How Business Travelers Buy: Hotel Pricing in a Social World

With the growing popularity and availability of online reviews and ratings, consumers have more information than ever before when purchasing a hotel stay.  In order to build effective pricing and positioning strategies, hotel managers need to understand how consumers are using all of this user generated content with price to make a purchase decision.  Dr. Breffni Noone, Associate Professor at Penn State, and I have done a series of studies to understand how consumers use all of this information to assess value, and ultimately, make a purchase decision.  Our latest research looked at unmanaged business travelers.

As in previous studies, we used a choice modeling experiment.  In this technique, researchers select a set of attributes of a product or service they wish to test, and subjects are presented with a set of options with varying combinations of levels of those attributes.  They are asked to select the option that is most attractive to them (the one they would buy).  As participants repeat this exercise over different sets of options, it is possible to statistically assess the importance of each attribute in decision making, and the value that they place on the attribute and its levels.

The study design

For this study, we told our business traveler participants that they were attending a meeting in a city center.  We told them we would show them a set of hotels that were “business-friendly” with equivalent class of service and amenities, all with locations equally convenient to the meeting.  We then showed them a set of three hotels in which the price (low, medium, high), review sentiment (positive, negative), review content (physical property, service) review language (emotional, descriptive), aggregate rating (low, medium, high), TripAdvisor Rank (low, mid-range, high) and brand (known, unknown, preferred) varied.  We asked them to select the hotel they would book from the set of three options, and they repeated that exercise three times.

The data was gathered via an online survey distributed to a representative sample of the US population.  We screened for participants who traveled on business at least six times per year, and were able to make the choice of where to stay themselves (i.e. not overly constrained by a corporate travel policy).  Since we knew that loyalty program affiliation could be influential in traveler decision making, we asked them to tell us what loyalty programs they belonged to, and to identify a preferred brand from within those loyalty programs.  We presented a list of brands within these loyalty programs that met the study criteria of “business-friendly” hotel, so for example, the Hilton Honors brands were Hilton, Embassy Suites and Doubletree.  Note that this was not a study about loyalty program membership, so we can’t really make inferences to the general population of business travelers, but it is interesting to see how these business travelers are affiliated with common loyalty programs.

Business traveler loyalty behavior and demographics

Figure 1 shows the distribution of membership and the distribution of preferred brands by loyalty program.  We also asked whether they belonged to a “non-brand” loyalty program (like hotels.com or Leading Hotels), and you can see that 45% of them were members of such programs.

Figure 1: Loyalty Program Membership of Sample

Figure 1: Loyalty Program Membership of Sample

 

Figure 2 shows the demographic composition of the business travelers in this study.  You can see that about half of them take 6-10 trips a year, and the vast majority stay two or more nights per business trip.  Interestingly, the vast majority of these business travelers do read reviews and say they are influenced by them.

Number or cards held, which programs

Figure 2: Business Traveler Study Demographics

Study Results

Overall Attribute Importance

The first output of a choice modeling study is the overall importance of each attribute in driving customer’s decision making.  The following list of attributes had a significant impact on value perceptions, and they are presented in order of importance to the business traveler:

  1. Review Sentiment (positive, negative)
  2. Brand
  3. Aggregate Ratings
  4. Price
  5. Review Language (descriptive, emotional)

Contrast this with the list for the leisure traveler:

  1. Review Sentiment (positive, negative)
  2. Price
  3. Aggregate ratings
  4. TripAdvisor Rank
  5. Brand

As you can see, there are already some interetsing differences in how these two segments assess value and make decisions, yet review sentiment is  most influential for both segments.

Influence of attribute levels on value

The next step in a choice modeling analysis is to understand how value assessments vary with the different levels of the attributes.  In other words, how do negative versus positive reviews impact value?

The following results were obtained from the analysis of value impact by attribute level:

  • When reviews were negative as opposed to positive, not surprisingly, there was a large negative impact on value perceptions
  • There was a small positive impact of the known brand over the unknown brand, but a large positive impact on value of the preferred brand over the known brand
  • While the value impact associated with both a mid-range aggregate rating over a low rating and a high rating over a mid-range aggregate were significant and positive, the impact of mid over low was actually greater than the impact of high over mid
  • There was a negative impact on value when the price was raised to the mid-level over the low price.  Business users did not notice the difference between the mid and high price
  • Finally, there was a slight positive impact on value of a review with descriptive language (“The bed was very comfortable”, “The room was cold”) over emotional language (“I LOVED the bed”, “The temperature in the room was annoying”)

Looking at the aggregate rating results suggest that it is more important to business travelers that the hotel is OK, than great.  They will assess what the experience will be like (by reading the reviews, especially descriptive ones), and as long as they feel it will be OK (and they can get points), they will book.  This doesn’t mean they don’t appreciate a great hotel, but in the balance between staying with their preferred brand that is just "OK", and a hotel with “great” reputation, they are likely to choose the preferred brand.  While business travelers are relatively price-insensitive, they do respond to a deal.  Hotels with an “unknown” brand that are in a better reputation position than the “preferred” hotels in their market (the ones with well-known loyalty programs), might be able to encourage business travelers to stay by offering a deal.  However, if the price isn't among the lowest prices in the competitive set, the business traveler is not likely to notice.

