⚠ We would appreciate if you would disable your ad blocker when visiting our site! ⚠

We Know Why You Stay (No, really we do. You told us.)

Order a reprint of this story
Close (X)


To reprint an article or any part of an article from Hospitality Upgrade please email geneva@hospitalityupgrade.com. Fee is $250 per reprint. One-time reprint. Fee may be waived under certain circumstances.


October 01, 2012
Value Pricing
Mark Hoare

View Magazine Version of This Article

Part two of two

In the previous issue the focus was on repointing thinking toward the fundamentals of value-based pricing, and aligning that to a rejuvenated understanding of guests, why they stay and how that directly affects their perceived value proposition at the time of shopping and purchasing the products being offered.

This article takes a step back to review an established and powerful tool that has been used across many industries, including: airlines, retail, insurance, financial services, healthcare and hospitality. This tool helps to qualify and quantify what it is that customers value most, what trade-offs they are prepared to make and how it drives their purchasing selections, especially when there are so many alternate hotel products from which to choose. 

Many hotels and hotel companies set out their stall neatly with what can only be described as experimental products and pricing, based on what they think their hotel product (the stay) is worth rather than definitively knowing that they have the right price point and value proposition for their guest mix. Others elect to replicate a successful property in their area and peg their services and pricing to that of their competitors. Not a totally ruinous approach, but the opportunity for those hotels to be leaders in their markets rather than followers is next to zero.   
So how does a hotelier set out and qualify exactly what it is the travelers to the destination want from their hotel stay, and quantify the value they attribute to that experience? The answer is by using conjoint analysis.  

Conjoint analysis is a proven tool or technique for evaluating consumer preferences for product features. It is most powerful when identifying which attributes and conditions are proven to best influence the consumer in making the actual purchasing decision. The objective is to collate conclusive data on what variables the consumer values most. With this intelligence in hand, product management can construct products and service bundles combining the most popular features. Essentially it is all about understanding consumer choices and the trade-offs they are willing to make. 

The Basics
In order to better understand conjoint analysis let’s use a hotel industry example. Consider a guest wanted to reserve a hotel stay and he or she had a choice of spending $120 or $190 for a room night. If this was the only consideration then the choice is clear, the lower priced room night is favorable. What if the only consideration in booking a room was the comfort of staying in an oversized room? If room size was the only consideration then the guest would probably prefer an oversized room over a regular sized room. Finally, consider that he or she can have a room with a sea view or a room with a property view. Almost everyone would favor the ocean view.

However, in a real purchase situation, consumers rarely make purchase decisions based on a single attribute like comfort. Consumers examine a range of features or attributes and then make choices or trade-offs that drive their ultimate purchase selection. With conjoint analysis the consumer examines these trade-offs to determine the blend of attributes that will be most appealing to the consumer. By using conjoint analysis the hotel company can determine the optimal features for its product or service. In addition, conjoint analysis will identify the ideal marketing message by identifying the features that are most aligned to the guest’s reason for staying. 

Basic Example
By way of a basic example, conjoint analysis presents choice alternatives between products/services defined by sets of attributes. Using the individual choices mentioned above, and the table below, we see that if size of room, price and view are the only choice attributes, there are still numerous combinations of stay options. (See below)

Offer     Room size          Price         View
1              over-sized         $190         property view
2              standard size    $190         property view
3              over-sized         $120         property view
4              standard size    $190         ocean view
5              over-sized         $190         ocean view
6              standard size    $120         property view
7              standard size    $120         ocean view
8              over-sized         $120         ocean view
Given the above choices, offer No. 8 is the most likely preferred choice, while offer No. 2 is probably the least preferred offer. The preference for the other offers depends on the needs of the individual guest.

Conjoint analysis can be used to determine the relative importance of each attribute, attribute level and combinations of attributes. If the most preferable product is commercially unviable, most likely offer No. 8, then conjoint analysis will isolate the?next?most preferred alternate offer.

When used in conjunction with specific traveler segment intelligence such as demographics, physiographics, purpose of travel and gender, hoteliers will be able to identify market segments for which distinct products may be attractive. For example, the leisure traveler and the business traveler may have very different preferences which could be met by developing targeted hotel stay offerings.

When shopping products, consumers will always be making trade-offs. A guest might like the luxury of an oversized room and the prospect of a sea view, but will pass on the offer due to price. In this case, the price has a high utility value. Utility can be defined as a number which represents the value that consumers place on an attribute. In other words, it represents the relative worth of the attribute. A low utility indicates less value; a high utility indicates more value.

