Customers don't have to buy our products, and users don't have to choose to use a feature. They will only do so if they perceive real value. Another way to think about this is that just because someone can use our product doesn't mean they will choose to use our product. This is especially true when you are trying to get your customers or users to switch from whatever product or system they were using before to your new product. And, most of the time, our users and customers are switching from something—even if that something is a homegrown solution.
So many companies and product teams think all they need to do is match the features (referred to as feature parity), and then they don't understand why their product doesn't sell, even at a lower price.
The customer must perceive your product to be substantially better to motivate them to buy your product and then wade through the pain and obstacles of migrating from their old solution.
All of this is a long way of saying that good product teams spend most of their time on creating value. If the value is there, we can fix everything else. If it's not, how good our usability, reliability, or performance is doesn't matter.
Just because someone can use our product doesn't mean they will choose to use our product.
There are several elements of value, and there are techniques for testing all of them.
Sometimes it's unclear if there's demand for what we want to build. In other words, if we could come up with an amazing solution to this problem, do customers even care about this problem? Enough to buy a new product and switch to it? This concept of demand testing applies to entire products, down to a specific feature on an existing product.
We can't just assume there's demand, although often the demand is well established because most of the time our products are entering an existing market with demonstrated and measurable demand. The real challenge in that situation is whether we can come up with a demonstrably better solution in terms of value than the alternatives.
The most common type of qualitative value testing is focused on the response, or reaction. Do customers love this? Will they pay for it? Will users choose to use this? And most important, if not, why not?
For many products, we need to test efficacy, which refers to how well this solution solves the underlying problem. In some types of products, this is very objective and quantitative. For example, in advertising technology, we can measure the revenue generated and easily compare that to other advertising technology alternatives. In other types of products, such as games, it's much less objective.