Adapting to Covid-19 Using Location Data
I recently returned from hospital in Singapore where I was a suspected coronavirus case. After multiple tests including CT scans, I thankfully came back negative (turns out I had pneumonia all along). The whole experience was awe-inspiring both in the efficiency, organization, and professionalism of the Singapore healthcare system and the amount of work each and every nurse and doctor had to go through to treat their patients.
Each time a nurse visited me they had to go through an ‘airlock’ type of room and put on all their protective clothing. Once they left, they had to remove their clothing and thoroughly disinfect themselves — a time-intensive process all for a two-minute visit! The burden on healthcare systems across the world is clearly massive.
My personal experience getting sick during the pandemic also got me thinking about how easy it is to spread the virus just by moving around and how important it is to abide by government guidance to stay at home or at least limit your movements. As someone who works in the location data industry, I have an appreciation for the mass movement of people, and staying at home and limiting contact with other people is the right thing to do right now.
I also had the chance to think about how location data could be used to help hospitals, governments, and businesses combat the spread of the virus.
Offline to online
We know restaurants and retailers are suffering at the moment as Main Street empties out. However, there are also opportunities, and we will see many firms and entrepreneurs be able to adapt, especially given that behavioral changes brought on by the virus are likely to continue once this pandemic is over.
Take food and beverages as an example, one of the industries that has been most affected. While no one is physically going to a restaurant, home delivery services are booming, and smart restaurants can use location data to increase their online take-out sales.
Consider an Italian restaurant that wants to send targeted advertisements to boost take-out sales. The restaurant’s first priority would be to reach out to existing customers, but thanks to location data, they could also reach out to other customers, such as people who have eaten at other Italian restaurants that are currently closed and not offering delivery.
Using historical location data, we can identify consumers who have visited an Italian restaurant, say, twice a month over the past six months. It would be safe to infer that these people are fans of Italian food and so would be receptive to ads promoting take-out pizza. The restaurant would now have the ability to send targeted advertisements to these users. Not only can the restaurant drive more online sales this way (we know that ads targeted in this way can garner up to an 11% conversion rate), but they can also increase their customer base, adding loyal customers who would hopefully stay with them after the crisis is over.
This same method could apply across industries. SaaS companies can target those who traditionally work in office parks, home exercise companies like Zwift can target those who go biking or to gyms, and ecommerce companies like home grocery delivery firms can target those who usually make visits to the grocery store. Although many B2C companies are facing a huge hit, there are still opportunities to gain customers and market share during these times.
Predicting the next outbreak using AI
Unlike after the spanish flu pandemic or even SARS, today we are generating masses of data that we can pump into artificial intelligence algorithms that could help forestall or even prevent another pandemic of this kind. This data includes everything from medical information and online behavior to social media and location data based on users’ movements before, during, and after the pandemic.
Location data can be used in combination with other types of data to uncover previously unknown insights. For example, we know that the severity of Covid-19 in part depends on viral load and dosage. Marrying medical data (such as chest x-ray results) with location data, we may be able to uncover hotspots where people contract the virus more seriously.
By studying the movements of people in the lead-up to this pandemic ,we can generate a much better understanding of how the virus has spread, where it came from, and through which channels. Social media activity combined with location data could help predict a panic buying spree in the initial stages of an outbreak, helping local governments prepare and retailers stock up.
The benefit that AI brings is that it can bring together disparate sources of data and information and make sense of it, identifying patterns that would otherwise take much longer to uncover. Following this epidemic, there will be a wealth of data that we can use to both analyze our own responses and also better prepare for the next virus, which will inevitably come.
Fighting the virus today and tomorrow
This is not the first pandemic, and it won’t be the last. One thing for certain is the effects of this one will fundamentally alter how our economy operates for decades ahead.
Businesses and organizations need to understand these changes and capitalize on this new reality. With each pandemic, the hope is that we can learn, better protect our citizens, and enable businesses and citizens’ lives not to be devastated during these times.
Mike Davie is CEO of Quadrant.
