Conducting pricing research 

Editor's note: Bernd Grosserohde is the director, strategic solutions operations, product and pricing area lead at GLG.

GLG LogoEstablishing the right price isn’t easy. Value-based pricing helps you monetize a brand’s true value. It requires comprehensive knowledge of what your product is worth to your customer or prospective customers. 

Pricing insight is elusive

Value-based pricing should be tied to product development. Companies should develop products with a clear understanding of what customers value and what they’d pay for it. The willingness to pay, an essential – but elusive – insight. 

Historical sales numbers are not helpful. They describe prices customers have previously accepted but not what they will pay later. It’s also difficult to ask customers directly about price. Many will give a price below what they’re willing to pay.

Insights about customer’s willingness to pay are also time-stamped. Consider how the pandemic has disrupted people’s willingness to pay for travel or office space, or how cloud computing has disrupted the willingness to pay for software and infrastructure. Businesses cannot trust today’s value-based price to hold steady indefinitely.

It is almost always worth the effort of gaining insights into customers. But smart pricing requires more than asking about price acceptance in a survey. Pricing research should consider the customer’s perspective on the perceived value of products, benefits and features throughout the entire product life cycle.

There are two methods to discern customers’ willingness to pay. The first is a simple tool to understand price sensitivity in early product development. The second is more complex and extremely powerful. It’s an approach for innovation and for the optimization of product and price together.

Toward effective pricing research: Van Westendorp

The first method, Van Westendorp’s Price Sensitivity Measurement, identifies critical price thresholds, it does not directly ask about the accepted price. 

In a survey, we would introduce a product or service concept and ask, “At what price would you say that this product is cheap, so that you would doubt the quality? Or too expensive, so that you would no longer buy it?” This early insight can help to align product development and pricing from the beginning.

This method is not recommended for testing multiple concepts. If you have four ideas, you don’t want to ask these questions four times in a row in the same survey. If you want to understand what constitutes added value as perceived by customers, or to optimize the price architecture for a portfolio of products, there’s a better method.

Toward effective pricing research: conjoint analysis

Conjoint analysis, or discrete choice models, is popular across many industries. Many companies use the method regularly as they can see how accurately it explains and predicts the choices people make when buying products.

You can use conjoint analysis to price both products and optional features. It can determine the best feature and benefit mix in new product development. It’s also great for existing products that need to be adapted to changing customer needs.

So how does it work? We break a product into parts, like a house made of Legos. In a conjoint survey, respondents would not assess bricks, roofs or doors, they would choose among houses. From these choices, we can derive the perceived value of bricks, roofs and doors. These perceived values can then create “what if” scenarios and build hypothetical new concepts and products and simulate that preference share among customers.

In the conjoint exercise, we do not ask direct questions – we ask them to make choices. They probably won’t know that this is a pricing study. They are just expressing their preference. The goal is to learn how customers would choose in hypothetical situations, not to understand choice among current products.

Learning from data, as opposed to only having the data, requires a full grip of your underlying business goals. The two sides complement each other. Bringing methodology, expertise and subject matter knowledge together in an efficient way is a challenge, but it’ll be well worth the effort. 

Want to learn more? Visit