One of the most difficult decisions to make when launching a new product is determining a price. You don’t want to leave money on the table by undercharging, but you also don’t want adversely impact demand by overcharging. Finding the balance between too low and too high can be tricky, and doing the survey research for these decisions can be even harder. After all, we can’t just ask, “Would you rather pay $2.50 or $2.80 for this tube of toothpaste?” That is why a comprehensive pricing strategy is so important. So how do you get that sort of information? There are several possibilities.
Designing a survey?
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Simple Pricing Research
In the first question of a series, we can ask how likely they are to purchase a described tube of toothpaste at $2.80. Then in the next screen we ask them their likelihood to purchase at $2.50. Next, at $2.30. You get the idea. With that reverse ratchet effect, we would review the results to find the biggest increase in interest. However, some researchers advise against this approach because after the second screen your respondents will anticipate another drop, and vote artificially low in the current screen expecting you’ll go even lower in the next. So the results become skewed, and no longer capture actual likelihood. It’s a valid concern.
Elaborate Pricing Strategy
In reality, large companies that sell consumer packaged goods exhaustively analyze the demand elasticity curve for specific products. In our toothpaste example, for a particular tube and brand, they would model how demand varies by price. The CPG companies and other large businesses do exhaustive quantitative research, sometimes using a technique called conjoint analysis. It’s a technique that requires working with a statistician or market research firm to do the analysis for you.
Other Pricing Options
If the simple approach concerns you due to likely skew, and hiring a statistician isn’t an option, there are ways to do your own pricing research. These options will give you some great information to work with as you decide how to price your product, without spending hundreds of thousands of dollars.
Monadic design is a common approach in market research surveys for pricing strategies. It’s where we ask people to indicate their interest in a particular product at a particular price point. With these restrictions (one product at one price) we can get an unbiased response. In a monadic test we typically split a population into, for example, three different groups; A, B and C. In Group A’s survey, they are exposed to the product at one price level, Group B sees a totally different price, and Group C sees yet a third. We can do this easily in AYTM by cloning one survey design and modifying that single question to include a different price point.
Another advantage of the monadic approach, aside from avoiding anticipatory responses, is that it saves space so that you can ask other questions. Maybe you’re also trying to understand which features (flavor, for instance) are the most important in considering toothpaste, or you might be testing messages or gauging competitive brand perceptions. We don’t want an overly long survey, but often when you have the opportunity to talk to people to test price, you have other things you’d like to ask them too. But if you have several questions just abut price, then you won’t have a whole lot of time to ask other burning questions.
An alternate approach is to do a variation of conjoint analysis. While true conjoint analysis requires working with a qualified statistician, a technique called “paired comparison” lets you ask people to make tradeoffs, and you can do that simply in a survey. Asking “Which of the following are you most likely to purchase?” followed by two options:
• A tube of toothpaste with features A, B and C at $2.79 a tube
• A tube of toothpaste with features A, Y and Z at $2.99 a tube
This allows you to understand whether there are certain feature combinations that will command a price premium. By asking for a choice between two products, it more closely simulates the choice your respondents would be making when looking at a store shelf.
Naturally we have to be very careful to avoid large numbers of unique combinations — you need to keep it simple. In reality, you probably already have plans to develop your product with either Feature Set A or Feature Set B, so you’re not looking at infinite feature combinations. Be realistic and use only likely combinations to gauge possible purchase interest.
Price Sensitivity Meter / Van Westendorp
The Price Sensitivity Meter Experiment (PSM or van Westendorp) is a very efficient method to predict a price range/optimal price perception for a new product or service. It reports what the customers’ expectations of the price will be. Our platform makes this option as simple as drag-and-drop without any messy programming, yet it still provides compelling results. We recommend using PSM as a directional tool, or as a first step of price research, followed by a more precise methodology such as a monadic price test.
PSM presents each respondent with the question “For [product/service], at which point would you consider the price to be…”, along with the following 4 prewritten subquestions. The respondent is prompted to type a price answer for each:
• So cheap that you would think it couldn’t be a quality product/service.
• A real bargain worth consideration.
• Starting to get expensive but you would still consider purchasing it.
• So expensive that you wouldn’t consider purchasing it.
When your survey is fulfilled, you will have a clear visual representation of the acceptable price range and optimal price point according to the cumulative prediction of respondents’ price sensitivities.
This test is based on graph theory, and features more accurate intersection calculation formulas than are commonly used in the industry.
The last word
Devising a pricing strategy should never be done in a vacuum. If you have competitors or substitutes, research their pricing. You absolutely need to understand what expectations your customers may already have about pricing in your product category. Knowledge, as they say, is power!
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