In the years since we launched our Neighborhood Boundaries™ product, our market has grown, and our processes have evolved in response. Increasing refinement of sourcing methods, customer feedback, and shifts in the world economy impact which metro areas we include in our product.
This is especially true outside of the United States and Canada. Internationally, we make measured decisions every day about which neighborhoods to map.
Intelligent Neighborhood Targeting
When we began mapping neighborhood boundaries on a global scale in 2010, we selected the metros to target based on their population. As this process has evolved and market expectations have changed, we now take additional indicators into account, including economic viability and tourism activity.
Maponics uses an “intelligent targeting” process to identify the most important cities for our customers. To compile the database, we use a scoring system based on indicators such as economic viability (GDP and GDP per capita) and tourism, along with additional scoring indicators based on customer inputs.
Berlin vs. Jakarta – Which to Include?
Intelligent targeting means that we examine a variety of factors about a city to determine when to include its neighborhoods in our database.
For example, if we used only population to compare Berlin to Jakarta, we would conclude that Jakarta takes priority over Berlin, as Jakarta is nearly three times the size of Berlin in population.
However, when you look at factors such as GDP and tourism, you see that Berlin exceeds Jakarta in economic relevance – suggesting that priority should be given to mapping Berlin’s neighborhoods over Jakarta’s.
|| ~9,600,000 people
|2010 GDP per capita
|Tourism: overnight visitors
|Tourism: airport enplanements
|Digital connectivity (country ranking)
Maponics’ Comprehensive Approach to International Neighborhood Sourcing
Using intelligent targeting, we have developed a consistent and comprehensive approach to building international neighborhoods.
Admittedly, it is difficult to pinpoint a method that accounts for all variables in a global market. However, our efforts have made it clear that indicators of economic growth, tourism, and others in addition to population are particularly relevant.
We will continue to refine our intelligent targeting to ensure that we’re mapping the global metros that are most important to our customers.
Maponics is known for providing state-of-the-art data for neighborhood polygons. Through our Neighborhood Boundaries™ product, we offer boundary data for different types of neighborhoods in urban areas.
But there are other communities where people live and work that are not so urban. To provide data about these geographies, Maponics has developed +Residential Boundaries™ – a new dataset designed to complement our Neighborhood Boundaries product. +Residential offers overwhelming residential coverage, with 100,000 U.S. boundaries and plans to expand to half a million residential boundaries by 2015.
The neighborhoods in +Residential are single use – at least 90% of each boundary consists of homes and apartment buildings. In contrast, neighborhoods in our Neighborhood Boundaries represent a mix of uses, such as service and retail businesses, homes and apartments, and public locations.
Summit Park – a town home development in the Denver metro region – is one of the areas included in Maponics +Residential Boundaries. Image source: Street View – Google Maps
Better Insight for the Real Estate Industry
In addition to providing overwhelming coverage of residential geographies, enabling real estate agents to reach more end users, +Residential gives customers a refined understanding of the use and function of the polygons in their dataset.
With +Residential, real estate portals can offer their users the chance to find homes within residential-only areas in the suburbs or bedroom communities of a metro region. This helps consumers conduct “lifestyle” property searches – that is, searching for all the locations that offer a suburban lifestyle.
Further, our residential boundaries help when analyzing the housing market by narrowing down variables. Rather than comparing home sales and values among mixed-use neighborhoods that might be different from each other, +Residential enables businesses to compare neighborhoods that are all singular in character and function. Fewer variables mean more reliable results.
The residential boundary for Summit Park in Denver.
Expanding the Concept of “Community”
+Residential Boundaries is fully compatible with the 2.0 Data Structure of Neighborhood Boundaries. Because the data in the 2.0 version of Neighborhoods is more uniform, it’s easier to add on companion datasets that extend the characterization of communities beyond urban neighborhoods. +Residential is the first of these companion products.
In the coming weeks, look for an interview with Paul Gallagher, Maponics’ Vice President of Marketing and Product Development, about our upcoming expansion of the Communities™ product family.