Are your customers cheap? Are they like Scrooge McDuck, squeezing every penny until it screams for mercy? Or are they brand loyalists or status seekers, and therefore less concerned with price? Gauging price sensitivity is a very common goal in market research, and naturally online survey projects have an important role here.
How do you actually gauge price sensitivity in an online survey? You will want to identify a set of statements to use in your design. Along with these statements you will need a scale. Either an “agreement scale” (a 5 or 7-point scale from “Strongly agree” to “Strongly disagree”) or a fit scale (a 5 or 7-point scale from “Describes me very well” to “Does not describe me at all”). Keep in mind that the goal here is to understand both what the respondent agrees with and what they disagree with. Both aspects are crucial.
Possible Statements That Reflect Pricing Attitudes
1. I like to be aware of all possible options before buying an expensive item.
2. I keep up with sales being offered by (department) stores in my area.
3. I feel that I can save a lot of money by using coupons.
4. I feel that coupons just aren’t worth the time.
5. I always want low prices but I’m equally concerned about product quality.
6. When I buy (insert product category here) products, I always want to make sure that I am getting my money’s worth.
7. When (grocery) shopping, I always look at the price per ounce or price per unit information.
8. I often shop at more than one store in order to find the best price for (kitchen appliances).
9. The money saved from shopping around is usually not worth the extra time it takes.
10. When I buy something that’s on sale, I feel like a winner.
11. I have favorite brands, but I typically buy whatever is on sale.
12. Buying expensive products makes me feel stylish.
13. I enjoy the prestige of owning products from high-end (fashion) brands.
(Items in parentheses indicate words you would most likely change to cater to your specific product category).
What can we learn?
In real life, you will likely use 5 to 7 such statements as one section of your online survey, and you will tweak the wording form these examples to be specific to your context (type of product, type of store, type of discount program, etc.).
After you collect your data, look for patterns. We’re offering our respondents the chance to either agree or disagree with opposing statements, which allows us to confirm their tendencies. An individual who doesn’t care to clip coupons for the grocery store will also likely agree that it’s not worth the time it takes to shop around for the best deal—they would rather go in, grab what they need and get out. Some people will have strongly consistent answers, others may have mixed opinions—both are fine. But you will want to seek out patterns.
Are Some Ducks Duckier?
One suggestion here; be sure to see if there are differences by subgroup. Do men respond differently than women? Does price sensitivity in your target market vary by geography? If you’re doing business-to-business research, does the price sensitivity you’ve discovered vary by company size or vertical industry? You want to know if there are particular subgroups that have notably higher or lower price sensitivity. Maybe your overall finding is that price sensitivity in your target market is very low; but are some sub-groups even lower? It’s useful to know.
Pricing & Promotional Decisions Are Easier With Data
Naturally you don’t have to use all these example statements, but I prefer to use at least five different statements before I draw any conclusions. As you can even see from this small set of examples, price sensitivity can be captured in different ways. Identifying where your target market falls on the “McDuck” scale of penny-pinching will allow your organization to make informed decisions on pricing and promotion.
(Note: Many of the statements mentioned in this article were inspired by work I have previously done using scales modified from the Handbook of Marketing Scales: Multi Item Measures for Marketing and Consumer Behavior Research, which was edited by William O. Bearden and published by Sage Publishing.)