Pedestrian flows in a shopping street are measured using sensor technology, manual counts, or camera solutions that register the number of pedestrians at a specific point over a given time period. The most commonly used methods are infrared sensors, Wi-Fi and Bluetooth tracking, and aggregated mobile data from telecom providers. Which method is most reliable depends on the purpose of the measurement and the available resources.
For retailers and investors looking to substantiate a location decision, insight into pedestrian flows is one of the most concrete indicators of commercial potential. The following sections address the key questions surrounding pedestrian counting and location analysis.
What methods are used to count pedestrian flows?
The most commonly used methods to measure pedestrian flows are infrared sensors, camera footage with image recognition, Wi-Fi and Bluetooth tracking, and mobile data from telecom providers. Each method has a different area of application, level of accuracy, and cost profile.
Infrared sensors are often placed at shop entrances and count the number of people crossing a threshold. They are relatively inexpensive and accurate at a fixed measurement position, but only measure the point at which they are installed.
Camera solutions with image recognition offer more context. They can not only count, but also map walking routes, dwell times, and crowd distribution in a street or shopping centre. This makes them suitable for more in-depth location analyses.
Wi-Fi and Bluetooth tracking detect mobile devices of passers-by and can thereby distinguish returning visitors from one-time visitors. This provides insight into loyalty and movement patterns at street level.
Mobile data from telecom providers is the most scalable method. Aggregated and anonymised location data from millions of users makes it possible to analyse pedestrian flows across large geographical areas and longer time periods, without any physical installation.
How reliable are pedestrian counts in practice?
Pedestrian counts are reliable as an indication of footfall, but the absolute figures are always an approximation. Reliability depends strongly on the measurement method, the duration of the measurement, and the representativeness of the measured time period.
A measurement on a single day provides a snapshot, not a structural picture. Seasonal peaks, events, weather conditions, and public holidays can significantly influence the count result. Reliable pedestrian data is based on measurements taken over several weeks or months, spread across different times of day and days of the week.
Furthermore, a counter always measures a point, not a route. Two premises on the same street can have considerably different pedestrian counts, depending on their position relative to a bus stop, car park, or anchor store. A raw count therefore says less than a measurement that also maps the direction and behaviour of the pedestrian flow.
For professional location analysis, pedestrian counts are therefore always combined with other data sources to obtain a complete picture.
What does a pedestrian flow say about the value of a location?
A high pedestrian flow increases the visibility of a shop and raises the likelihood of impulse visits. For many retail formats, turnover is directly correlated with the number of people passing the shopfront each day. Pedestrian flows are therefore one of the most direct indicators of the commercial potential of a location.
Yet the relationship is not linear. A busy shopping street with a lot of through traffic is not equally valuable for every retailer. A destination store that attracts customers on the basis of a strong brand or unique offering benefits less from high pedestrian counts than a convenience retailer or food retailer that depends on spontaneous visits.
The composition of the pedestrian flow counts at least as heavily as the volume. Age profile, purchasing power, dwell time, and the purpose of the visit determine whether the passers-by are also the target audience of the retailer in question. A shopping street with many tourists has a different commercial value than a street with a high proportion of regular local customers.
Real estate investors and landlords use pedestrian data as substantiation when determining rental prices. A higher footfall frequency justifies a higher rent per square metre, provided the location also matches the tenant’s target audience.
How do you compare pedestrian flows between different shopping streets?
Pedestrian flows are compared by standardising measurements to the same time period, the same time of day, and the same measurement method. Comparison is only meaningful when the measurement conditions are comparable. Absolute figures say little without context about when and how they were measured.
When comparing shopping streets in different cities or regions, additional factors come into play. A pedestrian flow of ten thousand people per day in a medium-sized city has a different commercial significance than the same figure in a prime urban location in Amsterdam, Rotterdam, or Utrecht. Rental prices, the competitive landscape, and the purchasing power of the local population differ per market.
Useful comparison points include the ratio between pedestrians and actual store visits, the average dwell time in the street, and the distribution of footfall across the week. Streets with a high Saturday peak but low weekday occupancy perform differently from streets with a consistent pattern throughout the week.
A specialist retail advisor typically has access to benchmark data with which a specific location can be compared to similar streets elsewhere in the Netherlands. Guidance on location selection is particularly valuable at this point: converting raw pedestrian data into a well-founded comparison requires market knowledge that goes beyond the measurement itself.
What data sources and tools are available for pedestrian analysis?
For pedestrian analysis in shopping streets, multiple data sources are available, ranging from public sources to commercial platforms. The most commonly used are aggregated mobile data, sensor networks from municipalities, commercial location data platforms, and industry research from retail organisations.
Municipalities and city centre management organisations publish periodic pedestrian counts for the most important shopping streets in many cities. This data is often freely accessible, but has limitations in terms of frequency and level of detail.
Commercial platforms offer greater granularity. They combine mobile location data, sensor data, and demographic information to produce detailed analyses at street or even building level. Quality and coverage vary by provider and by region.
In addition to external tools, the proprietary database of a retail specialist also plays a role. KroesePaternotte holds lease contract data going back to 1984, covering virtually the entire Dutch retail market. That historical depth makes it possible to place pedestrian data in the context of actual rental price developments and transactions, converting raw count figures into actionable market intelligence.
When is a pedestrian count not sufficient for a location decision?
A pedestrian count is not sufficient for a location decision when the composition of the pedestrian flow, the competitive landscape, the rental price, or the contractual terms have not been taken into account. Pedestrian data indicates how many people pass a premises, but not whether that location is also commercially viable for a specific retail format.
A location with high pedestrian counts but an above-market rental price may, on balance, be less attractive than a slightly quieter street with a lower rental burden and a better-matched target audience. The ratio between rental costs and expected revenue potential is the actual decision variable.
Moreover, a pedestrian count lacks information about the immediate surroundings. Which retailers are already present in the street? Is there a strong anchor store drawing visitors? Are there concentrations of vacancy that negatively affect the perception of the street? All these factors also determine the commercial success of a location and are not visible in a count figure.
Contractual aspects also fall outside the scope of pedestrian data. Lease length, notice periods, break options, and service charges are decisive for the total financial burden of a location. A thorough location analysis combines pedestrian data with rental price benchmarks, contract assessment, and knowledge of the local retail landscape.
For retailers looking to make a well-considered location decision, it is advisable to regard pedestrian flows as one input in a broader analysis process. Contact a specialist retail advisor to translate pedestrian data into a substantiated location choice, including insight into non-publicly available supply and current rental prices per street and city.
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