Last week I discussed two research techniques which can be used when determining the optimum pricing strategy – Gabor-Granger and Brand Price Trade Off (BPTO). These techniques are beautifully simple, but this simplicity has a flip side.

  • The choice may be over-simplified and no longer reflect real-life decision scenarios which can be complex and based on a series of conscious and unconscious trade-offs
  • With the linear raising or lowering of prices, respondents can easily guess what the researcher is doing and may be tempted to ‘game’ the result
  • Prompting respondents with an initial price point will frame their subsequent responses and thus under- or over-estimate the true price they’d be willing to pay
  • Only allowing a binary ‘would buy/wouldn’t buy’ response doesn’t capture important shades in between where people start to become more or less comfortable with a particular price point

This week, I’ll look at two pricing research techniques which can overcome these issues – the Van Westendorp Price Sensitivity Meter and Conjoint Analysis.

The Van Westendorp Price Sensitivity Meter

The Van Westendorp Price Sensitivity Meter overcomes some of these issues by allowing respondents to choose their own price points and share more detail on their reactions. To do so, respondents are shown the product and asked to indicate:

  • The price at which it would be too cheap to be of credible quality
  • The price where it represents a bargain
  • The price where it becomes expensive, but not prohibitively so
  • The price where it becomes too expensive to consider

At each price point mentioned, the cumulative percentage of respondents placing the product into each of the four categories above is calculated. For example, in a study to identify the optimum pricing strategy for a Business School’s one-day courses for professionals we found the following pattern:

Pricing strategy research - van westendorp output

This chart can be interpreted as follows:

  • The product’s price should be set within a range that most customers would think about buying it. The lower limit is determined by where ‘too cheap’ meets ‘expensive’ (called the ‘point of marginal cheapness’), while the upper limit is found where ‘too expensive’ meets ‘a bargain’ (known as the ‘point of marginal expensiveness’).
  • The ‘optimum price point’ is one where the lowest proportion of customers are put off by the price because they consider it too high or too low. This optimum point can be found at the intersection of ‘too expensive’ and ‘too cheap’

So in this example, the Business School was advised to ideally set the price at £700 or failing that, somewhere between £650 and £800.

Van Westendorp is a simple and useful technique but has four drawbacks:

  • There is no competitive context
  • By focussing solely on price it can make respondents artificially price sensitive
  • It requires no price/benefit trade-offs as would be made in real-life scenarios
  • It doesn’t allow the creation of tiered offerings where customers can choose the ‘standard’ product or upgrade to an enhanced version for a price premium

These issues can be overcome by using one of the most advanced pricing techniques – Conjoint Analysis.

Conjoint Analysis

When people make real-life buying choices, they go through a complicated mix of conscious and unconscious trade-offs between the price and the features of a product. Conjoint Analysis aims to replicate this process. It identifies various parts of the offering (like product features and price) and the different ‘levels’ at which these parts could be realistically set. For example, the delivery feature of a product might be available as same day, next day, or within 48 hours.

Pricing strategy research - conjoint analysis attributes

Using this information, the conjoint algorithm creates a series of hypothetical products each with slightly different attributes and prices. These hypothetical offerings are then grouped into sets of 3 or 4 and respondents asked which one, if any, they are most likely to buy.

Pricing strategy research - conjoint analysis question

This is repeated several times until a large number of potential combinations have been compared across all of those people surveyed. In making these choices respondents are indicating, without knowing it, the relative value (called a Utility Value) they attach to different product features and their price sensitivity. This means that, following statistical analysis to identify patterns in the data, Conjoint Analysis reveals:

  • The relative importance of different product attributes and prices in driving demand
  • The optimum product proposition and price to sell this at to maximise revenue
  • How to tier products (good, better, best) and price them relative to each other

It also allows ‘what if?’ scenarios to be explored where the impact on demand of different actions can be estimated, e.g. How would demand change if the price was raised by 10%? What impact would removing feature X have on demand? What would happen to demand if feature X was kept but at a lower performance level?