What does attribute-based shopping (ABS) mean for hotels?

Two modes of shopping commonly carry the name attribute based shopping (ABS). In the older form, widely used today, a consumer begins by choosing a hotel and stay dates and receives a list of rates. These rates correspond to combinations of room types and rate plans and each combination has a price. Both the room type and the rate plan for each combination have attributes. For example, a room type might have attributes like the bedding, max guest capacity or whether it has a view or a balcony.  Rate plans have attributes like cancellation policies or whether they include certain features like meals or prepaid Wi-Fi. Customers are not searching for those specific attributes, rather they’re filtering what’s been retrieved to find the best specific room type and rate plan for their needs. We’ll refer to this older shopping mode as attribute-based filtering.

In the new attribute-based shopping model, consumers don’t see the room type or rate plan combinations; they see a list of attributes they can put into a shopping cart to build the product they want. If Jon wants to stay at a particular hotel with his wife and they’re interested in a king bed with ocean view and a balcony, then he can specify those attributes without knowing the room type.  Each time he adds an attribute to the cart, the ABS engine prices that attribute separately and the consumer can see how each attribute affects the total price of the room.

What’s going on behind the scenes is very different from the attribute based filtering example. With attribute-based shopping, the hotel is not promising any particular room type or rate plan.  It must determine the price at which it will offer each attribute, based on the total inventory in the property that meets the consumer’s needs. As each attribute is added to the cart, it narrows the list of rooms that can meet the consumer’s need, so the CRS must determine the price of that next attribute going into the cart in real time.

This has two immediate effects: first, it allows the consumer to choose exactly what they want to pay for and nothing more, and second, by giving the hotel more flexibility in how it meets those needs, it could offer the customer a lower price than for a specific room type or rate plan while earning higher overall revenue. If the hotel has flexibility in terms of the room types that can be assigned, there are opportunities to optimize the room assignments and improve conversion.  For example, consider the following ‘traditional’ availability picture. For simplicity, let’s assume these are the only rooms in the hotel.

Room #	Bedding	View	Balcony	Cancelable	Wi-Fi	Breakfast	Price
1001	K	Ocean	Y	Y	Y	N	425
1002	K	Ocean	N	Y	Y	Y	400
1003	K	City	N	N	N	N	350

First, let’s assume we’re shopping in the filtering model and we present the consumer with room types and rate plans that include the above options.  If the consumer is interested in an ocean view king that has Wi-Fi and is cancelable, she will choose room 1001, thus removing it from availability for those nights.  If the next consumer wants a king room with ocean view and a balcony, there is no room type left that meets his needs. The second traveler may continue with a different product but they may also search other hotels or chains or other types of accommodations (e.g., home sharing) to meet their needs.

If, instead, the consumers are using ABS shopping for a king room with an ocean view and Wi-Fi, the first will see a price for those attributes, but not a specific room type, that she can book. The room assignment algorithm (which operates as the consumer is shopping, not on the night before arrival) might even tentatively assign her to room 1001. When the second consumer comes in looking for the king room with ocean view and a balcony, the room assignment algorithm can switch the first consumer to room 1002 and assign the second consumer to room 1001, thereby capturing two bookings instead of one.

The result of ABS in this case, is that the hotel could offer the consumer the package of attributes they want for less than the price of the RT/RP combo and still make more revenue. Let’s say the hotel offered each of the consumers in the example above the attributes they requested for $25 less than the associated than standard combinations.  In the first case, the hotel would have realized $425 in revenue for one room and in the second case they would have recognized $775 (425 -25 + 400 – 25) in revenue for two rooms.

Note that in the example above, the room assignment optimization algorithm for ABS shopping takes the room attributes into consideration when figuring room assignments, but does not consider the rate plan attributes like cancellation policy or Wi-Fi/breakfast inclusion.  These figure into pricing but not into room assignment because they can be priced and included or excluded as required to meet demand.

Of course, the big question is whether consumers will want to shop this way. The short answer is that, of course, some will want it, but it’s impossible to know how many without testing. Still, two things stand out: pricing and choice.  If, as we expect, the optimization of room assignments allows hotels to offer attribute bundles at less than the price of specific rate plans and room types, then customers will likely enjoy a price advantage. Regarding choice, consider an example where you go to the grocery store to buy bread and milk but the store only sells bags that are already pre-packed with multiple items. You can’t choose to buy just milk and bread, you have to find a bag that has milk and bread in it but you’re also buying other things you don’t need and, in some cases, can’t use.  That’s essentially what hotels are doing today—selling packages of attributes where some customers would prefer to go a la carte. ABS lets consumers buy, and pay for, only what’s most important to them.

We hear about disruptive technologies, innovations, or companies every day; often with little relation to its original meaning. Giving consumers more of what they do want and less of the fluff they don’t, especially at a better price, has been a key to success for many companies. Just ask Ikea and Southwest Airlines.

How will ABS functionality change the way hotels engage with the booking process via their existing systems?

Central Reservation System (CRS): While changes to the CRS will likely be significant, they will be incremental. ABS functionality will not require a complete refactoring of the current data model and for the foreseeable future, the attribute-based filtering model and the attribute-based shopping model will continue side by side.

Property Management System (PMS): The greatest impact on PMS is that hotels will no longer be able to hold inventory at the property level without fully exposing it to the CRS. The CRS will need a complete view of inventory, both allocated (for traditional shopping) and unallocated (for ABS shopping.) Many of the internal functions for PMS, such as housekeeping scheduling, will also have to adapt.

