Following testing and learning together as a blended team, we set out with a clear focus: if we don’t provide a way for business owners to meaningfully understand and engage with insurance recommendations, they remain unable to make decisions and access the right cover for their business.
For this to occur, we learned we must facilitate meaningful engagement with insurance recommendations using two ingredients - carefully balanced explanations of how each product worked, as well as examples of it in use across different business sectors. This allows small business owners to use expertise in their own business to access how applicable each product would be for their situation, and understand their own risk exposure.
I designed prototypes to test the riskiest assumptions - how accurately could we recommend insurance cover for each business, and what was necessary for users to feel confident enough to purchase online? Surprisingly, our early prototypes that focused on super accurate recommendations fell flat. Business owners didn't care that the calculation was accurate - they needed to know the 'why'.
We pivoted away from 'black box' recommendations, to providing a clear and relevant starting point recommendation that empowers users to cautiously make changes where appropriate. While this approach was certainly more difficult to navigate with legal teams and roboadvice regulation, everyone perservered as we could see the outsized impact it had on small business owners.