As marketers (and data nerds), we’ve been looking for some insight into how consumer behaviors have changed over the last several weeks.
PlaceIQ, a leading data and technology company that focuses on location-based insights as an integral part of business and marketing decisions, has provided an invaluable resource with their weekly COVID-19 U.S. Social Distance Tracker.
The COVID-19 U.S. Social Distance Tracker aggregates anonymized location tracking data from mobile devices to identify large-scale behavior trends to better observe changes in consumer behaviors based on foot traffic.
The end results are weekly reports that highlight movement-trends across retail, restaurants, travel & entertainment, auto dealerships, and other interesting findings. These generally reflect summary trends of foot traffic across each category and never display absolute visit numbers.
To better understand the report, we sat down with Drew Breunig, EVP at PlaceIQ.
Q: Before we dig into the report, let’s start with an explanation of what PlaceIQ does.
PlaceIQ’s software is able to derive human behavior out of location data. Analyzing streams of latitude and longitude, we’re able to derive meaning out of it. From this, we can understand what users are doing and their intent and then turn this into something usable for businesses in a way that’s privacy-safe.
Q: I’ve been following the weekly updates from PlaceIQ’s U.S. Social Distance Tracker. Can you explain what is included in the report?
To start, when things started happening, we recognized that PlaceIQ had data about how COVID-19 was impacting people’s movement. We wanted to focus on creating heartbeat reports with a constant stream of “news you can use.” But, as we set out on this analysis, there were things we wanted to avoid, such as creating dangerous data models by people playing epidemiology through predicting trends.
PlaceIQ’s U.S. Social Distance Tracker looks at trends in foot traffic in an aggregate to understand consumer behaviors within major categories like travel, retail, restaurants, and essential locations. From this data, we wanted to provide quick snapshots of how consumer behavior is adjusting over time during the COVID-19 pandemic.
Q: What were some categories that are included in the report? And how did foot traffic trend over the last several weeks?
We have been tracking all major categories and understanding consumer behaviors. Over the last couple of weeks, grocery stores, big box retailers, and pharmacies now see customers taking fewer trips, less often. These trips take longer, but much of that time is spent waiting: well-spaced lines emanate from grocery store doors as customers are metered and cars idle in pharmacy drive-throughs. With less shopping, but bigger baskets, consumers are taking more time to carefully plan their lists. Marketers should adjust their messaging and campaign timing to account for this shift, and pay attention to regional foot traffic. Traffic is up slightly while maintaining its new weekly rhythm.
In the Travel and Entertainment category, Hotel traffic has been interesting because you’d think it would be near zero. Discount hotels are not nearly as impacted because trucking and cross-country travel is still happening.
When we look at each of these, the regional breakdowns haven’t been interesting–even though the stay at home orders state-wide were staggered, once people realized it was real movement, activity halted around the same time for the entire country. The data shows the last month of foot traffic neatly divides into two phases:
- COVID-19 becomes real for many on 3/11, when the NBA suspends its season and we learn Tom & Rita Hanks are ill.
- Traffic to big box & grocery spikes as people prepare for the possibility of sheltering-in-place.
- Airport traffic hits 20% over its average as people scramble home.
- Large offices announce work-from-home policies ahead of official state orders.
- On 3/20, California is the first state to announce shelter-in-place orders.
- Traffic to big box and grocery falls below average on 3/19, and hits lows on 3/21 as the surge to stock-up completes.
Q: The trends with casual restaurants have been the most interesting to me. The shift in consumer movement has had differing impacts on each subcategory in the dining sector. Can you explain what the data is telling us?
Restaurants are interesting. Overnight, restaurants were forced to turn into a drive-through. Three things determined their success:
- Operationally– Do they have the supplies, menus, and cooks to support a drive-through? A month in, we started to see significant changes to larger brands because it took longer for them to respond. Local restaurants, on the other hand, can move quicker on changes and were faster to adapt.
- Routine & Habit– When you think of takeout, you think of pizza, McDonald’s, KFC, maybe chipotle. Now, restaurants have to re-educate people to think of their place as a drive-through.
- Reliance on Office Lunches– Lots of fast-casual restaurants are located on the bottom floor of office buildings, but nobody is going to work. Restaurants relying on office lunches have to go much further to adapt.
Q: From your point of view, what is the benefit for marketers to have this type of information?
Marketers will need to leverage data to make smarter decisions around their strategy. Everyone needs to look at how they can make their marketing more efficient because it’s crowded right now, and there are three ways marketers can address this:
- Where is behavior going away from it, and where are they going towards? For beauty–you want to have a better partnership with Walgreens because Ulta is closed.
- How are visits changing? Consumers used to grocery shop two times per week, and now they’re buying more once every two weeks and combining delivery with in-store visits.
- Where to invest and where not to invest? For restaurant brands, they will need to look to leverage location-based targeting to shift their story from talking about the kind of ingredients they use to educating people about takeout and delivery options.
Q: Any final thoughts?
It feels like we are on the floor right now. The first 10-15 days of this were sobering, and the routine of the workplace was broken. It’s encouraging to see us figure out the shelter in place and people working to keep business afloat. I want this creativity to keep happening as we move forward. We’re in interesting times, and I hope everyone stays safe.
We aren’t epidemiologists, but we have made our data available to UC Berkeley, Penn, and Yale. One of our goals for the social distancing tracker is to stay in our lane and provide #dataforgood to the experts who can unlock it for public benefit. Before COVID-19, PlaceIQ used location intelligence to understand consumer behavior. After COVID-19, we aim to fulfill the same role. While we do have PhDs in our company that work on our data, none of us are experts in public health or disease transmission. Therefore, you’ll notice our purposeful intention to not add to the noise on social media, make public appearances, or “point fingers.”
In recognizing the value our data can provide to the actual epidemiologists, public health officials, and economists thinking about how to best deal with COVID-19, we’ve taken the step to provide our data to a team composed of numerous universities well suited to preparing, documenting, and presenting it to the wider research community in a privacy-safe manner.
If you’d like to learn more about this, or download the data yourself, take a look at the team’s public Github repository available for all researchers to use.
Drew Breunig leads business application efforts at PlaceIQ, mapping client needs and goals to PlaceIQ’s audience, data and analytics products. Drew aims to make advertising and customer intelligence more effective, insightful and manageable through the use of local intelligence.
Drew joined PlaceIQ after spending the better part of a decade crafting brand and media strategies for advertising agencies and their clients, including HP, Glaxo Smith Klein, EA and Boost Mobile.