In my last post I compared online consumers to stock investors, where uncertainty adds a risk premium that decreases the price at which buyers are willing to pay. In this post, I would like to discuss specific examples for booking hotels online.
In Funnelscope’s analysis of tens of thousands of consumer reviews and ratings, one of the key determinations for consumers having a great or unpleasant experience with a hotel is a function of expectations. If there is a positive surprise, the hotel gets rave reviews. Any negative surprise, the hotel (along with the website that booked the hotel) gets dinged. I have been using the analogy of markets to describe online consumer behavior given the strong similarities. In markets, if a company announces earnings and comes in below expectations, the stock often gets crushed. And vice versa when the company announces earnings above expectations. The term “expectations” is key. This is where Funnelscope sees huge opportunities of improvement for the online consumer. The problem is that the data is still simply not good enough. Let me explain.
There are several effects that must be taken into account. The first order effect is actually quite obvious, although data for this is not easy to distill without a lot of time and effort. Let’s consider examples where you booked a hotel for vacation. Would you be happy if the room was extremely small such that you could hardly walk around? What if the amenities in the room were below average? What if the TV was not digital or had limited cable channels? How about if the room was great but the bathroom was small or dingy? Or how about if the room was great but the bed was uncomfortable? What if the bathroom only had a shower and no bathtub? Perhaps upon checking in you find that parking is $40 per day extra– wouldn’t you have wanted this information beforehand?
I can keep going but I believe the point has been made. My guess is that at least one of these things would be very bothersome to you. And the data shows that to be the case, since these are examples of critical factors that determine whether someone has a good hotel experience. Funnelscope’s technology has identified and created scores for these critical factors– initially for hotels and soon for other travel / local related services.
Bottom-line is that it all comes down to data. If online consumers had the data to measure and compare places on the attributes they care about, then their experience would be much better. The reason is because it provides a better picture around expectations. As I suggested in my last post, by reducing uncertainty, consumers would likely be willing to pay a higher fee to have this confidence. And I note above that the data also shows consumers place blame on the website they booked from if the experience was worse than expectations.
There is also a second order effect that makes this even more interesting. Using my markets analogy again, if the earnings of a company are not good but the investor knows they are buying at a low price, then expectations are met and everyone is fine. This goes for booking hotels as well. So not only are the data scores valuable, but the scores to price and expectations for a hotel determine customer satisfaction. Online expectations are typically created by the overall rating a hotel his given (i.e., number of stars) and price.
The problem is that Funnelscope has found ratings / scores within review and hotel sites to be too simplistic. One rating does not fit all consumers. For example, a rating for a hotel could be high yet the rooms are quaint, tiny, and romantic. If a family books the hotel with two kids and there is no room to move around, the experience will be unhappy even though the hotel is a quality one. So there needs to be a more detailed scoring system that gives online consumers greater information. This, in turn, allows expectations to be better met and therefore a more fulfilling service from the website that booked the hotel and the hotel itself.
Also, with price such a critical factor in determining expectations, there needs to be a better understanding of value. Value is not the same as budget versus luxury. There can be good value at luxury prices and good value at budget prices. So there needs to be a way to measure value and share this with online consumers so their expectations can be managed.
Lastly, there is a third order effect that is a function of temporal data. This can reflect the delta of various attribute scores for a hotel (i.e., how the scores change over time) or something as basic as hotel renovations. Take the circumstance where you book a luxury hotel but you happen to get here and it’s under renovation– wouldn’t it it be extremely valuable to have an indication of that information when you were booking the hotel?
These are the kind of data metrics that Funnelscope specializes in, and sees as critical to improving the online consumer experience. It all comes down to better data and reducing uncertainty.
