The Marketer Effect
Documenting superior return on investment for clients.
Imagine that you are selling your home at the same time as your neighbour. They are the same property type with identical standards, in the same area, at the same asking price. However, one property is ultimately sold at a higher price than the other. Why is that?
Historically, the sales success of a specific property has relied on the network of the real estate agent, word of mouth, print media and classified ads. The active use of digital marketing has increased significantly in recent years, and gradually moved from being relatively broad and generic to becoming more and more targeted and personalized. The latter is only possible at scale with the use of sophisticated technology.
Today, the demand for personalization is continuously increasing. Potential buyers want specific property ads that match their particular needs, interests and general life situation. For real estate agencies there is no alternative to investing in technology to ensure the best possible results for their clients. This is crucial for attracting more relevant leads and ultimately achieving the best market price for each individual object.
Marketer has for several years delivered results far above market average within digital marketing for the real estate industry, providing customized solutions for both agencies and developers. Being fact-driven in our approach to all client solutions and product development efforts, we strive to be equally fact-driven and honest about the results of our services.
In early 2021, Marketer acquired the data tech company Homefair that had a strong focus on data science and data driven solutions for the real estate industry. One of their founders, Walid Mustapha, with a PhD in data science, soon discovered that with accumulated data from the two companies, combined with AI, it would be possible to estimate the positive effect associated with marketing a property using Marketer’s platform.
“We are proud to be the first proptech company in the world to document the effect of our services in such a scientific manner. We call it ´The Marketer Effect´”, Mustapha announces.
The findings are calculated using data from more than 53,000 second-hand home transactions over three years, with Marketer’s solution utilized for about half of these properties evenly throughout the period. The effect is quantifiable as a consequence of the unique connection between a large pool of relevant data and AI.
The overall Marketer Effect
Translated into monetary measures, the overall positive Marketer Effect equals NOK 600 (Approximately EUR 58) per square meter. The figure below shows the mean difference between estimated property price using an objective AI property value system and actual selling price for properties that were sold using Marketer’s platform versus those that were not. So, for example, scaling this to a 100 sqm property results in an average increase in achieved selling price of a considerable NOK 60,000 (Approximately EUR 5758).
Results by Property Type
Mustapha describes the results of the findings with growing enthusiasm. “We found that there are differences in the effect related to property types, geographic regions, population density and other features relevant to the properties, which you can see in the figures further down. However, the mean of the results show that all property types are associated with a net positive effect of using Marketer’s platform". The results are as follows:
- Townhouses: ~NOK 31 000 (Approximately EUR 2982) in average increased selling price.
- Apartments: ~NOK 33 000 (Approximately EUR 3174) in average increased selling price.
- Semi-detached houses: ~NOK 77 000 (Approximately EUR 7407) in average increased selling price.
- Detached houses: ~NOK 135 000 (Approximately EUR 12 986) in average increased selling price.
"We expect that the effect will be even stronger in other countries that may have less open, transparent and concentrated markets than Norway. Further to this, a higher supply of second-hand homes relative to demand is expected to generate an increased Marketer Effect”, he continues.
“I remember reading a Slack message written by one of Marketer’s founders about how two similar houses in the same neighbourhood were put on the market with the same asking price, and that the one advertised through Marketer was sold at a much higher price. I then started to think about ways in which we could document this effect, and the potential return on investment and absolute value that was created for home sellers in general”, Walid says with great enthusiasm.
“To actually document the positive implications of using Marketer’s platform makes a huge difference to everyone, not just to our clients or the home sellers, but also to us internally at Marketer. As a data scientist, you have to be curious about data and finding value in data. Being a very curious person myself I find cases like this an absolute goldmine”, Walid concludes.