Price Laddering: An Effective Research Approach for Pricing Strategy

In research, the gold standard method for testing price points is through monadic design. But that method requires a large number of participants, and sometimes we don’t have that luxury. (See Rajan Sambandam’s White Paper – Monadic Price Testing vs. Price Laddering.)

In laddering exercises, we ask willingness to purchase at the price point of interest. Those unwilling to purchase are offered a lower price point, and we continue stepping down the ladder until we get a positive response, or we run out of price points.

The Gabor-Granger Pricing Technique

But what if you have a general idea how much you’re willing to charge, but could potentially charge more than that or less than that? As long as you have a range of price points to test, the Gabor-Granger technique can be quite useful. Rather than starting everyone at the top price and working down, participants are randomly assigned to one of the price points at the outset. Based on their willingness to purchase at that initial price point, they are then randomly assigned to a higher price point (if willing) or a lower price point (if unwilling). Their next answer determines their next path up or down the ladder. They keep moving throughout the ladder until they’ve reached the highest point at which they are willing to purchase – or not at all.

Depending on the number of price points being tested, this method can result in hundreds of potential paths through the ladder, which makes programming the exercise a monumental task.

The Price Laddering Technique

An alternative approach is to randomly assign respondents to one of the price points at the outset as described above, but after that always move them only one rung at a time up or down the ladder (as opposed to a random higher or random lower rung). This keeps the programming under control while still allowing for up/down movement throughout the exercise.

Regardless of which pricing research method is selected, results are aggregated for reporting purposes, so any potential biases inherent in each of the directional flows are smoothed out.