Posted by Angela Diaco
This weekend, the Super Bowl will thrust the fans, cultures and cities of Boston and Seattle into the global spotlight. Although they are separated by over 3,000 miles, they share quite a few qualities beyond hosting dominant football teams. We decided to investigate these cities' cultural identities, what makes them unique, and what the density of venues there say about local lifestyles.
At Skyhook, we have a unique view of the world. We've rigorously curated a database of every POI venue in the US, categorized by universally used taxonomies IAB and Google AdWords. We dug into our database to create the Venue Bowl 2015:
Boston and Seattle have nearly identical populations (by 2013 estimates), yet Seattle spans a much larger area. Another noteworthy consideration is how drastically the college student population deflates skews Boston's residential statistics (up to 30% by some estimates). Our interpretation of that skew is that while there is a significant portion of Boston's population that rarely dine out, shop, and indulge in luxuries, they are offset by residents of populous nearby areas such as Cambridge who eat and shop in Boston. By comparison, Seattle city limits cover a larger geographic area in which venues are more likely to depend on Seattle residents.
The national average referenced in the infographic was created based on the venues per capita and venues per square mile of the most populous 100 US cities. We compared venue category counts for Boston and Seattle against the index, but depending on the venue category, we used either a per capita or a square mileage comparison. This is because some venues, by nature serve geographic areas, and some serve a population. For example, grocery stores tend to be large venues, and are not frequently found in clusters. But it isn't uncommon in a major city to find several coffee shops on the same block.
Our venue database is a core component of our Personas and Context product, fueling key features such as Personas and Infinite Geofences. As a result, we place a high value on high quality venue data because it ripples throughout our product. Before entering any venue into our production data set, we perform thorough data quality testing, which we developed when building our global first-party location network.