Catering to the Costco Mindset: Finding the ‘Sweet Spot’ in Quantity Discounts (Knowledge @ Wharton)
Most for-profit marketers do not want to give products away unless they feel they will benefit by doing so. Nor do they want to lower price unless they see it as a useful way of simulating greater demand. But, marketers often find that at some point selling their products below their regular price is something they must do. Of course, marketers can simply run a “sale” where the price is lowered from its listed price. However, the problem with most sale pricing is the lower price applies to every product purchased whether a single unit or multiple units.
To encourage customers to purchase multiple units, quantity discount pricing is used where marketers do not allow a discounted price to kick in until certain requirements are met. For instance, some marketers handle this by not lowering the price until additional products are purchased (e.g., “buy three or more and take $1 off each”). Other marketers may not want specifically to advertise a lower price, instead they choose to give away extra product if a customer purchases a certain amount (e.g., “buy three and get the fourth free”). As a pricing strategy, these methods of quantity discounting are widely used.
But what level of discount should a marketer offer to encourage customers to purchase more? This is a question tackled by sellers since the dawn of commerce when, most likely, street merchants and farmers’ markets enticed customers with quantity discount offers (e.g., “buy two onions and get another one free”). For many marketers, determining quantity discounts is done either by using historical industry discounting methods or by undertaking their own extensive research such as test markets.
But this story looks at another approach to quantity discounting in the form of a marketing research technique called conjoint analysis. In marketing, conjoint analysis is primarily used to see how customers make product selection decisions. In simple terms, conjoint analysis looks at how customers evaluate a product when presented with different sets of features. By changing which features are presented as well as changing the value of each feature (e.g., strong or weak), the marketer can then get an idea of the type of products customers prefer.
In this story, researchers from the University of Pennsylvania and Columbia University use conjoint analysis to suggest how a fictitious Internet movie distributor might best set quantity pricing if they were to compete against Netflix and Blockbuster. What is interesting is this method does not involve field testing (e.g., in-store testing) but only customers participating through survey-type research.
So even without testing the market with trial pricing plans, the researchers were able to calculate the likely optimal price for MovieMail’s DVD rental service. Iyengar and Jedidi contend that using a mathematical formula offers companies a money-saving shortcut to determining the best way to employ quantity discounts.
In addition to developing product features and pricing, in what other ways can conjoint analysis help marketers?
Image by MelvinSchlubman