Humanity has known “where things are” since the dawn of cartography, with clay tablets from as far back as ancient Babylon detailing the precise locations of various sites around cities. In recent years, with the widespread proliferation of smart devices, we can now augment this geographic analysis with human movement at varying scales and over time. But the new availability of mobility data doesn’t mean points of interest are any less important. In fact, the increasing amount of things we can do with geospatial data makes having reliable and accurate POI data even more critical.
If we stop to think about points of interest and the ways in which they’re collected, we’ll come to find that they are most valuable when combined. Overlaying places with people, over space and over time can have many applications, but without a solid foundation of places, there is not much to analyze.
Yes, mobility data is important. Its importance, however, is limited to revealing the spatial behavior of human beings (or cars or trains or critically endangered Russian eagles) in relation to physical places. But it’s important to note that if you don’t know where places are located, the mobility data is rendered largely useless.
Another nuance is what we’ll call the fallacy of staticism (arguably not a word, though we found a document from Nietzche employing it and feel we’ve got a green light on this one). By staticism we mean the idea that they represent static, near-monolithic locations. This couldn’t be farther from the truth. Especially when it comes to commercial businesses their physical locations are anything but static. Look no further than this past year of tumult to validate our position that POIs are dynamic data points.
Once we acknowledge that businesses come and go, that points of interest change constantly, and the world as a whole lacks permanence, the next question becomes, ‘what cadence are changes being observed and reported in the data?’ If you have mobility data detailing movement patterns throughout Manhattan with a daily update cadence, they’d be largely useless if the POIs against which the data is intersected are more than a year old.
At SafeGraph, we recognize that the world is always changing, so we update our Places data every month to ensure that your decisions are based on facts about the physical world, not rusty pings from times long past.
Because everything has a geography, we learn of new uses for points of interest data everyday. But five use cases for places data do come up more than often than others. While far from exhaustive, here’s a breakdown of the primary roles that POIs play in driving key analyses across five sectors of business.
At the risk of using a convoluted term here, we’ll refer to companies with a direct focus on mapping products in the geospatial industry. Think of the mapping applications you use on your phone to find a gas station or coffee shop. The goal is to “know where things are” and update information about those things. If a store name changes or a place goes out of business, clients of mapping companies, whether individual users or enterprise clients, will want to know about it. Analyses are often performed on the data but the main goal always begins with knowing the location of as many places on Earth as possible.
Real estate firms want to know how patterns in peoples’ movement and the presence (or lack thereof) of certain businesses can act as proxies for growth in a given region. The classic example here is following certain brands’ physical expansion into new neighborhoods, the logic being that as popular brand A arrives, their target demographic inevitably follows. These sorts of analyses can be performed with points of interest data in both positive and negative scenarios, allowing real estate professionals to also identify areas to hold off on investing in for the time being.
The consumer packaged goods space covers everything from cookies to paper towels and beyond. Often we see among CPG brands a desire to more accurately identify and predict their total addressable market. This is the hypothetical denominator of all businesses that could carry a given product. Reaching this figure and expressing it spatially allows companies to better focus their expansion efforts at scale. CPG firms can also use points of interest data at a much more granular level to plan out expansion within a given city; for example, a candy company looking to sell into convenience stores in Chicago starts by identifying clusters of corner stores from neighborhood to neighborhood.
The term ‘financial institutions’ is intentionally vague and refers to every arm of finance and capital markets, as well as the ancillary offerings that serve them. Think investment banks, retail banks, PE firms, hedge funds, and management consultants. The variety of applications of points of interest data for these organizations is as wide as their own diversity, but generally speaking, the focus here is understanding how variations in locations across space and time can be used to predict implications for investments. For example, tracking the openings and closures of a particular segment of business across an entire country can better equip a team to make calls on whether to invest in expanding their investment into public equities of that sector. These same analyses can take on a much more granular level, sometimes even down to the block.
When we think about health in the context of location data, it seems the more common association found in discussion is around mobility data. It makes sense: understanding how people move around and where they do and do not spend time can shed light on myriad public health inquiries. Yet mobility data lacks room to fully shine without the ability to consider its relationality to a given subset of POIs. The value of points of interest data from a health context is in no way dependent on using it with mobility data. Many use cases require none at all. Consider the measurement of access to primary health care in a given part of the country. The real inputs we’d hope to have on hand are the places themselves, then demographic data on what kinds of people and how many live within a catchment area or other radius around each location. We might also look at survey data detailing what modes of transportation are available and preferred by the local population to further inform the parameters used to create the catchment areas.
Points of interest are critical for geospatial analysis in any industry. Without reliable places data, mapping, real estate property management, financial analysis, CPG planning, and public health initiatives would lack essential information for identifying areas of opportunity and risk. It’s a quirky trend in the world of location analytics that information on how people move about often occupies more of the spotlight than information on what places lie where - but it’s important to remember that without POI data, like Places, mobility data would likely lead to stale insights without context.
