If you had a billion dollars and only 24 hours to spend it, what would you do?

If I could trick my way around it, I’d invest it on treasury bonds so that I could cash it in later. If tangibility was the condition, then I’d spend it on an island and secure it fully to survive a zombie apocalypse (according to the Internet, it’s going to happen soon).

My point is, the world doesn’t just provide us with an unlimited budget for our unlimited wants. We all have to work within a certain budget and sacrifice most of our wants to secure what we need.


This is what our potential customers have to deal with as well. This is why testing price point is important.

In economics, we know that price of a luxury good is inversely related to consumption. It’s a technical way of saying that if your product does not fall into one of the basic needs of life, then more people will buy it only if it’s cheaper.

So the next best thing is to find an optimum rate that would strike a win-win balance between your income and the number of buyers. Here’s a table with hypothetical data to illustrate my point:

Price Test Table


And here’s how it would look like if you were to plot it in a graph.

Price Test Graph


The goal here is to identify the price that will give you the most revenue. And the best way to do it is to have different price tests so that you can measure the units sold for each price, put them in a table, and apply the data into a graph. You’ll be able to determine the price point that would benefit your company the most.

However, it doesn’t end there. Like any test, pricing should also be subjected to leverage. Look closer at my example above and you will notice two price points that generate the same revenue. They are: $60 and $70 with 70 and 60 units sold, respectively.

So which price tag should you go for? There are two scenarios that can optimize your revenue:

A. The lower price point ($60) will generate more buyers as it’s less expensive for the customers, but more costly for you

B. The higher price point ($70) will generate less buyers, but requires less effort and operational costs on your part.

But direct response marketers need to factor in their Customer Lifetime Value or CLV. Simply put, CLV is the estimated value or amount that each customer will spend on a company in their lifetime. This is especially crucial for marketers that cross-promote their products within their sublists.

In this case, option A proves to be a more beneficial game plan. Having a lower price point that generates more units (even if it generates the same revenue as a higher price point) will prove to be more profitable in the long run.

Would you or do you conduct price tests for your business? How important is finding the optimum price tag for your product to you? 

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