Market researchers have several different techniques for helping manufacturers set prices. Some lead to valuable insights, while others provide only confusion.
Carefully designed and professionally implemented quantitative research and data analysis together provide details that have a significant impact on outcomes.
Pricing is one of the most critical elements of a product in the marketing mix. Companies have to pay money to design a product, to develop/build a product, and to promote a product. However, a product’s price is the only element in the marketing mix which generates an income for an organization. Pricing strategies based on sound pricing research provide companies with a price that reflects the supply and the demand integrated into the relationship.
The Role of Quantitative Research and Data Analysis in Price
There are many types of research tools that help companies identify and discover various pricing models. A few key techniques, presented below, have their advantages and disadvantages.
For the sake of discussion, let’s consider several pricing strategies and then revisit our example question posed in the sidebar: “How does Apple price their phones so successfully?”
- Gabor Granger Price Laddering: If a market researcher comes offering price laddering, politely show him or her the door. This technique asks respondents whether they would buy a product at price x, then whether they’d buy at price y, then at price z and so on. Research shows that once respondents have accepted a given price, they’ll feel cheated by any higher price, while lower prices won’t increase their intent to buy. So after that first price is shown, laddering doesn’t yield any useful information.
- Van Westendorp Analysis: This is a more sophisticated analysis, but it is built atop a shaky foundation. Respondents are asked four questions about price:
- At what price does the product become too expensive to consider?
- At what price is it getting expensive but still within consideration?
- At what price is it a good value?
- At what price is it so inexpensive that doubts arise about its quality?
The responses are combined into a pricing curve that provides a range of customer-acceptable values. Two problems become apparent: 1) respondents quickly figure out the approach and give lowball prices, and 2) the range is often so wide as to be useless. For example, a manager might be considering a range of $15-$20/unit. Van Westendorp will often tell them to price it between $5 and $25.
- Monadic Testing: This is the primary technique used by big volume forecasters like Nielsen, and if the normative database is robust enough it can be useful. Respondents are shown a description of the product at a set price and then asked their likelihood to purchase the product. By testing other prices with other respondents, managers can get a sense of the pricing that will be the most profitable. The trouble with monadic testing is its lack of granularity. It can tell only about the prices actually tested. Sure, managers can test a range of several price points, but each additional price can require hundreds more respondents, which gets really expensive really quickly.
- Discrete Choice: This is the best approach to survey-based pricing research. It simulates customers’ real-life purchase decisions by giving them a series of choices between sets of competitive products, each with price, brand, volume, level of service and other important product characteristics. The design can test several individual price points and the analysis can extrapolate the customer appeal for prices between them. Beyond that, though, it can then show the relative importance of each product characteristic and identify the optimal level within each – helping product managers optimize product development and focus resources. Its inclusion of competitive products also makes it a tool many manufacturers and marketers rely on for scenario planning. But discrete choice can be more expensive than other options, and without careful design it can lead respondents to be more rational than they would be in real life. When done well it provides clear insight on a range of issues, pricing included.
So which pricing approach does Apple use? None of the above – not even discrete choice. Apple doesn’t ask consumers for direction; if it did, it would probably hear that prices need to be lower…and yet people still line up to buy the latest iPhone. Apple designs products and systems, calculates the value that they will hold to the customers who will get the most out of them and prices them accordingly. Pricing lower would certainly increase share, but Apple’s focus is on a more important measure: profits.
Context sees the value of quantitative customer research as an input that, when combined with deep industry understanding, can inform value-based pricing. This approach empowers clients to price strategically for their specific objectives.
Contact us to discuss your market research needs. Context provides a wealth of expertise in quantitative and qualitative market research design and data analysis, R&D, volume forecast modeling, insight generation and deployment, new product development and business plan creation, and competitive intelligence and market intelligence.