What are traffic counts and why are they important? 🚗🚶🏻🚦
Traffic counts are counts of vehicular and pedestrian traffic, which is conducted along a particular road, path, or intersection. These are metrics that are essential to retailers and real estate professionals alike for their decision making as it helps to provide key information regarding the flow of traffic to, from, and nearby to a subject site.
There are two types of traffic counting methods that PiinPoint offers:
Municipal Traffic Counts 🚦 - As the name suggests, these are traffic counts collected via studies conducted by local municipalities and tend to be intersectional traffic counts i.e. they capture traffic going in 4 directions. This is a more traditional method of collecting traffic data for these, such as using people counters, camera technology, or road strips.
Mobile Data Traffic Counts 📱 - These are counts that are modelled through using mobile location data and GPS pings from multiple unique devices. This method is relatively newer and incorporates the use of more advanced technology that allows us to derive these counts using a powerful machine learning model that is trained on trusted real-world data. We dive into more detail on this below. 👇🏼
What is Municipal Traffic Counts?
Traditionally, traffic and pedestrian counts have been sourced from municipalities and government organizations such as the Department of Transportation. While many larger municipalities and organizations conduct regular, statistically representative studies, other smaller municipalities and organizations conduct such studies infrequently or not at all.
Furthermore, many traffic studies are based on small sample periods such as a single day or maybe only part of a day and that data is extrapolated as if it were representative of typical traffic volumes of that area.
Nevertheless, this data is a valuable location analysis tool, particularly when assessing the busyness of two sites in the same city. To learn more about PiinPoint’s traditional traffic feature click here.
What is Mobile Location Data Traffic and why should I use them?
Mobile Location Data is a game-changer when it comes to tracking daily traffic volumes. PiinPoint’s custom vehicle traffic query allows you to look at modelled AADT (Average Annual Daily Traffic) and pedestrian counts for any major road segment in Canada & the US. That includes far-flung communities like Fort St. John, British Columbia.
In order to do this, PiinPoint has partnered with Veraset (SafeGraph affiliated company), a leading provider of anonymized mobile location data, to draw insights from 45 million mobile devices each month across North America.
Using advanced machine learning methodologies, PiinPoint is able to extrapolate on the sample of anonymous mobile traffic data to represent 100% of the North American population. PiinPoint takes into account demographics, population statistics, and observational data to ensure accuracy. In fact, our methodology enables us to see a median accuracy of over 81%, which instills confidence and offers insights that you can trust to make key business decisions.
Some of the key advantages of using Mobile Location Data Traffic counts include:
Apples to apples comparisons - The methodology used can be consistently applied across any geography or road segment
Far broader coverage - Using mobile data and GPS pings, we aren’t restricted to areas where a formal study was conducted, but we can now tap into pretty much any major road segment given that there is mobile data and GPS activity present there
Based on annual samples of data - Our traffic counts take into account annual sampling of data that we later breakdown to show on a more granular level. This provides you with more robust and consistent data to work with
Offers more granular insight - As mentioned above, our data is sampled annually which we further break down on a more granular level i.e. vehicles per day, pedestrians per week, etc. which allow you to see the traffic flow patterns and locate the peaks and dips in movement allowing you to get more insights and make the smartest decisions than ever before.
To learn more about MLD Traffic and watch it in action, click here.
FAQs Regarding Mobile Data Traffic
How is the data collected and who provides it?
PiinPoint has partnered with Veraset (SafeGraph affiliated company), a leading provider of anonymized mobile location data to source insights from 45 million devices each month across North America.
How do you distinguish between which mobile ping is a vehicle vs. a pedestrian?
Our traffic counts are distinguished by their respective travel velocity over a period of time. We have time stamps on each observation which allow us to make assumptions about the type of travel the mobile device was doing based on the interval between each ping. While it is far more nuanced, very simply put, higher velocity pings could be attributed to vehicle activity and lower velocity pings as pedestrian traffic.