Assessing overall value

Choice modeling analysis also allows you to look at a combination of attribute levels and assess the overall value to a consumer of an option with that set of attribute levels.   We are going to present a set of equations below representing an hotel option from the study. The important thing to focus on is not the value of result of the equation, but how the number changes as we change attribute levels.

The below equation represents the most valuable option for the business travelers, in order of attribute importance.

Positive Reviews + Preferred Brand + High Rating + Low Price + Descriptive Reviews = 1.52

With this set of attribute levels as a baseline, we can manipulate the attribute levels and track their impact on overall value.  For example, holding everything else constant, the below equation represents overall value when the price is raised from lowest to highest.  You can see that the overall value is impacted slightly, but not by very much.  This is not surprising since the price was only the fourth most important attribute to business travelers, and it was only the low price that the business travelers valued.

Positive Reviews + Preferred Brand + High Rating + High Price + Descriptive Reviews = 1.25

Contrast this result with the leisure traveler study, where price was the second most important attribute.  The first equation is the most valuable option for the leisure traveler, and the second shows the impact of raising the price from low to high.  Leisure travelers are clearly highly price sensitive.  The overall value drops significantly when the price goes from low to high.

Positive Reviews + Low Price+ High Rating + High TARank+ Known Brand = 1.95

Positive Reviews + High Price+ High Rating + High TARank+ Known Brand = 0.46

Now look at what happens when the most important attribute for each traveler changes.  Holding everything constant from the baseline, the first equation below demonstrates the impact of negative reviews on overall value for business travelers, and the second for leisure travelers.  You can see here that the impact on value for business travelers over the baseline was quite significant, nearly half of the value is lost when the reviews are negative as opposed to positive.  However, for the leisure travelers, all of the value is lost when reviews are negative.  Business travelers clearly pay attention to reviews, but they are willing to balance that against other attributes like brand and rating.  Leisure travelers simply wont consider the hotel if the reviews are negative.

 Business: Negative Reviews + Preferred Brand + High Rating + Low Price + Descriptive Reviews = 0.69

Leisure: Negative Reviews + Low Price+ High Rating + High TARank+ Known Brand = 0.01

 

Summing it all up

So, what does all this mean?

There are a couple of key takeaways from this study:

  • Reviews matter – business travelers look to the reviews to assess what their experience will be like.  If the review is positive or negative they want to know why.
  •  Loyalty matters – Business travelers will put up with “good enough” or “OK” if they can get their points
  • Price matters – Business travelers still recognize a deal, but it’s only the lowest price that entices them.  They are relatively insensitive beyond that.

Figure 3 summarizes the key takeaways from this study as compared to the leisure study.  These takeaways present several opportunities for hoteliers.  For example, a hotel that has a heavy mix of business travelers who are members of their loyalty program might be able to put off renovations for a while (assuming the declining quality of the product is reflected in declining reviews and ratings), but a leisure property would not.  A brand that is relatively unknown in the market, could attract business travelers to forgo their preferred brand if their reputation was better, by offering a “deal”.

The bottom line is that pricing in today’s social world is not getting any easier.  Not only do you have to understand your price relative to the market, and your reputation relative to the market, but you also need to understand your business mix.   All of these decisions require good knowledge of the market backed by solid revenue and reputation analytics.

Figure 5: Key Study Takeaways

Figure 3: Key Study Takeaways

 

 

 

 

tags: Customer Intelligence, Hospitality Analytics, Revenue Management and Price Optimization

6 Comments

  1. Posted September 10, 2014 at 1:13 am | Permalink

    No real surprise when it comes to the outcome of this study. The main question is of course (as reviews and sentiment change and can be influenced); Do you adjust your pricing or do you invest in your guest experience or do you do both? In addition, what happens if your competitors increase their ratings and improve their sentiments, do you drop your rates? This is a topic where it can be easy to jump to conclusions, but it is important not to. Unfortunately this study does not take into consideration the main complexity of the actual market; The dynamics if the constant changes to price, review sentiment, ratings etc. in addition it fails to take into recognise the correlation between price and rating/review sentiment. But this just confirms the complexity of the matter.

