The science of dating and house-hunting
How many dates do you need to go on before finding the right partner? Luckily (or not-so-luckily for some), mathematics can shed some light on just the right number of dates a person needs to go on before they should stop and commit.
There is a popular “optimal stopping” solution in the field of decision science, widely known as Rule 37%. Rule 37% says that in order to find Mr. or Miss Right, you should settle down with the next best person you go out with after dating 37% of the potential candidates in your lifetime.
Assuming an average Joe gets to go out on a date with 20 different candidates in his lifetime, Rule 37% says he should date at least seven people (37% of 20) and reject them, before settling down with the next best person he dates.
This maximizes his probability of finding that dream partner. For the more mathematically inclined, you can read more about the optimal stopping theory, also known as the secretary problem.
Settling down is no laughing matter. Arguably the only thing that beats getting hitched on the priority scale is buying a home. Fret not, for decision science solutions such as Rule 37% can be applied to a broad range of problems, including buying property.
Just following your heart may not always be right
How often have we been told to “go with your gut feeling” or “just follow your heart” when it comes to choosing a home? Counterintuitively, investing in million-dollar properties can still be a snap decision for many. First-day sales of new launches tend to yield better results than later-day sales, driven partially by herd mentality. Science provides a solution.
Suppose you have three months to buy a house (excluding another two months to sort out the paperwork to complete the sale) and you are only available to view the potential properties on weekends. If there are 12 weekends or 24 Saturdays and Sundays in three months, Rule 37% says you need to spend at least nine Saturdays and Sundays (37% of 24 days) viewing, assuming you view an equal number of properties each day.
Try to not commit to any of the places you see in these first nine days, unless the property is an exceptionally good deal. This step ensures you build up sufficient understanding of the types of property that might be suitable for you, such as the layout, facilities and level of furnishings.
From the 10th day onwards, get ready to buy the unit that is better than all the places you saw in the first nine days. Say, for example, on the 12th day of viewing, you find a place that is better than all the other places you have seen. Committing to it will be your optimal decision.
This process gives you the greatest chance of sealing the best deal without having to physically view all the available ones in the market, which would be a dreadful task given the time constraints. You also cut the risk of committing too early to a place you may eventually regret buying.
Strictly speaking, one of the key conditions of Rule 37% is that you can never revisit the properties you have viewed. However, this only applies in a fast-moving market or if the sample size is large; otherwise, you may not find a better property after rejecting those you have viewed. If the sample size is small, one can simply refrain from committing to the first 37% properties viewed.
The first 37% of the properties viewed serves to build your understanding of your personal preference
What’s the right price?
Nicholas Sparks, author of The Notebook, once wrote: “There’s no love like the first.” Inevitably, we tend to compare many of our life relationships to the first, regardless of whether or not it ended well. There is an aura of mystique to being the first.
In decision science, there is a term for this cognitive bias — anchoring. Anchoring is our tendency to rely too much on the first piece of information we received when making decisions. In real estate, this problem rears its head in its most important element — pricing.
Gregory B Northcraft and Margaret A Neale, professors from the University of Arizona in the US, conducted an experiment on real estate pricing and found that even professionals were affected by anchoring bias.
In the experiment, a group of real estate agents were each given a package containing information on a selected property, such as listing price, floor area, photos, layout and a summary of sales transactions in the neighborhood for the past six months. The only item that was different was the listing price.
Each participant received one of these four listing prices: a) US$119,900, b) US$129,900, c) US$139,900 and d) US$149,900. Participants were also brought to the property for a physical inspection and were then asked to provide a valuation of the property.
Surprisingly, estimates varied widely and were heavily influenced by the listing price. For example, agents who received the lowest listing price of $119,900 submitted conservative valuations of $114,204 on average.
On the other hand, agents who were given the highest listing price of $149,900 submitted bullish valuations averaging $128,754, despite being given the same information on the subject property, less the price.
Science as a solution
As players in the property scene, being aware of inherent problems and potential solutions is critical to helping you gain a competitive advantage. An understanding of simple decision science theories can provide practical rule-of-thumb solutions.