Kitt is an end-to-end office company that helps brands find, design, build and manage their office. The most important part of this revenue chain begins with Find. Kitt did this with their Search Platform, much like Rightmove or Zoopla, only for commercial brokers looking for office spaces for their clients. Kitt’s internal Business Development Representatives (BDRs) used the Search platform daily, albeit with tedious and laborious routines, but external broker usage had never really picked up and was massively limiting company growth. For this project with Kitt, I was brought on as their first and only product designer to achieve two goals:
In collaboration with my product manager, the sales team including the BDRs, and a team of developers, I redesigned Kitts Locations and Search platforms, resulting in a 400% increase in location updates and a 50% increase in external broker enquiries. So, how did we get there?
I carried out user research interviews internally with BDRs and externally with several brokers. Noticeably, the most pressing issue was not to do with the Search platform itself, but its trustworthiness as a result of the poorly designed Locations platform, the database on which all live offices are managed. Some key quotes included:
“Not all locations are up to date so I’m hesitant about using Search and call up agents myself instead.”
“I don’t trust the platform filters.”
With this level of mistrust in the platform’s database, BDRs ended up spending hours manually checking location details themselves and used other platforms. For brokers, trust was never gained in the platform in the first place, and such was never visited again by 92% of brokers that had opened an account.
As a result, I designed a Priority Ranking Exercise. This exercise involved research participants ranking the importance of various information elements when evaluating potential office spaces. The participants were presented with a selection of information tiles, representing key factors such as building name and address, map of building location, photos of the building, public transport links, unit floor number, unit square footage, unit price per calendar month (pcm), and unit minimum term length. They were tasked with arranging these tiles along a scale ranging from low importance to high importance.
The results from this exercise revealed a consistent pattern in the participants' prioritisation. Notably, unit price pcm, unit square footage, and the map of the building location consistently emerged as the top-ranking factors. Subsequently, unit minimum term length, photos of the unit, unit fit (blank, partial, full), and building name and address followed in importance. This data played a pivotal role in establishing a baseline: locations must meet the minimum information requirements in order to go live on Search. Additionally, the Priority Ranking Exercise results informed the information hierarchy of the Search platform redesign.
