Vividi helps a Prague-based shopping mall understand their visitors' behaviour. It provides them with demographic information on customers and peak hours and helps to optimize the space as well as the recommended peak hours for each area. Vividi was collecting data also during the COVID-19 pandemic. What was the impact of governmental regulations and their subsequent easing? We are happy to let you take a peek at the results.
It is important to mention that the shopping mall is not typically organized. It is located in Prague’s suburbs and connected to a public underground transport junction as well as a bus station. It is not too extensive, and the neighborhood residents often use the shopping mall as a shortcut to get to the public transport. The second significant characteristic is the residential area which is attached to the building of the shopping area. The residents of the building therefore also use the halls of the shopping mall to get to the transport or to simply go outside and come back. The shopping mall contains a supermarket, small boutiques, coffee shops, restaurants, a drug store and a pharmacy.
Vividi is an innovative solution for analyzing excessive amounts of variables. The solution is custom-made and accounts for customer interests and needs. This shopping mall focuses on the customers’ demographic data, such as age and gender, and tracks the number of people streaming through its halls. To get the most accurate data and cover the key locations in the mall, the system uses 7 Vividi devices in different areas. The data are merged in the analytic process, or can be used separately to understand the particular events and actions in various places.
In the past months, the whole world has been hit by the COVID-19 pandemic. The Czech Republic underwent a coronavirus lockdown, social distancing, and numerous governmental restrictions. The first positive cases started on 1 March and other confirmed cases followed without delay. The government proceeded to implement various regulations, declared an emergency, and after the critical period passed, it started easing the restrictions.
We used the data of the shopping mall from this period to observe how the pandemic impacted the visitors’ behavior. The graph describes the occupancy in the mall for just over a two-month period, starting from 9 March until 17 May. The easily noticeable regular drops in the graph correspond to weekends. Some of the boutiques are closed on Sunday and the traffic is not so high in the public transport either.
On 10 March, the governmental directive closing all schools came into force, two days after the state of emergency was declared. The data captured by Vividi does not show any clear impact, as the number of people in the mall stays approximately at the normal level. A substantial footfall decline (roughly 50%) happened on 14 March when shopping malls and other shops were compulsorily closed. The specific structure of the shopping mall and the particular stores in the mall ensured the drop was not to zero visitors per day. Other shopping centers were closed since that date and had no traffic. In this particular mall, the traffic was created by a few stores which remained open, such as the supermarket and pharmacy. The rest of the traffic can be ascribed to the residents, as people shortcutting their way to public transport creates a low level of traffic. The other irregular drops were caused primarily by state holidays (Easter on 13-16 April, 1 May, and 8 May), marked by red arrows in the graph.
After the biggest drop, the number of people did not remain the same. We can observe the trend of slow growth of the number of visitors since the beginning of April.
We cannot see any distinct divergence right after the releases. For instance on 2 April (reopening of shops offering face masks, respirators, hand sanitizers, etc.), 9 April (reopening of hobby markets and bike stores), 20 April (reopening craft stores), 27 April (reopening stores of less than 2500 m2) and 11 May (reopening of all the stores). It means that the easing of governmental regulations did not have an immediate and direct effect on the people returning back to normal life. We can only speculate whether it was caused by the decrease of fear of the coronavirus, which has been fading gradually, rather than leaping with each release of regulations, or whether it was due to the reaction to the government’s easing of regulations being spread out in time. Regardless of these possibilities, occupancy is slowly getting back to normal and we expect to be at the same occupancy as before the pandemic in late July.
From the data, we can also observe another interesting consequence of the lock-down. When we compare only the data from the camera pointed towards the supermarket, we discover that this particular supermarket is generally slightly more visited by men than by women as, ordinarily, approximately 56% of customers are male. In consequence of the pandemic during the middle of March when the lockdown was implemented, the ratio started to drift. Since mid-March until mid-May, 39% of customers were male.
In the Czech Republic, the government agreed on implementing special shopping hours for senior citizens to lower the possibility of contagion of COVID-19. Every day, all supermarkets had to reserve 2 fixed hours established by the government for shopping only for people older than 65 years. Data from the particular supermarket shows only little impact of older people making use of the reserved hours. The data also confirms the ignorance on the part of younger people who did not respect the reserved shopping hours. Furthermore, it took about one week for the people to get used to the times. The government’s changing the issued time thrice also played an important role in the length of the adaptation.
In the Czech Republic, the government agreed on implementing special shopping hours for senior citizens to lower the possibility of contagion of COVID-19. Every day, all supermarkets had to reserve 2 fixed hours established by the government for shopping only for people older than 65 years.
Data from the particular supermarket shows only little impact of older people making use of the reserved hours. The data also confirms the ignorance on the part of younger people who did not respect the reserved shopping hours. Furthermore, it took about one week for the people to get used to the times. The government’s changing the issued time thrice also played an important role in the length of the adaptation.