Classic survey methods for finding optimal prices - In focus: Van Westendorp method

Originally published on: supra.tools/key-articles

The central bottleneck in developing a pricing strategy and pricing, in general, is knowing what the customer is willing to pay. Therefore, early techniques have emerged to mine this information; the first-mentioned here are the Gabor-Granger and Van Westendorp methods. These classic methods have an obvious price advantage. They are simple and inexpensive. Moreover, they are understandable and can be easily explained to a larger team of decision-makers. Reason enough to want to understand exactly what classical approaches can do and where the limits are.

Many aspects are involved if you look at textbooks and reference books on pricing. It is about determining the optimal price for certain constellations from the price-sales function. It is about how the situation changes when there is a sales intermediary – the trade. It is about the specifics of new products, price bundling, and assortment pricing. It is about organizational promotional tactics. It is about the psychological effects of anchor prices, sequence effects, the influence of graphic design, it is about threshold prices, and and and.

All these specialized books presuppose that it is known how customers react to prices and the change of these up to the purchase resistance with a product or a service quite fundamentally. The object of desire is formally called the price-demand function or price elasticity.

It is all the more astonishing that three facts have to be stated:

1. the pricing literature does not deal with how to find and validate the information that is crucial for pricing.
2. pricing literature wrongly assumes companies have the information about what customers are willing to pay across the space of possible prices for all their products.
3. pricing practice shows a different picture: for almost all SKUs in B2C, this information is not available.

Only selected new products are analyzed today. Large players afford sales modeling where price-demand functions for certain products in certain markets can be calculated for a narrow price spectrum based on real shelf prices and sales volume data. However, these are limited to narrow price ranges and existing products.

In short, there is a clear need to understand customer price willingness and exactly what their price sensitivity/price sensitivity is, and how at what price points.

What does methods for measuring willingsness-to-pay need to be able to do?

If one is striving for broader use of willingness to pay measurement, four objectives are key:

–?Easy to set up: Ideally, companies should be able to set up the measurements independently without resorting to a special market research industry. Even medium-sized companies often have hundreds of SKUs, hundreds of new SKUs every year and therefore need a solution for all products.

–?Cost-effective: In line with the number of SKUs, the price per measurement should not represent an insurmountable investment, as the investment required can scale quickly over hundreds of SKUs.

–?Easy to interpret: Insights can be implemented most effectively in the enterprise if they are easy to access and understand.

–?Reliable, accurate enough: The simplest, cheapest, and most intuitive solution is not worth implementing if it does not deliver valid results. Biased information can even harm. However, if the information is indicatively correct, an inaccurate estimate may be better than not performing one and relying entirely on expert opinion.

Procedure in practice - RedBull and Van Westendorp Price Sensitivity Meter (PSM)

When RedBull invented the energy drink, the price issue had to be resolved as with any new product. It was clear to the creators: the willingness to pay is largely driven by how well the holistic added value and benefits are communicated. Drinks with bold “stimulant promises” already existed at that time.

After this groundwork was exemplified, the brand conducted a Van Westendorp NSS Price Sensitivity Meter (PSM) analysis. This process is designed to explore the space of possible price points.

It revealed a willingness to add a price of 20% to a maximum of 50%. However, the brand later opted for a much higher price premium. Why?

Van Westendorp determines the price space where most potential customers consider price points fundamentally acceptable. However, this price space changes fundamentally when looking at a narrower target group.

This is exactly what RedBull did and found a price potential of almost 300%.

However, valid price optimization is not possible with the van-Westendorp Price Sensitivity Meter. “Why?” more on that in a moment.

Therefore, Gabor-Granger was used next. It enables an estimate of the demand created given a price.

The optimization results were then validated and calibrated in test markets. The rest is history.

Here’s how it works methodically:

Van Westendorp Pricing Model - approach, advantages, limitations.

The Van Westendorp Pricing Model originates from market research, was developed in 1976 by Peter Van Westendorp, and is based on these four unaided questions:

1. at what price would you consider the product so expensive that you would not buy it? (Too expensive)
2. at what price do you think the product would be so cheap that you would feel the quality could not be good? (Too cheap)
3. at what price do you think the product is so expensive that you would have to think about buying it? (Expensive)
4. at what price of the product would you call it a bargain – a good deal for the money? (Cheap)

The success of the evaluation of the Van Westendorp Pricing Model is calculated as a percentage across four metrics for each price point and rated by respondents as follows:

–?Too Expensive: This or lower prices are perceived as too expensive.

–?Too Cheap: This or lower prices are NOT perceived as too cheap.

–?Expensive: This or lower prices are found to be expensive but still acceptable.

–?Cheap: This or lower prices are perceived as NOT cheap.

The intersections of these metrics mark the price range and the (supposedly) optimum price point.

–?Lower price limit of the price range: Expensive=Too Cheap. The price that more people consider “expensive/still acceptable” than people consider the product “too cheap.”

–?Upper price limit of the price range: Cheap=Too Expensive. A price that more people consider “too expensive” than people consider the product “cheap.”

–?Optimal price point: Too expensive=too, cheap. Price at which the number of people who do not consider purchasing because the product is too expensive or has too cheap prices is minimal.

The methodology is suitable for exploring the acceptable price range of possible price indications without any influence. The evaluation logic has a plausible appearance but is a good example of how misleading plausibility can be.

It already starts with the fact that the price at the “too expensive = too cheap” point is by no means one of the prices where the sum of both numbers is minimal. This is often true, but it is rather coincidental.

Furthermore, the evaluation logic is based on the idea of finding the prices with the highest demand. This idea is suitable for identifying a price corridor to search for the optimal price points.

However, it is not suitable for profit-optimal pricing. This is because optimal prices maximize profit, not sales. Profit depends on the margin that results from prices.

It is an open secret in user practice (which is interestingly not reflected in the language of the pricing literature) that the Van Westendorp method may be a way to identify price corridors. Still, it is unsuitable for getting a good handle on the issue of price optimization.

Limitations and advancements: Simple, inexpensive, and accurate methods.

The van Westendorp method allows us to explore the framework and the price spectrum of possible prices in an unbiased way.?Garbor-Granger?is the simplest method to enable meaningful profit-maximizing price optimization.

Both methods are subject to strong survey biases in some cases. Depending on the context, respondents tend to underestimate their willingness to pay. The extent of the bias varies greatly in individual cases, so it cannot be anticipated across the board.

The quality of the survey also depends on the realism of the product description. Products whose willingness to pay is largely determined by the price of the comparison product (shelf neighbor) should be presented in the same way: a shelf example with an anchor price of the shelf neighbor. For this case, the two approaches measure a price-premium propensity score rather than the price-demand function.

To avoid the response bias regarding the underestimation of willingness to pay, so-called indirect methods have been developed

–?Conjoint Measurement

–?NeuroPricing?

–?Implicit Intelligence?

The first two groups of methods do not meet the characteristics listed above. They are not easy to set up and easy to interpret, nor are they cost-effective.

Implicit Intelligence??is an exception. Here, measurement methods from Neuroscience are used and calibrated with Causal Machine Learning. While the methodology is elaborate, it is as simple as?Garbor-Granger?for the user, and the cost is also moderate.

The methodology has been tested and perfected by?Supra.Tools?experts since 2016. They are a valuable addition to the spectrum of methods for price optimization.

Learn more about?Implicit Intelligence??in this article.