Governments have enacted a variety of orders, legislation, guidelines and enforcement to get large numbers of people to stay home. We know that these measures are critical to the public health effort to contain transmission of COVID-19 and flatten the curve.
But which Americans complied with stay-home orders?
We did an analysis on population groups as it relates to going out rates during the evolution of the COVID-19 pandemic. Using our privacy-compliant mobile movement data alongside demographic, psychographic and behavioral data, we were able to capture the full picture across America.
For most Americans, the COVID-19 pandemic represents the single most disruptive event in their lives. Routines have been profoundly altered in a relatively short period, forcing all of us to adapt in ways that seemed unthinkable a few months ago.
The most profound change we have embraced is the restriction of movement in our daily lives. Business closures, stay-home advisories and social-distancing orders have all impacted how often we go out. Not surprisingly, we see different rates of compliance across the country. Our data analysis helps to understand who is complying with COVID-19 movement restrictions, who still needs to get the message and how to reach them.
We examined the movement patterns of Americans from early February to late April based on an anonymized mobile movement database.
In the first weekend in February, when COVID-19 movement restrictions were not yet in place, the country was at a normal activity level. The county-level map below shows the percentage of people who went out that weekend. People in rural areas were most likely to go out, generally traveling greater distances than urbanites to pick up groceries, go to their jobs or see family and friends. People in suburban and urban counties normally don’t travel as far or as often outside their homes.
By the third weekend in April, the national picture looked very different. With the COVID-19 crisis at its peak and firmly planted in the American psyche, the percentage of people going out along major coastal metro areas drops significantly. We saw residents of major cities like Detroit and Chicago staying home more often than others, and small town and rural America also reducing their going out rates in response to the crisis.
Americans are a diverse population in a large country. They have different demographic profiles, socio-economic circumstances, behavior patterns, attitudes and values. To capture the full picture of people across America or more importantly, the factors influencing their behavior during the COVID-19 pandemic, we used privacy-compliant demographic, behavioral and psychographic data at small geography levels to draw insights about the population. By comparing population segments that share some common characteristics but differ in their stay at home compliance, our data analysis identified three key insights that can be used to inform public outreach, program development and communications.
We looked at two Claritas PRIZM Premier® segments that are both middle-aged and live in small American cities.
22 Middleburg Managers is an upscale segment of business professionals who mostly own homes while 64 Family Thrifts is a low-income segment with people employed in the service industry who mostly rent their homes. One key difference is that many 22 Middleburg Managers residents can continue working from home or have the means to order groceries and other goods for delivery to their homes. This may account for the fact that their going out rate is 16% below the national average.
64 Family Thrifts residents are on the front line as cashiers or in the food service industry and must go out to work or venture out for food and supplies. Their going out rate is 22% above the national average. Despite their differences in movement levels, both segments share a common value around “Active Government”, a tendency to believe that government performs socially beneficial functions.
In the early days of the crisis we saw reports of spring breakers on the beaches of Florida violating social distancing guidelines. Young people became a focal point for pandemic-related containment communications. But our research indicates that urbanity and income play a larger role in going out behavior than age.
In urban areas we looked at two segments, the older 07 Money and Brains and the younger 21 The Cosmopolitans. Both are upper-class segments, with incomes above $90,000 and highly educated. The segments show 25% and 21% rates respectively that are lower than the national average for going out. They can stay in because as executives and programmers they can work from home. While they differ significantly in their use of social media, both segments watch CNBC and CNN at above the national average.
In rural areas we looked at the older segment 57 Back Country Folks and the younger segment 65 Young & Rustic. They are both low-income and predominantly high school educated. These segments respectively showed levels of going out 25% and 27% higher than the national average. This may be attributable to their lower incomes and the fact that they have no choice but to go out for their work and to get the essentials. Segment 57 Back Country Folks higher movement levels is also a concern given that they index highly for high blood pressure, one of the co-morbidities most likely to cause complications for COVID-19 patients. Both segments are fans of National Geographic and the Discovery channel, but advertising social distancing messages to these segments may not be effective given that they have to go to work to keep the lights on.
We compared two low income segments to understand the differences in going out behavior between city segments and rural segments. Both segments are middle-aged, mostly without kids living at home and with lower than average incomes. One big difference between the two segments is that 45 Urban Modern Mix has a going out rate of 2% above the national average, while 55 Red, White & Blues has a going out rate 22% above the national average. While both segments find themselves on the front line as nursing aides, plant operators, protective services and cashiers, the residents of 45 Urban Modern Mix live in denser neighborhoods with stores nearby and do not travel as far as the residents of 55 Red, White and Blue to get essentials. On the other hand, any going out behavior by 45 Urban Modern Mix is more likely to bring them into contact with more people because of their higher density neighborhoods.
We found that 45 Urban Modern Mix spend 5 or more hours per day on social networking sites at rates 48% higher than the national average. They use those sites for dating and job searches. They also like sports apps like MLS and NBA. Advertising messages encouraging people to follow social distancing guidelines through these websites might be a good way to reach them. Since they rank high on a variety of psychographics indicating concern for others and the world like “Ecological Concern”, “Global Consciousness” and “Social Responsibility”, framing messages to help others and the world is a good way to speak to this segment.
By contrast 55 Red, White and Blue are much less likely to use social media, turning to radio and television instead for entertainment. They listen to classic country stations at four times the national average. On television they are fans of the INSP network where they watch western classics like Gunsmoke and Walker Texas Ranger. Country music on CMT network is a close second favorite. Unlike 45 Urban Modern Mix, the residents of 55 Red, White and Blue index quite low on the psychographic “Global Consciousness”. They are more likely to believe in “Parochialism”, meaning they are more tied to local and national concerns, and in “Obedience to Authority”. A strong, clear message from government officials is better than ambiguous rules or guidelines.
Governments have enacted a variety of orders, legislation, guidelines and enforcement to get large numbers of people to stay home. Further improving compliance will require more nuanced strategies targeted to specific populations who cannot, or will not, stay home. To do so effectively means accessing demographics, behavioral data and psychographics to provide rapid insight into populations of interest.Americans are a diverse population in a large country. We behave, think, consume and generally act differently based on thousands of attributes, including where we live. The COVID-19 pandemic has shown this to be true when it comes to compliance with movement restrictions.
Environics Analytics has a privacy-compliant database called MobileScapes developed from aggregated mobile phone movement data from multiple sources. Using these data, we identified devices that were out of their homes during the daytime for weekends from early-February to late-April.
Claritas PRIZM® Premier segmentation system is a lifestyle segmentation system that classifies Americans into 68 segments linked to thousands of behavioral and psychographic dimensions. We used these data to find out about different population groups as it relates to going out rates during the COVID-19 pandemic.
The measure of “going out” was devices that were observed more than 300 feet, at least three times for ten minutes each in a day, from their inferred home ZIP+4; a very small area defined by the United States Postal Service to facilitate mail delivery. We chose weekend data because the largest percentage of the population would be free to choose their activities on typical non-workdays.
We aggregated the data to various geographic areas to understand the patterns at a national, state and neighborhood level. Next, we analyzed the results through the lens of the PRIZM Premier segmentation system. PRIZM Premier assigns every American ZIP+4 to one of 68 lifestyle types based on demographics, socioeconomic status, behavior and psychographics. This analysis helps identify areas where the populations may not or choose not, to take the stay-at-home orders seriously enough and provides insights into who they are and how to motivate them.
All maps and graphs Are EA generated. To learn more about the data used in the creation of this post or to ask a question about your specific situation, get in touch. We’re ready to help.