Pathing reports provide detailed information about the travel of individual devices, either contextually in time to a visit to the study locations, or alternatively, following the travel over a specific interval or independent period of time
Table of Contents
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Pre-Post Report/Pre-Post Sampled
Provides, for all study locations, all the points the device was seen before and after visiting a specific polygon. The timeframe for the before-and-after window is set at the time the report is requested. The report is formatted as follows:
| Polygon ID | UM ID | Unix Timestamp of Visit |
Pre-Post Visit Timestamp |
Pre-Post Visit Latitude | Pre-Post Visit Longitude |
This report can be tricky to work with when first using it, as data for both pre-visit observations and post-visit observations are mixed together in one column.
Pre-Post Report Interpretation
As mentioned in the main body of this paper, the pre-post and pre-post sampled report can be tricky to interpret without guidance. An example of a report could look like this:
|
Polygon ID |
UM ID |
Unix Timestamp of Visit |
Pre/post-visit timestamp |
Pre/post-visit latitude |
Pre/post-visit longitude |
|
Polygon A |
ID 1 |
150050 |
150020 |
39.55440 |
98.656031 |
|
Polygon A |
ID 1 |
150050 |
150000 |
39.55443 |
98.656029 |
|
Polygon A |
ID 1 |
150050 |
150175 |
39.55601 |
98.656031 |
|
Polygon A |
ID 1 |
153950 |
153900 |
39.55478 |
98.656004 |
|
Polygon A |
ID 2 |
150154 |
150006 |
39.875541 |
98.487265 |
|
Polygon B |
ID 3 |
150695 |
150716 |
39.546819 |
98.586512 |
In this example, during the timeframe of the report, Polygon A was visited by 2 different uniques, ID 1 and ID 2. ID 1 visited Polygon A twice (timestamps 150050 and 153950). The first three rows relate to the first visit to Polygon A by ID 1. On the way to Polygon A, ID 1 was observed twice (rows 1 and 2 show timestamps lower/before the timestamp of the visit). Row 3 shows a point where ID 1 was seen once after the visit to Polygon A (pre-post timestamp higher/after the visit timestamp).
ID 2 visited Polygon A and was seen only once in the before-after window, in this example case, just one time at 150006 before the visit at 150154.
The Pre-Post Sampled report is delivered in the same format, but only a sampling of pre-and- post visits is used. This sampled report is good for use cases where the amount of data returned in the pre-post regular report is overwhelming and unwieldy, making analysis by non-big data engineers a challenge. A random sampling of pathing behavior is often sufficient to pick up broad trends for pathing.
Pathing X Report
The Pathing X Report, like the Pre-Post report, also contains information about the travels of a device before and after being seen in a study location. The data, however, is presented in a different format:
In this case, the timing of the observation in relation to the visit is expressed in a +/- format.
|
Polygon ID |
UM ID |
Latitude of Observation Point |
Longitude of Observation Point |
Time Before Appearance In Polygon |
Unix Timestamp of Observation |
A value of 60 in the “Time Before” column means the observation happened 60 seconds before arrival at a study location. A value of -120 means the observation happened 2 minutes after the appearance in a study location.
Note that there will be some lines in this file that have a Time Before value of zero—these are the so-called “zero points” and represent observations inside the study location.
Pathing X with Context/Context-Only
The Pathing X Report contains all the points a device was observed. The Pathing X with Context enhances this report by adding 3 additional columns to the report:
| Polygon ID | Polygon Name | Polygon Category |
This report leverages Near’s internal library of high-quality retail polygons. If an observation point appears inside one of these locations, then the information about that location is appended to the observation.
This report also has an option to receive only those pathing reports that are within Near's polygon library, instead of all points enhanced with the context.
The Pathing X Rollup report, or Feeder report provides a summarized output of where visitors to a location visit before/after visiting the study locations. The results are delivered in a series of four files that are at the polygon, polygon category, sub-sector and sector level.
The sector analysis file contains some special values in it, in addition to the sector information. The report has a “CEL” value which is the percentage of study location visitors who were seen at their CEL within the report’s pre/post time window. The “CDL” value is the percentage of visitors who were seen at their CDL in the pre/post window. And then finally, “Transient” indicates that the visitor was only seen in points more than 20 miles away from the study location that was not near their home or work area (thus being likely transient through the area).
The sector file is thus formatted as follows:
|
Destination Category |
Sector Name |
Number of Uniques |
Percent Appearing in Sector in Pre/Post Window |
Subsector:
|
Destination Category |
Sector Name |
SubSector Name |
Number of Uniques |
Percent Appearing in Subsector in Pre/ Post Window |
Category:
|
Destination Category |
Category ID |
Category Name |
Number of Uniques |
Percent Appearing in Category in Pre/ Post Window |
Polygon:
|
Destination Category |
Polygon ID |
Polygon Name |
Number of Uniques |
Percent Appearing in Polygon in Pre/ Post Window |
Custom Context
Instead of using the Near internal polygon library, API users can pass in their own custom POI to use for context. This is done by means of a standard geoJSON input which can contain categories and polygon names.
Cluster Report
The cluster report is a specialized pathing report which attempts to algorithmically identify popular stopping points for devices on their way to and from study polygons. Unlike the “with context” family of reports, this report can identify areas that are outside of identified POI.
The output of the report is a geographic file (geoJSON or geoDB) which can be imported into mapping software. Each cluster or stopping point is identified by a contour shape and a number associated with the contour shape which outlines how many unique visitors were identified as stopping within that contour shape.
Numerous parameters can help adjust the ruleset for when to create a contour, based upon the underlying Human Movement Data.
Supported Countries
| Report Type | Recommended Countries |
| Pathing X | Any |
| Pathing X + Add Context | US & Canada |
| Pathing X + Context Only | US & Canada |
| Pathing X + Custom Context | Any |
| Pre-Post | Any |
| Sampled Pre-Post | Any |
| Feeder | US |
FAQs
The report adds additional columns to a standard Pathing X or device history report. These additional columns add context to the pathing points. If the observation point was within known POI Location, the information about that POI is returned. These observations have to have taken place within the before/after timeframe of the report window.What does "add context" mean for pathing and device history reports?
How do I interpret the feeder report?
The Feeder report provides summary level information of where visitors go before/after visting the study locations. It gives you a sense of what locations your customers also go in route to visiting your store locations.
The report provides the number of devices, well as the percentage of devices seen in your study locations were also seen in those other locations.
The information of where visitors go is provided at the individual polygon level, polygon category, polygon sub-sector, and polygon sector level. This gives you a sense of your customers shopping behaviors and movement.
What are the differences between pathing, pre-post and feeder?
All of these reports provide detailed information about the travels of individual devices.
-
Pre/Post - This report provides, for all study locations, all the points the device was seen before and after visiting a specific location.
-
Pathing - Like the Pre-Post report, this report also contains information about the travels of a device before and after being seen in a study location. The data, however, is presented slightly differently. In this case, the timing of the observation in relation to the visit is expressed in a +/- format.
-
Feeder - This report provides a summarized output of where visitors to a location visit before/after visiting the study locations. The results are delivered in a series of four files that are at the polygon, polygon category, sub-sector and sector level.
Why don't the percentages in my Feeder report sum exactly to 100%?
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