Opening up a restaurant in New York?
Here is the example of an analysis that uses expert knowledge, data science and all kinds of available data to discover the best location for a new business.
The three most important things in retailing are: location, location and location.Lord Sieff of Brimpton (Marks & Spencer)
One of the most important strategic decisions to be made when opening up a business is choosing the perfect location for it.
At minimum, it should be highly-visible, competitive, stay within a reasonable budget, have sufficient customer base and meet local and state regulations. Criteria must be stringent because, once made, location decisions can be very difficult to undo.
The importance of location is something that PlaceLab crew knows plenty about. We are here presenting the results of a proof of concept that demonstrates the full range of PlaceLab’s capabilities. The main concept was based upon the general problem of choosing an optimal location for any business. Ultimately, the geographic and business domain criteria were narrowed to finding the perfect location for a restaurant in New York City.
The site selection process must encompass all elements that could possibly have any influence on the success of a restaurant.
Food quality, service and ambiance are naturally, essential factors, but so is the number of workforce in the area, crime rates and accessibility. In addition, the evaluation process must also account for competition, their reviews and price ranges.
Results of the analysis for the sample of 29 available rental spaces are shown on the map bellow. Narrowing down the final location occurs over two phases: selection of a region and actual site selection. Some of the factors used for the analysis on both, region and individual property level, can be discovered on the map.
Explore some of the best regions and rental spaces for a restaurant in NYC.
The optimal business property is currently one-click away. However, the solution can be expanded to match any geographical area,type of business and to allow users to actively participate in the decision-making process. For example, users might already have a preferred region or would like to drive the analysis into direction that suits the vision of their business in the best way.
Data sources used for this research include USA Census Bureau, NYC Open Data and Google Places API. Information regarding the actual properties was manually assembled and might differ from the current real estate market offering.