Imagine being the boss of the internet only car dealer Carzoo.
Your entire business model relies upon people being happy to buy what is typically their second most expensive purchase, without seeing it or test driving it first.
It’s really interesting to consider some of the assumptions that need to be true in order for this business to succeed ;
- People will happily buy a car without seeing it ‘for real’ and test driving it
- A money back guarantee will be enough to make people feel comfortable to spend thousands online
- People will prefer shopping for cars in this way because car salespeople have such a bad reputation
- People will be happy to buy cars online despite there being no physical dealership to go to if things go wrong
I wonder what research Carzoo did to explore these assumptions in order to get to the point that they were happy to launch the service?
As with every product and service, there are always a bunch of assumptions that need to be true in order to succeed.
On a recent project, we ran a really useful exercise designed to flush out our riskiest assumptions.
Critically, it also helped to identify how much confidence the team had in each of them being true.
It worked like this.
- Ask everyone to list all of the assumptions that they feel underpin the success of your product or service (If people are struggling ask them to pretend they are funding it with their own money and watch the assumptions flow!)
- Take each assumptions in turn and plot it on the following matrix by asking yourselves two simple questions:
- How important is it that this assumption is true for us to succeed?
- How much confidence do we have that this assumption is true?
The more assumptions that you have in the top left of the matrix, the more might be feeling that your business model might be build upon a house of cards!!
We used our top left ‘most important / low confidence’ assumptions as the key areas of focus for our user research in order to learn more about them.
We also chose other assumptions to explore from the top right of the matrix to check whether our confidence in them remained.
After the research we reflected on all of the assumptions and re-plotted some of them based on our new knowledge.
It’s important to note that it’s hard to validate assumptions completely as being ‘true’ or ‘false’, in reality you use research to look for signals that will give you more or less confidence in them.
A useful way of thinking about them is as ‘rolling assumptions’ in that you continually explore the most critical ones until others become more important.
The ‘assumptions board’ that this exercise gives you is a useful tool to update throughout the product lifecycle as it gives you a useful reminder of your riskiest assumptions and helps you with where to focus your future research.