The initial spark
It is the year 2016. Stefan Heitmann and Markus Stadler are meeting in Wollerau for a Sunday brunch. And they have a plan: they want to develop a new business idea. Stefan Heitmann, a law and economics graduate, had already founded MoneyPark four years earlier, Switzerland’s leading independent mortgage advising service. Markus Stadler, a graduate of engineering mathematics, was working at a management consultancy in Switzerland during that time. Stefan, who already knows the real estate sector well from his experiences as the founder and CEO of MoneyPark, has a business idea in mind for the new start-up in the same industry.
A glance at the future
Stefan has noticed that the real estate sector is still relying on backward-looking methods and historical data. There is little transparency for buyers, owners and sellers. The entire world of real estate is relatively conservative as a whole. Of course, that is partly due to the product with which it deals: houses or flats are built from bricks; they are built to last. That feature inherently anchors them in the past. The sales process, in particular, uses comparisons with historical data: What has been built, what has been sold? What flat sizes have been in demand? Stefan and Markus set out to turn that approach upside down. They want to shift the industry’s focus to the present and future.
«I cannot accept that we are still navigating the real estate market in 2016 through the rear-view mirror and with the windscreen covered. I want to make the windscreen transparent.» With this statement, Stefan Heitmann presented the basis for the new business idea: improving transparency for all players in the real estate sector with digital, data-driven products that facilitate better decisions and boost sales.
Vision: anticipating market developments
During their discussion, Stefan and Markus arrive at the following questions: Could a sufficiently large database help us predict developments in the property market? Could comprehensible, user-friendly real estate software solutions help people access the relevant data?
Using machine learning and artificial intelligence, they aim to turn a deluge of data from the real estate industry and surrounding sectors into analyses and market forecasts. Stefan Heitmann, who is fascinated with machine learning and big-data models, explains: «Just a few years ago, it would have been impossible to process the vast data operations that a cloud can handle. Today, we can move more data than ever before.»
Their top priority is to address their business partners’ pain points. From the start, the two founders maintain close dialogues with partners from the finance and real estate industries in order to create an independent centre of competence for artificial intelligence and data analysis that is focused on customer needs.
Their common goal is clear. They recruit data scientists and software developers. Their task: to develop secure, well-maintained and cutting-edge digital solutions for the real estate market. Stefan and Markus know that they will not accept any compromise when it comes to quality. Of course, they also need data engineers who produce, monitor and test the backbone of PriceHubble: the data, gathered from hundreds of sources. Again, quality comes first when it comes to the quality of the data streams. Stefan and Markus start off with a small team: one astrophysicist, one machine-learning expert and one part-time data analyst. The small group builds the foundation for the self-learning system, which collects vast volumes of information, analyses it and processes it to generate a precise forecast.