The first step to analyzing the potential liquidity of a marketplace is understanding its geographic extent. For example, Upwork will see transactions filled between freelancers and employers all around the globe, while Tinder will (typically) only see two people dating within the same city. Tinder would therefore require a city per city launch and a city per city liquidity analysis. In local marketplaces, there is a strong correlation between density and liquidity. The higher the number of participants within a relevant radius, the higher the liquidity of the marketplace Security Operations Center.
as the number of transactions filled out of the total potential transactions in a marketplace. We refer to density as the number of participants within a certain geographic area.
Let’s use Tinder as an example. If in a given week Tinder acquires 1,000 female participants in Chicago and 1,000 male participants in New York, Tinder’s number of total users increases, but its liquidity remains the same Day Trip to Macau.
Now, if Tinder acquires 1,000 female participants and 1,000 male participants all located in the borough of Brooklyn, this higher density of users (from both sides of the marketplace) will lead to higher liquidity.
To determine the density in a marketplace, you need to first define the limits of the geographic area within which its transactions can be filled.
This distance threshold (“r” in the visual below) is different for every marketplace and you will identify it by understanding how far your customers are willing to travel to complete their transaction. For example, a seller at Letgo might not be willing to travel 30 minutes to sell a used skateboard for $30, but a babysitter at Care.com will likely travel 30 minutes to make $150 for a day of babysitting Window Type Air-Conditioner.
Once you define this distance threshold “r” you need to maximize density. But how?