How can a firm figure out where its demand curve is? The short answer is you never know for certain.
The longer answer is that the best way to gather information about demand is to charge a price and see what happens. When you set a price and observe a quantity, you have just seen one point on the demand curve for that time and location.
And this means that one of your best sources for information about demand is your past data. Now, in analyzing this data, you need to keep in mind that demand curves move over time; as willingness to pay for our product (or rival products) changes, or as prices of rival products change, demand curves can shift either left or right. As a result, today’s demand curve is not likely to be exactly the same as yesterday’s.
What about for new products, where you don’t have any past history to examine?
With new products, it is harder to determine demand, but one important factor to keep in mind is that demand comes from willingness to pay. If you can somehow estimate consumers’ willingness to pay, then you can construct demand in much the same way we have done.
This is easiest in the b-to-b (business to business) context, where your customers are for-profit firms. A customer’s willingness to pay for your product will be closely linked to the amount of additional profit you generate for your customer.
In the b-to-c (business to consumer) context, it can be difficult to get a handle on willingness-to-pay. There are no rules about what willingness to pay should be, and it’s easy to get tricked.
There’s no formula that would describe a customer’s desire to reduce their environmental impact. And this makes it difficult to sort out what the willingness to pay for a new product like Orbital’s shower system.
In this case, the best option may be small-sample market research. One low-cost approach would be to survey potential customers about their willingness-to-pay for an energy-and-water saving shower system.
Small sample sizes might mean your data will not be representative of the entire mass of consumers. In addition, survey respondents really have little incentive to tell you what they really think. If a customer says “Sure, I’d buy an Orbital shower if the price were $5000,” that’s less reliable information than actually observing a customer parting with the cash. A survey respondent might be telling you what s/he thinks you want to hear, but an actual customer is putting his/her money where his/her mouth is.
A medium-cost approach would be a small-scale product launch. Imagine opening a showroom an arid, well-to-do area where many residents are concerned about their environmental impact. (Palo Alto, California seems perfect for this!) Such a rollout would allow the firm to set prices and then assess demand using actual data. Here, the concern would be finding a test-market that’s truly representative of broader market conditions.
In general, you have accept the fact that you never know demand with certainty. We think it’s better to analyze the information you have rather than proceeding with guesswork, hunches, or unchecked intuition.
Although Orbital cannot accurately predict the demand, it tries to educate customers in a way that will increase their willingness to pay. On their website, they have an interactive section called
Measure Your Savings. Click on either “Commercial” or “Residential” and you will have the opportunity to tailor information such as location, watercost, shower length, and daily showers to your personal experience. The website dynamically displays water savings, energy savings, and estimated cost savings per year as you adjust various factors. Emphasizing the environmental and monetary savings highlights the benefits of the product to the customer.