There are a number of behavioral economics concepts that can have varying degrees of practical usefulness for your business, depending on the industry, but are (imo) all useful as food for thought in your day-to-day decision making processes.

-The Decoy Effect (https://en.wikipedia.org/wiki/Decoy_effect)
The decoy effect highlights the importance of thinking through the structure of tiered product pricing. If you're wondering why newspaper sites like the Economist or WSJ offer digital+print subscriptions that are closely, if not identically, priced to just print subscriptions, this concept helps explain that. Essentially, when you have a menu of prices, carefully creating one or two throwaway options helps make your other offerings seem much more reasonable.

(See the related concept of anchoring below)

For some real world examples, see:
https://www.economist.com/blogs/democracyinamerica/2009/05/t...
http://www.nytimes.com/2006/10/21/dining/21plate.html

-Base Rate Neglect (https://en.wikipedia.org/wiki/Base_rate_fallacy)
This explains why many people ignore general prior probabilities, and focus on specific given probabilities. Give the Wiki a read, there are some pretty stark examples of decision making gone wrong.

A closely related example of this from Bayes' Theorem is the following classic: http://sphweb.bumc.bu.edu/otlt/mph-modules/bs/bs704_probabil...

Base rate neglect can help explain why people dramatically overestimate the accuracy of things like medical tests. Understanding what a "99% accuracy rate" really means can have life changing consequences.

-Sampling Bias (https://en.wikipedia.org/wiki/Sampling_bias)
This serves as a counterpoint to a practice some of the other commentators in this thread have mentioned, i.e. "asking your customers". If your end goal is to serve a diverse set of customers, it's essential that the sample of potential customers you're asking is not biased in some extreme way. For example, asking customers who are only from a specific geographic region, are only of a specific size in terms of headcount, revenue, etc.

I can't find the exact HN discussion, but there was a post that was a stark example of this a few months back. The gist of the post was that someone had built a software business that was able to address a niche accounting problem that many of his local plumbers (electricians maybe?) faced. He grew it to $500,000 in revenue relatively quickly, only to find that very few other plumbers across the country had this accounting challenge. This entrepreneur eventually shuttered his software business, since future prospects for growth were negligible.

-Anchoring Bias (https://en.wikipedia.org/wiki/Anchoring; see in particular the "negotiations" section)
Anchoring has direct applicability in pricing and negotiations. IMO anchoring bias is why if you feel that you are charging too little for your product, raise your prices sooner rather than later. After a certain amount of time, your customers will be "anchored" to that previous price point, and will be quite unhappy with a price increase.

-Sunk cost fallacy (https://en.wikipedia.org/wiki/Sunk_cost#Loss_aversion_and_th...)
This fallacy is quite prevalent in the real world. It's particularly egregious in the defense contracting world, where defense contractors have convinced the US Congress to fund projects that are years behind schedule, and billions over budget. The fallacy can best be described as "throwing good money after bad".

I'd like to note that sometimes this concept is over-applied. If you budgeted $10 for a project, and at the $10 spent mark you discover you need to spend $1 more to complete it, it's not necessarily falling into the fallacy to spend that $1 if the end benefit from that completed project still justifies the overall cost.