Is it just me, or does a $5 coffee irritate you too? It's that little bit too expensive to swallow, right?
Or how about the other way around... does the new iPhone crossing that $1,000 boundary feel like you're guaranteed to experience excellence?
In this post we explore how psychological price barriers affect consumers' purchase decisions, and help you optimise your product's pricing (for your consumers and your business), weighing up traditional pricing research methods and sharing PLAY's bespoke approach for FMCG products.
The coffee problem.
Just recently, a few of us from PLAY went to the local coffee shop to get our required morning dose of caffeine and something slightly upsetting happened... the café had put the price up from $4.50 to $5.
That’s where pricing research comes in.
PLAY’s preferred FMCG approach.
We like to do things a little differently around here (if you know us then you'll know that already!).
Here's how it works.
1. Show the concept to test unpriced purchase intent.
This will allow respondents to make a realistic assessment of the price at which they would expect to see it on the shelf.
3. Reshow the concept, but this time priced.
4. Ask value for money at the proposed price point.
5. In the analysis, top and tail the data to remove outliers.
6. Compare the priced purchase intent results with unpriced purchase intent and expected 'on shelf' price.
This will reveal whether the proposed price is within or outside consumer expectations.
1. Van Westendorp
2. Gabor Granger
- Good for getting unprompted/unbiased opinions on acceptable pricing, e.g. if the product is the first of its kind
- Simple for respondents to complete
- It doesn’t reflect how people think when buying FMCG products - there’s a strong argument that most people are perfectly capable of giving a ballpark price for common FMCG products
- Doesn’t generally have any context unless you take the approach we recommended above, and include a shelf with competitor products before the exercise
- Widely used in research but has no scientific basis and has not been validated (for example, no evidence that respondents don’t gives figures that are lower than what they’d actually pay)
- It assumes that price is a reflection of value or quality, so is not useful for a true luxury good
- It also assumes that there is a point at which a price can be so low for a product that people feel it will be poor quality, and won’t buy it
- Good for getting ‘realistic’ responses because you’ve provided the range of prices in which the product will be launched
- Simple for respondents to complete, and relatively quick
- Can produce demand and revenue curves
- Doesn’t generally have any context unless you take the approach above and include a shelf with competitor products before the exercise
- Responses are biased in the sense that you are providing the respondent with a range to respond to, though there is an element of randomisation to try to disguise the range
- Widely used in research but has no scientific basis and has not been validated.
Over to you.
PLAY specialises in FMCG and retail research, so if you want to look into pricing up your latest product innovation or you've made a change you want to test and optimise, get in touch on 02 8097 0200 or email firstname.lastname@example.org.
And as always, if you've got any research or consumer insight problems or questions you'd like to chat about - we're happy to share our veteran advice!
P.S. Talking of innovation, download our quick guide to find out how to harness the consumer perspective in the innovation process.