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The newhome.ch AG is a Zurich-based, rapidly growing company owned by Swiss real estate companies as well as cantonal banks. On average, it hosts more than 150,000 listings and attracts around 1 Million visitors per month. Around 60% of its users are visiting the site via mobile phone. Its goal is to provide a comprehensive and customizable real estate ecosystem by using the latest technological solutions, innovative and intuitive “matchmaking” as well as functionalities that are consistently geared to the users.
In 2020, newhome wanted to relaunch its platform in order to become more user-friendly. Specifically, the company wanted to update their interactive maps, as map-based real estate search is becoming increasingly important to home seekers. Its main challenges were:
The newhome team was keen on keeping the amount of external services to a minimum and looked for a flexible partner that matched their agile working culture. That is why newhome decided to work with TargomoAPI.
One of the key solutions was the integration of travel time as a search option. As a result, newhome now allows users to start their real estate search from personal addresses such as their workplace, their partner’s workplace, and the kid’s school and select transport mode as well as maximum travel time. Consequently, these parameters would be used as filters for the search results.
In addition, newhome users now can display relevant Points of Interest (POIs) as well as routes to personal locations when selecting a real estate offer. In order to get the new platform up and running in the shortest possible time, Targomo and newhome started their project with a hands-on workshop.
After first implementing the travel time search feature, newhome’s customers immediately loved the new option. At the request of some customers, the platform even refined the feature so that users could choose a separate transport mode and maximum travel time for every single personal address. Within the first few months after relaunching the platform, newhome was able to lower both their exit rate as well as their bounce rate by 15%, and the finetuning has only just begun.