COVID-safe customer testing: part 1
99% of companies today have lost their way to validate that customers want what they’re currently building. This series will put your process through its paces as well as teaching new tricks along the way.
Part 1 is dedicated to making sure what you want to learn isn’t going to burn up with a false positive
Our aim over this series is to use Marty Cagen’s model of validation to understand the three deal-breakers for anything we think can create value:
- Can we build it
- Can they use it
- Do they want it
If you have a direct question on any of these just email me your question: james@leancup.com.
Our goal with understanding each of these three areas assumes that we want to build something that either resolves pain or generates value for your customers. To do this we need to define goals that these new projects will have and then test if they are meeting them. This is also known as Build-Measure-Learn from the Lean Startup movement. We start this process by defining a series of assumptions about the pain/gain our customers have and then framing them as a set of questions, or hypotheses.
Focusing on customer-first requires a rock-solid set of hypotheses before testing begins
In most cases, the point of failure for customer-focus normally lies before any questions are asked with team-driven confirmation bias. Solving this isn’t just for COVID; it’s a life-skill around creating questions we ourselves cannot break.
Let’s say you wanted to test a new COVID safe way to make returns for your e-commerce store, you might create the hypothesis:
We believe that customers will want to return their unsatisfactory products safely
But what have we assumed? We believe that people have the same definition of unsatisfactory. Or, more specifically, we believe something is either good or bad because we want to build a returns model around things that have the definition of ‘bad’. We’ve decided the definitions without ever involving a customer in our process which causes the potential for a false-positive. Another way this is sometimes phrased is as lacking the ‘customer language’ of a problem, as a business we have our own language and so we can’t trust any potentially shared terms.
We believe that some customers do not want to keep their products
We believe that customers who do not want to keep their products do not know the next steps to take
We believe that customers who do not want to keep their products do not complete the next steps in a way that they want
Nesting your assumptions and hypotheses is the easiest way to stop your biases coming into play because the most basic of ideas is going to best tested. This doesn’t require any more customer time and is one of the easiest ways to make your customer interactions more valuable.
We’ve written hypothesis and now we need to test things with our customers
Armed with your new list of assumptions to test and a series of problems or solutions to share it’s now about conducting fair and open exchanges with your customers to learn what ideas are false (never say we’re seeing what ideas are true, that’s pesky confirmation bias coming in again)
