Try not to think too much and give a quick answer: Let’s suppose one of your friends is looking for an external hard-drive. She has checked the different options available for a specific well-known brand and needs your advice on the best choice. The options are listed below:
- A – 500 GB / 100 €
- B – 750 GB / 240 €
- C – 1,5 TB / 215 €
Already have it? OK, we’ll review that later 🙂
This basic set of three options and their configurations on price/capacity are not random. When pricing products, there are some contextual effects one can use to enhance the performance of a particular option. In this post we are going to review one of them, but there will be more in the posts to come.
Market always has the last word in pricing discussions, but contextual effects could be very powerful and interesting for certain situations, complementing the final decision.
Let’s begin by introducing the best known of them: the decoy effect.
I am going to use a well-known example, first introduced by Dan Ariely, professor in Duke University and MIT and researcher in the field of behavioral economics. Dan was curious about why the Economist newspaper was providing these three subscription options. Two options providing different value at the same price…
When he asked his students about these three options, the answers were as follow:
- A- Web subscription: 16%
- B- Print subscription: 0%
- C- Print & Web subscription: 84%
Quite logic, isn’t it?
One of the main assumptions of decision making (IIA) states that if some option receives no support, to present it or not is not going to alter the final outcome (market share of the rest of options).
Let’s say you are choosing between an iPhone 5 and a SGalaxy 4. Suddenly, the guy of the store adds an old Nokia 3310 as a third alternative. I am sure you would agree this third option is not going to make a difference at all in your final decision.
So, considering that no student was selecting the undesirable option B, let’s remove it and see what happens when the questionnaire is used again in another group of similar students. When only considering options A and C the outcome was:
- A- Web subscription: 68%
- C- Print & Web subscription: 32%
So, what happened here?
That third option (B) was useless from the point of view that no one is selecting it, but it was really useful considering that it increases the market share of the most expensive option. So what exactly is that option B?
This option B is what is called a decoy option. By introducing a third alternative with no real value to the costumer, her/his perceptions about the rest of the options could be modified and directed towards one specific option. The key to define a third option acting as a decoy is to focus on their attribute levels. Define a target option, set their attributes, and then just introduce a third option (nearly or completely) dominated on these attributes. This easy and simple mechanism has proved a very robust behavior across multiple fields of research and practical applications.
Understanding the mechanics underlying this effect requires some more lines and thorough reading. However, if you are interested, I can recommend you some good papers on the topic. I’d be glad to get in touch!
Now it’s time to rethink what would have been your decision about the hard-drive without considering the initial option B…
Next time you configure a random product through multiple selection processes, think about it. Even when you choose some tapas this summer from a Spanish bar’s menu, just think if that medium size tapa costing nearly as much as the big one is really a non-sense option 🙂David González