Pedestrian traffic is one of the most relevant indicators in location intelligence projects. Given the difficulty of knowing exactly the number of passers-by when we need to analyze a high number of locations, the ideal approach is to work with floating population estimation models, as I explained in a previous post.
We will focus here on quickly presenting the applications and benefits of using pedestrian models in geomarketing:
Pedestrian Traffic in Retail
In the analysis of physical stores or establishments, it is obvious that foot traffic is one of the variables that best explains the turnover of each location, especially for impulse or convenience consumption: gifts, bookstores, hospitality, convenience food, and more.
The following graph shows the relationship between the turnover of a set of retail establishments —grouped by deciles— and the value of the pedestrian index developed by Unica360 (as an average for each decile of establishments). The conclusion is clear: when taking a certain volume of cases, there is a direct relationship between the pedestrian index and the establishments’ turnover.
This direct relationship makes floating population key in retail geomarketing projects: catchment area analysis, commercial network segmentation, selecting optimal locations for expansion…
Pedestrian Traffic for Real Estate
It is clear that foot traffic is a deciding factor in determining the value of a commercial premises. From appraisal entities or banks to final clients (retail brands), as well as real estate portals or agencies, everyone needs to know the market value of properties as accurately as possible.
Having a good pedestrian traffic model allows for the automatic «enrichment» of thousands of properties, reusing this information in subsequent analytical segmentation processes. For example, the real estate department of a retail chain could «filter» properties served by a real estate portal, keeping only those that exceed a certain pedestrian threshold and continuing to analyze only those. Or directly cross-reference this indicator with prices to search for discrepancies in the correlation between both indicators.
The following map shows our Microtarget pedestrian traffic index and a series of commercial premises segmented by price. The approach consists of identifying premises with a «low» price (lighter color) located on road segments with a high pedestrian traffic index (red). Even though both are generally correlated, finding those cases far from the regression line represents a great commercial opportunity.
Finally, in the residential sector, pedestrian traffic is an indicator that qualifies a home, which can be applied to housing segmentation in various ways: recommendation engines, or user interfaces that allow choosing between «lively» or «quiet and silent» areas.
Pedestrian Mobility and E-commerce
It might seem like there is no relationship, but the great challenge of e-commerce today lies in «last mile» logistics: designing optimal delivery systems that minimize the monetary and ecological costs of goods delivery.
In this sense, e-commerce has a great opportunity with pickup point systems (PUDOs), whether they are stores, lockers, or post offices. For this, it is key to design an optimal pickup point network based on the population in the surroundings, but also based on the transient pedestrian population.
Pedestrian Traffic and Out-of-Home (OOH) Advertising
Measuring the effectiveness of OOH advertising has been an aspiration for advertisers for decades, as shown in the interesting methodological paper from AIMC: Audience measurement in OOH advertising (2000).
The segmentation possibilities that pedestrian traffic models bring to OOH advertising are immense:
- Pricing adjusted to the audience of each specific support.
- Location expansion: acquiring supports or placing new ones optimally.
- Designing segmented circuits by audience type.
The following map shows a pedestrian traffic analysis against a series of OOH supports (billboards, bus shelters, banners). The client/advertiser wanted to know the quality of the contracted supports and the differences between supports in the circuit, with the goal of requesting personalized circuits.
Urban Pedestrian Mobility and Smart Cities
Foot mobility patterns are decisive in analytical projects for Smart Cities, urban planning, mobility optimization, equipment sizing, and transport demand. A pedestrian traffic model that allows for behavior simulation through complex scenarios is key in many of these projects.
Similarly, telecommunications services—whether public (municipal WIFI antennas) or private operator networks (fiber, high-speed mobile coverage)—are affected by pedestrian traffic intensity.
If you need precise and reliable pedestrian traffic estimations, we can help you. You might also be interested in how to simulate vehicle mobility and the applications of vehicle traffic in location intelligence.
Guillermo Córdoba