How to measure foot traffic in a wholesale market?

POI analytics through Big Data techniques allows companies to understand an area of interest and thereby implement strategies, expansion models, and solutions within any business sector.

Information about a specific location or a set of similar locations can help companies make better decision-making. Combined with additional contextual parameters such as human mobility, sociology, dynamics of an area, etc., POI data can be used to build meaningful information structures that enable more robust analysis and planning for expansion models.

Businesses can use POI data to identify, locate and analyze shopping areas, assess new business opportunities, and outperform their competitors by evaluating their performance through observing foot traffic around and outside their outlets, and by using alternative data to understand consumer behavior.

At PREDIK Data-Driven we conducted a detailed study where we characterized one of the largest wholesale and retail markets in the world, located in Mexico City, Mexico, during the month of February 2021.

Through analysis and characterization of the point of interest, we estimate the specific locations where the highest amount of pedestrian traffic is found, classify pedestrians as residents, workers, or visitors, count the observations per day, collect sociodemographic aspects and categorize the most visited places in the city, in order to obtain and know the distribution of visits that are generated in various areas of interest. This analysis aims to answer the following questions:

Which areas and locations have the highest concentration of foot traffic?

By generating a heat map covering a radius of one kilometer, we identify the foot traffic around the market, allowing us to identify the mobility patterns and the concentration of visitors in the area.

Within the analysis, several calculations are performed, where we segment vehicles and pedestrians, allowing us to omit vehicles from the analysis, which generates much more detailed and focused information on consumers and the market in the area.

Which is the distribution of visits at the wholesale market?

With these analyses, it’s possible to perform the percentage distribution of visits per hour, day, month, and year allows us to estimate the times and schedules of certain stores or locations, to understand the moments of the day where the peak of foot traffic appears, to evaluate the average dwell time of visits within zones or points of interest and to identify the times of the day that are more and less favorable to implement a product or service.

This helps businesses gain an overview of how crowded the market is and how the foot traffic the area distributes by day of the week, month or year, allowing them to implement strategies to reach objectives faster and more efficiently.

Who are the people that visit the wholesale market?

With a data layer of the Global Wealth Index, collected by Facebook, the economic levels of the visitors were estimated. Meanwhile, by applying location intelligence analytics, corporate buildings, residential areas, schools, etc. are located; allowing us to classify the inhabitants as students, workers, residents, or “floating or instant population”, i.e. people who only pass through that area to get to another location.

What other places are visited by the people identified in the wholesale market?

The points of interest identified in the area were also categorized to understand foot traffic behavior patterns and thereby identify potential markets and locations that generate the most activity.

We also conducted a detailed analysis of the behavior and mobility of people in the municipality of Karisandra, in BangaloreIndia. Read the complete article here

Thanks to the frequency of updates, coverage, ease of use, and consistency of the data, these analyses help determine where to build new infrastructures (site selection). At PREDIK Data-Driven we help our clients understand consumer behavior patterns, measure competition, and understand user needs by region.

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