Room assignments: Traditional room assignments today are often manual processes and done the day or evening before check-in. In the ABS world, room assignments are the result of an optimization algorithm that will have to run at the CRS level with full knowledge of all inventory that will be sold through ABS. Assignments would ideally be run after each room is sold, though it may be possible to use approximations that will work between optimizations.

Pricing: Today’s revenue management systems operate with RT/RP in mind. Adopting ABS will require new processes to price attributes based on attribute inventory, forecasted demand, and other factors unrelated to RT/RP combinations.

Loyalty systems and CRM: ABS offers a unique opportunity to morph loyalty programs into something much more effective and specific to the consumer.  With ABS, hotels can now see exactly what their customers really want, rather than what they say they want. Instead of being forced into the RT/RP combinations available today, they can tailor their loyalty programs directly at those attributes. Hotels will be able to tailor offers in the moment, based on earlier attribute purchases combined with current behavior.

Internet shopping: CRS-connected internet booking engines are the likely first place ABS will appear but GDS will be able to offer it as well. Because ABS must be done at the CRS level and the CRS must work with the pricing, room assignment, and loyalty functions in real time, it’s not possible to push attribute prices to an OTA cache through an ARI upload.  That means that the bigger OTAs that shop their own caches Pcan’t offer ABS—only entities that shop directly through to the CRS will be able to do it. OTAs that cache will be restricted to offering the conventional RT/RP options they do today.

Rate comparison shopping: ABS presents a problem and an opportunity: It’s a problem in that hotels will not be able to compare ABS pricing with competitors, though they will still be able to compare RT/RP products as they do today. It’s an opportunity since hotels will be able to offer lower priced ABS products without OTAs or other distributors claiming they’re not getting the best available rates. The ABS model can’t be compared to RT/RP products, nor can it be effectively rate shopped because of its fully dynamic nature and the huge number of possible attribute combinations.

Benefits to Hotels

• Lower prices, higher conversion: Hotels will have the ability to potentially offer consumers lower prices on specific ABS products while improving revenues due to higher overall conversion.
• Ability to offer consumers customized products: No longer limited by the conventional RT/RP combination offers, hotels can offer consumers more customized products. (If you’re wondering if consumers will put up with less certainty, look at Hotwire.)
• Better information about what customers want: Hotels can derive more exact information about what their customers really value, as shown by their willingness to pay for it.
• Richer cross-selling opportunities: With ABS, rate plan attributes become just a set of ancillaries that can be combined with the room. There is no difference between adding breakfast or a 10-day cancellation policy vs. a bottle of wine or a spa treatment.  Hotels, and consumers will think about the room separate from the attributes they want to add to it.
• More flexibility in creating room types: By better understanding exactly what customers want, hotels can rearrange and recreate their room types to better align with real customer needs. They can also use this data to shape future hotel builds.
• Hotels can recapture product value: ABS products cannot be shared with OTAs or wholesalers, which means hotels can recapturing value that would otherwise go to the distributor.
• Added pricing flexibility: Hotels gain more freedom to adjust their ABS pricing dynamically and out of the range of rate shopping services.
• It’s future-proof: As new interaction channels continue to emerge, including voice and text, the ABS model will stand up to time. It would be much simpler to send a text that reads, “Find me a room with a king bed and Wi-Fi in the Acme hotel next Thursday for two nights,” knowing they’ll receive the lowest priced room that meets those needs. The same voice command could be stated by saying “Alexa” first, to make hotel bookings simple enough to do with voice services. Try that with RT/RP combinations!

Benefits to Consumers

• Lower prices: While more analysis is still needed, the opportunity to improve revenues by optimizing room attributes looks promising. If they can be raised enough to improve profitability for the hotel while reducing unit prices for consumers (and removing middlemen,) it will be a win for both hotels and consumers.
• Improved availability: As hotels get better at optimizing room attributes at a more granular level, the chances for a guest getting what’s important to them at the right price will improve.
• A simpler shopping experience: Consumers will no longer have to compare room types and rate plans across 10, 20, or more combinations, often having to click down to details to get the info they need to understand exactly what they’re buying.
• More targeted offers: Hotels can achieve more targeted offers as a result of gaining a better understanding of what their customers offer.

The Opportunity for Change

In this article, we defined and examined ABS, distinguished it from its predecessor, explored its impact on hotel systems and presented the benefits to both parties. While the benefits to hotels and consumers are clear, the challenges of its rollout are not yet completely determined. Even so, this future-proof, flexible functionality presents a rare, enduring opportunity for hotels to get closer to their customers and at the same time, improve revenues.

The process of shifting to ABS is a complicated and potentially lengthy one that will likely inspire lively debates about how to achieve it successfully. Some changes will be harder than others but the best approach is an incremental one; hotels and third parties should embrace a hands-on, trial-and error approach to ABS, with a focus on early adoption. Hotels that embrace ABS sooner than later will have the advantage of refining the process and creating a virtuous cycle, particularly as companies start to use AI for the more complex algorithms. Those that wait a year or two increase the risk of losing competitive advantage.

In the book “Blue Ocean Strategy[1]” the authors argue that true innovations are those that offer better products and lower prices – a fitting description of ABS. How would implementing ABS functionality into your booking experience impact your culture, hotel systems and bottom line?

[1] www.blueoceanstrategy.com