What makes Mobile Location Traffic different from the traditional municipal traffic counts?
While traditional municipal traffic counts are conducted by local municipalities and/or government organizations, and are often based on intersectional traffic data that is only conducted at their sole discretion, it often proves to be difficult to truly rely upon.
Mobile Location Traffic helps counter all these issues by using mobile phone and gps pings from over 45 million devices, looking at virtually any road segment, being updated annually, and taking into account directionality of the traffic flow. Using mobile location data for traffic analysis allows for a more apples-to-apples comparison, higher accuracy and focused traffic count analysis to take place.
Why do these counts seem so much higher or lower than the municipal counts?
Sometimes, the counts generated through mobile location data appear to be either higher or lower than those seen using the traditional municipal counts. This happens for multiple reasons such as directionality, how many roads are feeding in to the count, how long of a segment it is, one way vs. two way street, etc.
Given the different methodology of data collection and calculation in order to generate traffic counts, there may be certain discrepancies. However, rest assured that multiple points and concerns have been taken into account and PiinPoint is able to generate traffic counts using mobile location data with 81%+ accuracy.
Why is this showing a one-way when I believe this to be a two-way road?
Sometimes, it happens that the road we are looking at has a median in between separating the road in two. Even though it might technically be the same road, given the median in between, PiinPoint’s road classification system treats it as two one-way road segments in order to increase accuracy and make it easier for the user to understand.
What types of roads do you cover?
We cover the following road segments:
What do the different colors on the segments indicate?
The different colors on the road segment indicate the different sides of the road and help out with understanding the directionality of the highlight road segment.
What determines a segment length?
PiinPoint’s road network data is derived from the road network from Open Street Map (OSM). With this dataset, there are many attributes that describe each road such as speed, number of lanes, road hierarchy (highway, primary road, secondary, etc.), and many more. A single road segment is typically from one intersection to the next intersection, with an intersection being when a road makes contact with another road (an overpass would not count as an intersection with the road under it). However, wherever there is a change to one of these attributes, the road is split where the change happens. This leads to the final road segment length, and why you may see many different road segments between intersections.
How is privacy maintained for the mobile data you collect? Can you identify who the mobile devices belong to since you’re using their location data pings? PiinPoint has partnered with Veraset (SafeGraph affiliated company), a leading provider of anonymized mobile location data, to draw insights from 45 million mobile devices each month across North America.
It is a dataset that is enabled only through consumers consenting their sharing of location. The general impression toward location-enablement is contentious; particularly regarding how much of an effort apps make to ensure the user understands what they are opting-in to. PiinPoint takes additional precaution in the delivery of mobile location data. First, the data is anonymized. PiinPoint ensures the data is de-identified, where the observations have only a device ID, disconnected to any individual user. There is no information collected regarding the individual, contrary to popular assumption that the insights include information on the individual’s usage on the phone, what apps they have, or their contact information. Second, the data is aggregated for display or understanding in PiinPoint products and services, so there is no way you can look at one individual - even a de-identified one - and their unique activity. Data is aggregated to either a Dissemination Area (DA) or Road Segment. For geofencing purposes, there must be a minimum of 15 people within the geofenced area to be visualized.
How is your Mobile Location Data impacted by Apple's recent iOS 14.5 update?
On April 26, 2021, Apple released an iOS update (14.5) that would add increased privacy settings for iPhone users, by allowing them to opt-out of apps being able to track your activity across sites. Activity in some cases, includes location activity. Many users of Mobile Location Data have wondered if this change will impact the data created by vendors such as Veraset.
Throughout the month of May and June 2021, PiinPoint has actively monitored the size of observations being received from Veraset. Thus far, there have not been significant changes to the data available. This is likely due to the fact that the iOS 14.5 updates were primarily focused on tightening restrictions around other activity tracking, as opposed to simply detailed location settings.
PiinPoint continues to work closely with Veraset to monitor and see if these observations change.