Price came first” and “I still focused on price"), price was primarily mentioned in combination with other attributes (35 percent of respondents). 19.3 percent mentioned price in combination with reviews, frequently speaking about the tradeoff they made between these attributes (Table 4).
One respondent wrote “The price was taken into consideration, but if a lower price room is in a hotel with bad service and other negatives, I would always go with the higher price. If the rooms at the other two places were clean, good service, and other positives, the less expensive of the remaining two would be chosen”.
Table 4: Attribute mention breakdown
Key Takeaways
The purpose of this study was to determine how consumers used price and non-price information to make hotel purchase decisions when they were asked to make a choice among alternatives.
Quantitative and qualitative results clearly supported the following takeaways for hoteliers:
- 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, reviews contributed the most to consumer choice behavior followed by price.
- Power of the negative review: Negative reviews removed the hotel from the choice set in the minds of the consumer. Low price or high ratings and ranking will not overcome the impact of negative reviews. Consumers focused in on this information source as an indication of the current performance of the hotel, and indicated that they would tradeoff a lower price for a hotel with more positive reviews.
- Consumers prefer to pay a low price: While consumers will go for a higher-priced hotel when the lower-priced hotel has negative UGC, they still prefer to pay the lowest price possible. All things being equally positive, they will look for the lowest price. Hotels need to pay attention to how their reviews compare to the competitive set when setting price.
- Consumers only notice high ratings and rankings: When consumers make purchase decisions, ratings and rakings will only make a difference if they are high as compared to other choices in the set. 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 hotel industry is no longer just about competing on price. Consumers are clearly turning to user generated content to inform their hotel purchase decisions.
This means that in order to compete effectively, hoteliers must understand how their online reputation compares to the competitive set, and specifically, how they are positioned relative to the competition in the sentiment of their reviews. We are operating in an era of value transparency, making it even more crucial for hotels to understand their value proposition, and firmly establish that in the minds of the consumers.
[i] The study design and research results are taken from Noone, B and McGuire, K (forthcoming) “Pricing in a social world: the influence of non-price information on hotel choice”
Journal of Revenue and Pricing Management, ( http://www.palgrave-journals.com/rpm/journal/vaop/ncurrent/full/rpm201313a.html)
[ii] Anderson, C. (2012) “The Impact of Social Media on Lodging Performance” Cornell Center for Hospitality Research Reports, Vol. 12, No. 15.
NB: This is a guest article by Kelly A McGuire, PhD, SAS Executive Director of Hospitality and Travel Global Practice, and Breffni M. Noone, PhD.
NB2: Thumbs images courtesy
Shutterstock.