- Higher visitation from women aged above 45 years across place categories, whereas Millennials and Gen-Z avoided stepping out.
- Visitation at entertainment, recreation places and hair salons were similar to before the stay-at-home order.
In an effort to reboot the economy, Georgia’s Governor reopened the state for business from April 24. The order detailed relaxations in business operations and opening of non-essential businesses such as hair salons, gyms, bowling alleys, dine-in restaurants, and nail care artists, among others.
Businesses can’t help but wonder whether the pandemic has onset a radical behavioral shift or will consumers go back to their old patterns? What is the first place or activity that consumers will visit/do post the relaxation of the stay-at-home order?
To better understand the trend, we studied the weekly visitation pattern and demography of consumers seen at malls, hairdressers/salons, restaurants, and entertainment/recreation locations from March 1 to April 30. We also analyzed the Density Index which measures crowding at places during busy hours to see whether social distancing continues to be of consequence.
Let’s take a look at what the data revealed.
Humans are truly social beings
- Entertainment and recreation places experienced a Density Index of 5.29 which is ~83% of the crowding seen before the issuing of the stay-at-home order. Similarly, personal care services experienced a Density Index which is ~75% of the Density Index seen before the stay-at-home order.
- Malls experienced a significant decrease in the Density Index indicating that the general population avoided malls as they have a higher propensity to get crowded. It may take a couple of weeks for malls to experience comparable visitation as was seen in the pre-COVID period.
Crowding at place categories shows a necessity to strictly follow the social distancing norms.
We also analyzed the daily visitation across place categories. This can help businesses understand what consumers may choose to do within the first few days of reopening.
- A majority of the non-essential businesses witnessed a higher daily footfall within a day of its reopening, with restaurants witnessing 45% of its total footfall in the first 24 hours.
- Data showed that footfall at entertainment and recreation places was equally spread across the period. These businesses can expect a steady footfall in the coming days as well.
People seem to be looking for ways to unwind and recover from the distress caused by COVID-19.
Older people were highly active post the relaxation
- People aged 45 years and above were predominantly seen across these place categories. This age group was majorly seen at restaurants compared to the other places.
- Older Millennials between the ages of 26 and 35 years were seen visiting hairdressers/salons and avoided other place categories, especially malls. As these locations are not regularly frequented by the same individuals, in the coming weeks we can expect an overall decrease in the footfall contribution from this age group.
- Gen-Z was seen visiting entertainment and recreational places.
Gen-X and Boomers have been identified to be more susceptible to COVID-19, therefore, it is important for this age-group to continue practicing social distancing.
Women step out more than men
- The majority of the audience stepping out after the reopening of businesses were women.
- Hairdressers/salons and malls had the highest visitation from a female audience – 86% and 62% respectively.
Understanding whether this behavior is an immediate effect of the stay-at-home order or a long-term one is yet to be determined. Studying these visitation trends over longer periods of time can help brands stay relevant and plan for the future.
In case you missed our global analyses on the changing behavior of people in the real-world amid COVID-19, download it here.
Disclaimer: The data is used to measure the impact on businesses and consumer behavior and is not an explanation for the infection rates. If you choose to re-use our analysis, please contextualize it and attribute the content to Near. Near’s data platform is privacy-by-design and the data is gathered from real-world signals in an anonymized and aggregated form.