Florida Reopening

Walk Across the Beach or a Gym Membership – What Florida is upto Post Reopening?

Amidst lockdown, reopening, call outs and subsequent short term curfews, at large Florida is open for business. Most of the non-essential categories such as salons, gyms, restaurants, and cinemas opened their doors for the residents of Florida

In an effort to sail through the current pandemic, Florida residents have come together to restrict crowding across all the counties and categories of places they earlier loved to visit. In ‘the new normal’ the way they sustain their livelihood and consume both commodities and services has taken a turn. With such a drastic change in consumers’ journey, what can be the path ahead for businesses? 

To understand the pre and post-lockdown trend, we studied the visitation pattern and demography of consumers across 3 counties – Miami-Dade, Broward County, and Palm Beach – between June 1st and June 30th 2020. Later, contrasted it with their pre-lockdown behavior from March 1st and March 15th 2020.

We also explored the density index in various places of interest and analyzed the visitation patterns across different counties.

Let’s bring in the data.

Work and work-out take the front seat

Post reopening, average density dropped across all the categories with almost 50% less footfall when compared to pre-lockdown phase.

%age Change in Average Density by Category

The graph shows the change in average density across various categories on an aggregate level during the pre and post-lockdown phase.

  • Places of worship and cinemas witnessed a significant drop in the density index indicating that the residents chose to restrict their movement by compromising on communal and recreational activities. As further relaxation on outdoor activities comes into play, leisure venues may start to revive.
  • In spite of the restriction that only outdoor dining was permitted, restaurants saw a decent footfall with only a drop of 51% in average density.  
  • Average density at places of worship saw a sharp decline with a drop of 59%.
  • Florida residents remain committed to a healthy lifestyle which thereby contributed to the least decrease of 47% in average density at gyms.

Now let’s look at county-wise distribution across these categories:

Density Index – Pre-Lockdown

Density Index – Post- Reopening

The graph shows the county-wise change in average density across various categories during the pre and post-lockdown phase.

  • Miami maintained the highest density index out of three counties in restaurants, gyms, cinemas and places of worship. This trend was consistent with its pre-lockdown phase.
  • Palm beach had the highest density index for corporate offices during both pre and post-lockdown phase.
  • Similarly, Broward County maintained the highest density when it came to public transport.
  • Except for Palm Beach, both Broward County and Miami-Dade experienced the highest density in the public transport category during both the pre-lockdown and post-reopening phase. 

Although in absolute sense there’s a massive decline in average density when compared to the pre-lockdown phase, however, when seen in comparison to other categories public transport is going to be the most crowded area for Broward County and Miami-Dade.

% Change in Average Density by County

The graph depicts countywise percentage change in average density.

  • The average density across all counties reduced to almost half of their pre lockdown density with Miami-Dade experiencing the highest drop of 54%.
  • Broward county experienced the least change in average density and that was by 42%.  

Gen-X and Baby Boomers are stepping out more

We also looked at specific age groups, to observe the shift in their consumer behavior during both the periods.

Breakup by Age Group Pre Lockdown

Breakup by Age Group after Reopening

The graph shows the age-wise change in average density across various categories during the pre and post-lockdown phase.

  • During the pre-lockdown phase, footfalls at restaurants, gyms, and offices were driven by 25-34 year-olds. However, after reopening the trend shifted towards 45+ as they frequented observed categories more often than the other age groups.
  • After reopening, Millennials and Gen Z are social distancing more by avoiding public places.
  • In the pre-lockdown phase, 45 + year-olds preferred to use public transport the most, however, after reopening they were seen mostly visiting corporate offices.

Given Gen X and Boomers are more susceptible to imminent danger of contracting Covid-19, they can increase their efforts when it comes to social distancing.

Neighbourhood is the place to go

At large, the residents are restricting their movement and are more likely to travel less than 5 miles for availing both essentials and recreational facilities.

Break Up by Distance Travelled Before Lockdown

Break Up by Distance Travelled Post Reopening

The graph shows the break up based on distance travelled for various categories during the pre and post-lockdown phase.

  • The percentage change in visitors at gyms, restaurants, and grocery stores travelling 3-5 miles experienced the highest increase after reopening by 39%, 22%, and 26% respectively. This increase came at the expense of folks who were earlier willing to go the extra miles for these categories.
  • After reopening, people preferred to travel less than 3 miles for places of worship, offices, public transport, and cinemas.
  • Visits to hair salons became more localised as people were more likely to travel either less than 3 miles or  3-5 miles to avail their services.

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, please 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 reuse 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.