We had an idea for an app that matched people moving house with neighborhoods that matched their lifestyle.
Most of us have had bad experiences with renting apartments or homes. Finding the right place is difficult, listings can be misleading, and information about the surrounding neighborhood usually requires a local’s knowledge – placing new arrivals at a significant disadvantage.
To begin with, we set out to validate that this was truly a problem via survey and group interviews. We found that:
Therefore, our initial personas became:
This led to two basic user stories:
Our initial thinking was that users would simply answer 4 qualitative preference questions (ranked on a scale of 1 to 10) from which our algorithm would recommend a short list of suitable neighborhoods. From there, users would begin their search, relatively confident they were looking in the right places.
We went through many iterations to arrive at a user flow that made sense. We started with why, moved through the what, before presenting the results.
Our first iteration drew heavily on dating apps for inspiration. We began with a list of questions to gauge what the user was looking for. First we asked why in order to ensure a quantitative match, say near a university or work if the reasons for moving were listed as school or work respectively. We then asked users what they were looking for in a neighborhood. This was centered around qualitative lifestyle factors such as restaurants and nightlife, parks and cafes and so on.
After testing this with users, it became clear that users wanted to see rental listings immediately, and beginning with a wall of questions – even in the context of returning more highly personalized results – was a significant obstacle to that.