How to do pricing research
Tl;dr: When asked point-blank, people can’t easily translate the value of their experiences and outcomes into pricing. Therefore, pricing research must first correctly identify a buyer’s reference set and calculate the economic value of the differentiated attributes of your offering in relation to the reference set.
People do irrational things – especially when it comes to making purchase decisions. Customers will pay thousands of dollars on luxury items that they know nothing about, while they refuse to pay a dollar for a trial membership on a useful platform. This type of human behavior is often overlooked by the product teams when they are researching or validating an opportunity.
In such an environment, you simply can’t rely on what customers say they’ll do to understand their motivations and the triggers for adoption. While you can’t rely on what people say they’ll do, you can rely on what they have done, in the past.
While you can’t rely on what people say they’ll do, you can rely on what they have done, in the past.
How do people measure value?
As buyers, we are acutely sensitive to differences and not so sensitive to absolute values. In a 2003 research study, Dan Ariely and his team called this phenomenon “coherent arbitrariness.” To understand this better, consider the two drivers of our value judgment: perception of fair value and willingness to pay.
Imagine you’re traveling and that you don’t own a scale to weigh your luggage. In that case, you would assess the weight of your suitcase by relying on your muscle memory. You might recall from memory what it had felt like to lift 50 lbs or you might weigh some other item with known weight to compare. Perception of fair value works in a similar way. We rely on our memory for assessing what things “ought to cost” but usually don’t have a clue about their worth. We say: “If I am paying X for that, this ought to cost Y.”
We say: “If I am paying X for that, this ought to cost Y.”
Consider another example from your morning beverage. When your coffee or tea is too hot to hold, does is it matter if it’s 190 degrees or 195 degrees? So long as it’s above your tolerance for heat, you simply can’t hold it in your hand. Willingness to pay works in a similar way. If the benefits of an offering don’t surpass our tolerance for a problem, we are simply not willing to pay for it.
Behavioral economists who have researched buyer behavior in-depth report that our perception of fair value is relative and formed in relation to what we already know about other products and experiences that we are familiar with. This relativity might cause several problems for product owners and researchers. For example, the anchors your prospective buyers use to make fair value judgments may or may not be the right reference set for comparing your solution. In some other cases, there might not even be a reference set. While in yet other cases, you might not calculate the economic impact of your offering in relation to an existing outcome, correctly. Your pricing research design must mitigate each of these research errors.
Identifying the right reference set
Identifying the right reference set is especially problematic for new products or new-to-the-world technologies because people simply don’t have sufficiently reliable experiences from which to draw their value judgments. Therefore, the pricing researcher must guide the respondent to identify the right reference outcomes but do so in an objective manner and without biases - confirmation bias, projection bias, recency bias are three of many that might come into play. Here are some example frames:
Can you walk me through the last time you accomplished [the desired outcome]?
How do you achieve [the same desirable outcome] today?
What [process/tools/skills/knowledge/assets] do you use to achieve [the outcome]?
Keep in mind that the reference set might be a combination of processes, tools, skills, systems, and solutions that buyers acquire separately and utilize individually. Make sure to also uncover the hacks, workarounds, and hand-offs in your respondents’ workstreams. Most innovations live in the gaps between processes, hand-offs, systems, tools, and solutions. Here are some example frames:
How does a peer of yours use the [process/tools/skills/knowledge/assets] differently?
Where does the process you just described break most often?
What did you do when [an example of a process breakage] happened last?
Quantifying the qualitative responses
Another goal of pricing research is to calculate the economic value of your offering to the customer – EVC. EVC depends heavily on the economic value of the reference set as it aims to measure the differentiated benefits of your solution over the next best competitive alternative - NBCA. Therefore, it’s critical that you not only identify the correct NBCA but also do some math with your research respondents.
Different from the psychological value, the economic value must be directly attributable to the financial results of a buyers’ activities or performance. In B2C the typical quantifiable outcomes are efficiency, social/emotional gains, new utility, or experiential advancements. In B2B, some common value drivers are net new revenue, cost reduction, productivity, risk mitigation, and social, emotional, and experiential value drivers.
Contrary to common belief, qualitative, in-depth interviews can be credible resources to run and validate the economic impact of a solution with your respondents. Sometimes, these interviews might be the only source of information when it comes to economic value. Here are some example frames:
• For drivers of net new revenue, validate the scale factors and the units of scale with the respondent. Net new revenue might come from new customers, markets, channels, or partners or from existing customers.
• For cost reductions, calculate the cost savings as a percent of a budget or revenues and repeat this for each of the desired outcomes.
• For efficiency and productivity benefits, arrive at the total average cost of a resource on an annual basis, and have your respondent confirm those numbers.
• For risks mitigated, articulate the risk factors by estimating their impact on business continuity, market share, reputation, customer lifetime value, costs of non-compliance, etc..
• For social, emotional, and experiential value drivers, measure respondents’ propensity for each of the value drivers.
Knowing your non-customers as well as your customers
Product owners and marketers alike are keen on translating the needs pains, and gains of their market into value propositions. They conduct a lot of customer and prospect interviews and focus groups with people who would indeed buy and use their products. In our experience, it’s equally important to understand who the non-customers and lost customers are. In some cases, knowing who would not need your product or for what reasons they would stop choosing to use it are even more valuable. Consider the case for the subscription business model: a monthly churn of 2% means losing a quarter of your annual revenues. Wouldn’t you want to know your non-customers and lost customers as intimately as you know your loyal ones, if you were losing 25% of your business annually?
To sum up, if you’re undertaking qualitative pricing research, design your process so as to:
Identify the correct reference set,
Relate the economic impact of your differentiated offering to the reference set,
Get to know your non-customers' value drivers as well as your prospective customers’ drivers.
Fortunately for visionaries and product owners alike, we have developed quite a few tried and true methods for doing pricing research, successfully. We’ll cover the quant methods for market validation and setting prices in another post. Feel free to reach out to learn more.
