July 8, 2020
Now more than ever, understanding the impact of location on store performance is vital. Places are dynamic, and as the fallout of the COVID-19 pandemic continues, are changing more rapidly than ever. These changes around your store or store network in turn can have a significant impact on performance.
One of the best ways to measure performance and put sales into context is by layering detailed footfall data on sales and revenue figures to understand the reasoning behind changes or fluctuations in performance. In this blog, I'm going to run through four of the key footfall trends you should be measuring to understand how the location of your store is impacting performance.
Photo by Anna Dziubinska on Unsplash
TOTAL volume of footfall
In order to assess how a store is performing it is important to understand the base level of footfall in a given area. When footfall data is harnessed, stores can identify opportunities and determine whether there are enough passing customers to make operating worthwhile. For example, if your store is located just off a main retail thoroughfare, are you accessing enough customers from the main street? And is the saving in rental costs offset by the lack of passing consumers?
The example below shows footfall levels for two locations in the same city centre with a Local Data Company footfall sensor, about a 2-minute walk away from each other.
Figure 1 shows that Location A’s weekly footfall peaks at 81,000 in summer, while Location B has a peak of only 61,000 – a substantial difference. Over the course of the entire year, Location B sees volumes 42% lower than that of Location A despite their close proximity. Even after carefully selecting a town/city based on demographics and other key metrics, analysis must drill down to micro locational trends. This level of forensic insight can make all the difference.
Figure 1: Weekly footfall throughout the year in 2 locations in the same city (Source: Local Data Company)
Analysing hourly footfall trends can be useful on top of conversion rates and other performance KPIs to indicate the most profitable times of day.
For bars, clubs and entertainment businesses, mornings are largely irrelevant. The majority of stores are closed before noon and come alive at night. These units would, therefore be better suited to a location which is relatively quiet during the day and picks up in the evening.
Figure 2 shows three footfall trajectories for locations in the same city, all with different consumer missions: leisure focused, shopping focused, and office worker dense which all have different trajectories throughout the day. Footfall at the leisure destination increases at a more gradual rate than the other 2, reaching its peak in the evening as leisure activity fuels the night time economy.
The shopping location has a smoother curve with a longer peak from 1pm to 7pm. At this point footfall drops sharply, as day turns into night and stores close shutters. For the worker location, there are clear peaks in the morning, lunchtime and the afternoon as you would expect.
This kind of forensic examination of hourly trends allows us to pinpoint the most suitable location for any type of store.
Figure 2: Hourly footfall profile of different locations (Source: Local Data Company)
Daily profile throughout the week
Analysing how daily trends differ between the working week and the weekend provides rich insight into the profile of a local area and supports our understanding of the demographics of the surrounding catchment. We can determine if an area is comprised of office workers (peaks around 9am, lunchtime, and 5-6pm on weekdays, but quiet weekends); or, a weekend shopping location (quiet weekdays and general increase in footfall on weekends). Leisure-focused areas also tend to have more consistent footfall throughout the week, and then an increase at the weekend.
In Figure 3, we return to our three destination types to review the differences between each when we look at the week vs the weekend. Looking at the leisure-focused location first, we can see an expected increase in footfall at weekends. Some consumers prefer to go out on weekends - perhaps dining at restaurants, or a trip to the cinema. In this particular location, we can see that footfall increases by 20% compared to the average weekday.
For the shopping location, the daily average for footfall declines significantly when placed alongside weekends. The worker location experiences a 67% drop in footfall at the weekend – a sharp but understandable decline as this location is almost exclusively office space. Because footfall is so low at the weekend, retail and leisure units in the surrounding area will often close, opting to only operate 5 days a week.
Figure 3: Average daily footfall of different location profiles on weekdays vs. weekends (Source: Local Data Company)
Many retail and leisure destinations function seasonally, and this can have a huge impact on an occupier’s chance of success.
Figure 4 below illustrates the fluctuation in footfall in two locations over the course of a year: a student town and a seaside town. It shows that in the warmer summer months, the seaside town picks up in footfall due to holiday makers, beach lovers and nearby residents enjoying the sun (when it appears…).
At the same time, however, the student town experiences a dip in the summer. Students make up a large proportion of the town’s population, so when they leave there is a notable drop in footfall. When they return for the new academic year, it rises once again.
Annual footfall trends are incredibly useful and support strategic planning of targeted marketing campaigns or budgeting sales month-to-month, based on the evidence and ground-truth data.
Figure 4: Weekly footfall throughout the year in different cities (Source: Local Data Company)
For more information on footfall measurement and tracking, please see our footfall resources page which includes critical information for those starting out with footfall counting.