    • Kelly McGuire Kelly McGuire
      Posted September 16, 2014 at 4:19 pm | Permalink

      Niels, Thanks for the comment. This study demonstrates that you have to manage reputation as carefully as you manage price (as you indicate, in as much as you are able to manage reputation). The study also indicates that all things being equal consumers prefer to pay a lower price, but negative reviews are difficult, if not impossible in the case of leisure travlers, to overcome by simply lowering price. I think the results of our study explain some of the effects that a revenue manager would see in the dynamic marketplace, and they have value when determining a price strategy. You are right that for tactical day-to-day pricing, the environment is complex enough that these effects are not easy to identify or manage manually. In fact, we've been doing a lot of work with our Revenue Management solution provider, IDeaS, to account for these effects in the pricing decisions provided by their system - and certainly finding opportunities for our clients who are in a top reputation position to be a bit more aggressive with their pricing strategies.

  2. Posted September 16, 2014 at 3:37 pm | Permalink

    Dr. Kelly - Great stuff, but follow up question if I may. Your study does not mention it specifically so maybe you have some insight elsewhere, but are you able to ascertain the impact on these decisions when business travelers have corporate rates with brands in these business centers?

    • Kelly McGuire Kelly McGuire
      Posted September 16, 2014 at 4:12 pm | Permalink

      Keith - thanks for the question! For this study we specifically looked at "unmanaged" business travelers, meaning that anyone with negotiated corporate rates that were required to book only at certain hotels would not have been in the sample. The reson for this was that if they were required to stay somewhere, UGC wouldn't matter - good or bad, they'd have to book. However, the business travelers in this study said they had some guidance in terms of how much they could spent, so most of them had to pay attention to that. So, I think the relationships in this study would hold if the rates that the business traveler were presented with were corproate negotiated (or some combination of corporate and not), provided the business traveler had the freedom to book a hotel that was not at negotiated rate. If corporate travel policy restricts to only one preferred hotel brand in any given market, then that would override any of the effects.

      • Posted September 16, 2014 at 5:43 pm | Permalink

        I think you will find it rate that a company has a rate with just one hotel; usually having a few around the area, so travelers have some options and the businesses aren't putting all eggs into one business. To that end, when you take rate essentially out of the picture, it would seem there would be greater emphasis on the UGC and reviews. To how much they are willing to overlook the "warnings" of reviews and in their "just ok" hotel decision making - points or no points.

        BTW- the percentage of non-brand programs is a little scary. Yet another indicator there is no such things a "loyalty" program and makes you wonder why hotels keep spending $$$ on supporting these programs.

        • Kelly McGuire Kelly McGuire
          Posted September 16, 2014 at 8:34 pm | Permalink

          re: the % of non-brand programs. We also asked them how often they stayed with their preferred brand in the last 12 months, and 68% stayed between 25-75% of the time - only 4% stayed 100% of the time - and you see that they had an average of over 2 memberships each - so yeah, these business travelers are not very loyal!

8 Trackbacks

  1. By Guess What Is More Important For Business And L... on September 2, 2014 at 3:06 pm

    […] With the growing popularity and availability of online reviews and ratings, consumers have more information than ever before when purchasing a hotel stay.  […]

  2. […] Source: blogs.sas.com […]

  3. […] further information – see my previous post which outlines the details of this study. tags: Cornell Hospitality Research Summit, Hospitality […]

  4. […] studi mostrano che non tutti gli ospiti rispondo alle recensioni online nello stesso modo. Uno di questi report, realizzato da Breffni Noone, professore associato alla Penn State University, e da Kelly McGuire, […]

  5. […] My own presentation was held in the Practice track, and all three of the presenters in this section focused on revenue management.  I presented “Revenue Management in the Big Data Era” where I focused on the industry and technology changes that are driving new challenges to revenue management, and how Big Data appears to offer the opportunity to face these challenges more successfully in the future – when that data is paired with new analytic approaches.  In my presentation I referenced several studies that are showing the potential value of big data to revenue management, including Kelly McGuire and Breffni Noone’s studies on Hotel Pricing in a Social World. […]

  6. By Navigando si impara on November 27, 2014 at 11:20 am

    […] studi mostrano che non tutti gli ospiti rispondo alle recensioni online nello stesso modo. Uno di questi report, realizzato da Breffni Noone, professore associato alla Penn State University, e da Kelly McGuire, […]

  7. […] in a Social World” research, co-authored by Dr. Breffni Noone from Penn State, including a blog summary of our project on how business travelers buy, and a video summary of the research results. Natalie […]

  8. By How Business Travelers Buy: Hotel Pricing in a ... on February 2, 2015 at 6:59 am

    […] With the growing popularity and availability of online reviews and ratings, consumers have more information than ever before when purchasing a hotel stay.  […]

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