The following presents a list of supposed utility values provided by an individual guest:

Comfort             Utility
oversize             38
standard size    19

View                   Utility
ocean view        18
property view   11

Price                   Utility
$120                    45
$190                      7

A number of insights can be derived from these utility scores. First, a greater value is expressed for the oversize room (38 vs. 19), a moderately greater value is placed on a sea view over a property view room, but a much greater value is placed on the $120 price over the $190 price.  It is also possible, and encouraged, to average all the respondent’s utilities and also explicit sub-segments of respondents. The importance of an attribute can be calculated by observing the difference between its lowest and highest value, referred to as the range. That range denotes the maximum influence the attribute can contribute in an offer to that guest. In the above example:   

Room size Range = 19  (38-19)
View Range = 7            (18-11)
Price Range = 38          (45-7)

In order of impact, these ranges indicate that price is the primary driver, room size is next, and view is relatively unimportant. This individual guest will make the purchase decision on price then comfort, with little regard for view. However, if this particular respondent was a leisure traveler, staying for multiple nights, view may very well have had a much greater range and accordingly weighed more heavily on his or her purchase choice. By using these conjoint analysis techniques, it is possible to not only evaluate an existing rate and selling strategy for validity, but can also be used to qualify new products and their combinations of attributes ahead of offering them to the market. This is referred to as what-if analysis.

For example, a hotel may look to attract more mid-week business travelers to the property and wanting to know the optimal combination of attributes in a new business rate that will appeal to business travelers using upper mid-scale market class hotels. Deriving range values for each of the following attributes would be appropriate: price, guarantee/cancel policy, complimentary breakfast, in-room task area, oversized room, complimentary Wi-Fi, double airline miles and executive lounge access.

For a new leisure rate the influencing attributes to be assessed would differ, and perhaps include: price, children free, view, deposit policy, day spa access, late checkout, airport transfers and discounted local attractions.

A what-if analysis undertaken over the same respondent dataset could also include evaluating the influence of attributes within the single product offering. Determining the propensity for a guest to purchase the leisure product above if the price were 10 percent, 15 percent or even 20 percent lower.

To further amplify the relevance of conjoint analysis to the hotel industry, back in the mid-1980s Marriott set about defining a new hotel brand that would align with the business traveler who averaged six trips per year staying in motels or mid-tier hotels, and the leisure traveler who traveled on average twice a year staying at hotels and motels. Rather than design the new hotel product based on what the company presumed it knew through observation of these two segments, Marriott let these two segments define the new product (brand) for it. At the core of its information-gathering process was conjoint analysis.

In Marriott’s case it was developing an entirely new hotel brand from scratch, and one might argue that it was the most extreme application of conjoint analysis seen within the industry. The process gave birth to Courtyard by Marriott, and even the brand name was chosen through the analysis process.

For insight into the scope of the endeavor, Marriott established its optimal hotel design by factoring in seven primary hotel features (facets): building shape, rooms format, food-related services, lounge facilities, non-room services, leisure facilities and security factors.

Across these seven facets were 50 attributes comprising 160 attribute levels. The survey’s resulting output was at odds with the in-depth experience of Marriott executives who had expected that a smaller version of a typical Marriott hotel was needed. To their surprise the study resulted in a hugely successful new product that was distinctly different from the incumbent Marriott hotel product, with clear appeal and alignment to a distinct target market segment.      

Is conjoint analysis right for me? As we have seen there are numerous, relevant applications for conjoint analysis at all levels within the industry. If a hotelier is seeking to configure a defined collection of attributes for a product and the consumer’s purchase decision will be rational, conjoint analysis can definitely work. However, if the purchase decision is in any way driven by impulse or by image, then this technique will not be of benefit. Fortunately, this article focuses on using conjoint analysis in support of developing a more consumer-aligned rate and selling strategy, and for this conjoint analysis excels.

A closing example of applicability is a hotel that was witnessing pressure from a lower-priced alternative and contemplated lowering its own prices. Then, the results of a conjoint analysis showed the market valued its products differently from the competitor’s. The first hotel chose not to lower its prices, but to slightly reconfigure its offering. As a result, bookings increased and the property realized incremental revenues that it otherwise would have never seen. Not every situation is as dramatic, but when conjoint analysis is done right it is powerful.

How to Move Forward 
Designing, conducting and analyzing a conjoint analysis study is possible, and there are software products available to help. Nonetheless there are many nuances and important decisions to make in each step of the process. For example, there are different conjoint methodologies, each with its own approach to data collection. The one that is appropriate depends on the objectives of your study. Unless a property already has a trained in-house resource who will execute several conjoint studies per year, it’s likely that it will want to engage someone with experience in the field to help navigate these nuances and then construct and execute your study according to the market the hotel is in.   

Mark B. Hoare, is a partner with The Prism Partnership LLC, which operates a marketing practice and a research and survey practice, both having real-world experience in the use of conjoint analysis. For more information, please visit www.theprismpartnership.com or call (404) 424-9258.

©2012 Hospitality Upgrade
This work may not be reprinted, redistributed or repurposed without written consent.
For permission requests, call 678.802.5302 or email


want to read more articles like this?

want to read more articles like this?

Sign up to receive our twice-a-month Watercooler and Siegel Sez Newsletters and never miss another article or news story.