Finding your dream place to live? Easy if you’re in Norway
A case study of finn.no’s location insights product out of a Product Manager’s perspective
Building an innovative product is tough. Even if it consists of nothing but bits and bytes, developers’ time is expensive and Product-Market fit hard to reach. A business case becomes much easier when your product provides value for more than one party and market dynamics work in your favor. This improves margins as well as your competitive position.
The case study – Finn in Norway
To illustrate this, I will be looking at finn.no, a Norwegian classifieds (think marketplace) platform which is, among other products, connecting buyers and sellers in real estate.They have, I find, an outstanding location insights product which is creating value for all parties in the market (Side note: I have no affiliation with finn.no).
I had the chance to speak with Jørgen Hellestveit, a product leader and future CPO. With a long history in real estate, he intimately understands the market and its participants. Jørgen was kind enough to explain the dynamics behind Finn’s location insights value proposition, why it is working so well and their plans for its future.
Finn’s location information product
Now, before an overview of the Norwegian real estate market, let’s have a look at Finn’s location insights product and how it works.
For most property listings on finn.no, a significant part of the ad is centered around the property’s location: users see cards with facts relevant for most home seekers such as public transport, demographics or shopping (Side note: this is originally Norwegian content and translated automatically so the exact wordings may be wrong).
In addition, users see a component with personal reviews regarding a neighborhood like illustrated below.
Finally, viewers can open an interactive map with freely configurable points of interest, much beloved by Finn’s users, according to Jørgen.
Location insights are an add-on product which can be bought by homeowners or agents when listing a property. It is available, however, even beyond the core platform: The underlying data comes from a set of APIs which can be accessed externally, for instance, by agents to showcase neighborhoods within their own apps.
With this content, home seekers get a detailed overview of a property’s neighborhood to make better decisions. Indeed, this has become so popular that, for listings which have not bought this add-on, home seekers call Finn’s support hotline complaining about the missing insights.
Home seekers in Norway
Now, why did this come to be such a successful product? To understand, let’s take a step back and look at Norway, a land of homeowners. More than 80% of households own their home, a status advanced by government policies and central for peoples’ identities.
This leads to a high interest in home listings. As Jørgen pointed out, Norwegians love browsing homes on finn.no. Out of 6 million Norwegians, 3.1M are visitors on finn.no in any one year. A third of these are hunting for a new home, the rest are looking for inspiration or exploring neighborhoods and offers. Per adult Norwegian that’s 7.5 hours per year, an entire workday, spent “window shopping”. Actual transactions are less: around 100k homes change owners per year via the platform.
Market structure and incentives
In terms of the market structure, Norway is a sellers’ market with intense demand per property, leading to high and rising prices (until the recent market correction). Still, real estate agents have a material interest in maximizing bidders for any one property since they represent it exclusively. As they get a share of the sales price, they have the incentive to create a great ad to maximize their potential revenues : For this, they invest in 360° viewings, high quality pictures but also neighborhood information. Location information also works in the rental segment: by helping tenants make better choices, the company’s reputation improves and users return.
Product dynamics and in a favorable market
Now, as we better understand the market, let’s explore how Finn’s location product benefits from self-reinforcing dynamics as it serves multiple parties. To understand this, we take a brief look at the product’s roots:
It was originally brought to life by an innovative entrepreneur from Bergen. He created pdf location maps (“neighborhood profiles”) and sold them to real estate agents who thus made their brochures more attractive. This turned into a value proposition loved by both agents and buyers, as they both benefited. Strong growth resulted: agents showcasing the feature reached new users and home seekers familiar with the component asked agents to provide good location information.
The product’s success eventually motivated Finn to buy the company, boosting the product’s reach and adding a new party to the product system: finn.no’s classifieds platform itself. The platform benefited by attracting more users via interesting neighborhood profiles and aiding their high-intent users in making better choices (now the most important value driver, according to Jørgen). As a result, user experience improved as well as traffic and conversions. This, in turn, made the platform a more popular place to list one’s property. In addition, aided by the resources of Finn, the product became more capable and better known. It was increasingly used by agents to inform themselves about locations in order to increase their chances of winning a listing. They also employed location insights to better highlight special features of their ads, for instance ski slopes close to a mountain cabin or the proximity of the shore for a seaside house.
Every part of the product system thus reinforces each other: value created for one party spreads to the other players as well. This makes the product as a whole more valuable and hard to dislodge by competitors. The result is a strong market position for Finn: its neighborhood information product has become central for real estate listings in Norway, much beyond the finn.no core platform.
And this is not yet the end: based also on location information, Finn are working to help users find the right property by presenting similar properties. They are also planning to include neighborhood infos in their search (“Give me a property with great public transport”). Highlighting carbon footprint differences across properties (e.g. because of a longer or different commutes) is another focus area. The goal there is to nudge people into making more environmentally-conscious choices.
Unfriendly market forces: Spain
To make the importance of market dynamics even clearer, let’s compare Norway with a market in which its forces work against this value proposition, Spain: Here, Jørgen explained, their location product was much less successful. The reason: agents there do not have exclusivity for listings, so every agent has a much lower incentive to invest in their ads. Why? A sale may well happen via another agent. As a result, agents are less willing to pay for location information and may even not publish a property’s address to not have it snatched away by another agent. Not knowing the exact address, of course, makes a neighborhood intelligence product much less powerful.
Market forces make or break products
What does this all mean? A product leader needs to be very clear about the market structure. What are the players, what are their incentives and where is value created. Is it possible to structure and position a product in a way that it serves more than one party or use case? Market forces are so important that I would even add market structure and incentives to a product manager scope beyond ensuring desirability (will people want this) and viability (is this profitable and can our business support it). This would highlight its importance for PMs and founders who, myself included, often neglect this aspect.
To conclude, I will leave you with this question: what are the key participants in your market, what do they want and where exactly is value created? Being clear on this may open new use cases for your product or help you discover virtuous cycles based on multi-party use cases. Having understood this, you have the chance to build a much stronger product: more profitable and harder to copy or displace by your competitors.
Are you working on an innovative geo data use case in real estate? I’d love to chat!
Also, if you have questions or comments, please reach out to firstname.lastname@example.org or geosci.de/en/contact.