- How do I appeal to the largest number of consumers? (TURF analysis)
- How do I prioritise marketing messages or product attributes? (Max Diff)
- How do I find out what people value in my (new) product / service? (Conjoint)
- How do I identify what drives a desired behaviour or outcome? (Key driver analysis)
- How do I know what to prioritise to meet strategic goals? (Gap analysis)
- How do I build consumer loyalty? (Consumer journey mapping)
- How do I use behavioural science to improve my research? (Cognitive biases)
- How do I live without you? (LeAnn Rimes)
- How do I know how many people will buy my product at a given price? (Van Westendorp’s price sensitivity meter)
- How do I assess the impact of my advertising? (Ad effectiveness)
- How do I turn data into clear findings (Data visualisation)
- How do I tap into the unconscious perceptions that influence decision-making? (Implicit response testing)
- How do I reduce a large amount of data into something more meaningful? (Factor analysis)
- How do I group people together based on shared characteristics? (Segmentation) Scheduled for 14/05/2021
- How do I forecast market share at a given price point? (Brand price trade off) Scheduled for 21/05/2021
- How do I account for cultural differences when surveying across markets? (ANOVA) Scheduled for 28/05/2021
- How do I judge brand performance relative to competitors (Correspondence analysis / brand mapping) Scheduled for 04/06/2021
Why you need to ask if the price is right
Early on in my market research career I worked on a project involving dog medicine. Upon being allocated to the project team I remember wishing I was working on something a little cooler, but all these years later I still think the findings were fascinating. One of the main insights was that this particular dog medicine would increase its market share if it was more expensive.
The client wasn’t expecting to hear that if they charged more, they would sell more, and of course make more profit! In the absence of the end user (the poorly pup), being able feedback on how the medicine was helping, owners equated a higher price point with a higher quality, and therefore more effective product. It’s a niche example, but it nicely sums up how both the perception of price, and the price itself impact a decision to purchase. Conversely, sometimes a lower price point, if found more attractive by a large enough proportion of the right people, can also result in greater profit.
If you want to find out how changing the price (either up or down!) will impact take-up, there are a number of different research techniques that can help. But the most direct way to assess how many people will buy your product at a given price is to use Van Westendorp’s price sensitivity meter (PSM).
What is Van Westendorp’s price sensitivity meter?
Van Westendorp’s price sensitivity meter allows you to see how many people will buy your product across a range of price points. From this, you can calculate how total revenue might change if price is adjusted. The output also shows you the price point which the largest proportion of your target audience find acceptable, and the upper and lower limits of an acceptable price range.
The secret to Van Westendorp’s price sensitivity meter comes from calibrating the answers to six questions. Firstly, respondents are asked to identify the price at which they feel the product or service in question is:
- So inexpensive you would doubt its quality and not consider it
- A bargain – a great buy for the price
- Getting expensive, but you might still consider it
- Too expensive for you to consider it
Next, purchase intent is asked (typically using Newton Miller Smith’s purchase intent extension):
- If [product / service] was available at [insert bargain price chosen], how likely would your household be to buy / subscribe to it?
- If [product / service] was available at [insert getting expensive price chosen], how likely would your household be to buy / subscribe to it?
What does Van Westendorp’s price sensitivity meter tell me?
The first four questions are used to plot the cumulative proportion of consumers who find each price point too cheap, a bargain, getting expensive and too expensive. The intersections of these four perceived prices show where consumers expect your product / service to be priced.
Layering the data around price acceptability with intention to purchase at those price points then allows you to see the potential revenue each price point could generate, guiding decisions around how to price your product or service.
For the most accurate market view, intention to purchase as claimed in the survey can be downweighted to account for the fact that not all those who say they would purchase at that price will go on to do so, and / or to account for market awareness (in the survey environment 100% awareness is created in order to capture as much data as possible).