In the first week of lockdown in the UK, 35% of VAYU’s citizen data scientists ran COVID-19 related datasets.
We weren’t surprised. We made VAYU accessible to all. No coding, no degree, just data science for everyone. Create data science reports in just a few clicks. Simple, intuitive and empowering.
When people started logging in and running the data, we knew right then that we’d addressed the two business challenges which often stand in the way of innovation, time and money.
Prompted by our users, we followed suit and looked at some interesting data from the food industry - a sector in an undeniable crisis.
Understandably, coronavirus is now the most talked about subject across the social media landscape. Newsfeeds and timelines are awash with trends like #MondayMotivation and #StayAtHomeSaveLives.
This messaging on social media, at least in the UK, reflects people coming to grips with a period of isolation and working from home. We’re each doing our bit by limiting the spread of the virus, trying to take this massive change in our stride, but business are suffering as a result.
Food services, like restaurants, pubs, takeaways and cafes, are among the worst hit.
We visualised a number of interesting datasets with VAYU. In minutes we were able to gauge public opinion, assess the worst hit sectors and chart the downward trends of some of the most affected companies.
With a year on year decline of 100%, OpenTable has been transparent with their data, even sharing their datasets for others to use, as well as preparedness guidelines and other tools to help businesses registered with their service to handle the inevitable downturn.
In a press release, the online restaurant reservations giant said: “As the COVID-19 pandemic keeps people home and some cities, states, and countries limit restaurant operations, our community of nearly 60,000 restaurants faces unprecedented challenges.”
We looked at two datasets – global operations and UK operations. We wanted to see if Australia, Europe or the Americas had been impacted in different ways.
Well, the data is pretty conclusive, and the correlation between the two sets is almost identical, save for one minor upturn around March 14th. This could be because, at that time, the UK sensed their own lockdown on the cards, heading out for one last meal at their favourite restaurant.
As cafes and restaurants limped on, hoping to trade for as long as possible before the eventual lockdown, people became more decisive.
Weighing up human health and business health, it quickly became obvious who or what should be prioritised.
Footfall shrunk gradually before dropping sharply, as nations began to impose tougher isolation and social distancing rules in the latter half of March.
In a snap poll, 58% of people said that they’d stop visiting restaurants and cafes, while 28% said that they planned to visit less frequently. A day later, Boris Johnson announced a mandatory lockdown in the UK.
Although government grants and assistance for businesses are slated to begin rolling out soon, it’ll be an uphill struggle to adapt and recover, and some say that the directives issued by the government came too late in the day, ultimately allowing for the spread to worsen, leaving businesses with little else to do but continue on until more concrete restrictions were announced.
Knowing what we do now, it was written in the data. The trajectories, the projections, and the trends gave some businesses and individuals the inside track - an understandable narrative from which to make strong-minded decisions.
All data tells a story, and the story it tells you can be a powerful thing. Giving your data a narrative and visualising it can inform your business to make data-driven decisions.
It could see you through a complicated challenge, reveal a truth previously hidden or help you make sense of something complex. But how do you do that when the tools themselves are just as complex?
There are many complicated data science tools out there. Too often they require a level of skill possessed only by the most educated data scientists, requiring complicated programming languages like Python and astronomical subscription fees.
To address these challenges, we made VAYU, a no-code data science platform for those out there who are curious, businesses with questions they need answering and those looking to see what story their data is telling them.
We’re opening up VAYU for a limited time only, free of charge for anyone who needs help making sense of their data. In times like these, if nothing else, one thing we can do is keep an eye on the data.
Being reactive, short sighted and eruptive is rarely the answer, especially in a time of crisis.
Instead, we must think long term, read the data, breathe and step carefully.