2020 Changed Our Approach to External Data. Here's What to Expect in 2021

Share Article

The impacts of 2020 in the business world and at home—as much as these things can be separated—will continue to be felt for a long time. At Data Hunters, Eli Adry, a technical digital marketer with a passion for reducing CPA (Cost Per Acquisitions), considers strategies to adopt for the future.



Imagine waking up in the middle of the night to get a glass of water, and someone has moved all the furniture. In the same way, data professionals had a choice to make in 2020 – do they feel around and risk bumping their toes on the couch in the dark, or do they turn on the light and reassess?

At Data Hunters, we understand very well how 2020 bashing became the latest craze on TV and social media. Our Facebook, Twitter and even LinkedIn feeds are full of memes, quotes, and inspirational posts waving a happy goodbye to 2020 and happily welcoming 2021. 2020, in fact, was not a great year for the world. The COVID-19 pandemic ran wild, “stay at home” has become the most common pastime, face masks have become fashion and unemployment went to all-time highs.

It was an even stranger year for the tech world. The start of the pandemic stopped everything else. Investments were halted, corporate travel went down to zero, sales slowed down and the end of Q1 and beginning of Q2 left the business, finance, and tech world at a standstill.

Then, something extraordinary happened. Mid-pandemic, tech investments started to pick up again. IPOs continued trending and VCs ended up spending more in 2020 than they did in 2019 (according to research by CB Insights). This was mirrored within the businesses too. Even though trends shifted, and complete industries came to a halt, money was still being spent. Out went travel and retail; in went remote working tools, eCommerce, digital health and – most interestingly – data.

Setting the scene

In practice, data, and more specifically externally collected data (“alternative” or “3rd party”), is used for two major reasons.

BI (aka learning from the past) – Every aspect of the business uses external data to build charts, analyze trends, identify opportunities, and understand gaps and white spaces. Analytics platforms and BI tools offer off-the-shelf or ad hoc solutions that analyze large datasets to track anything from consumer and buyer behavior to drug use adherence or disease spread. These visualizations are used to extract insights and take actions.

Machine learning and advanced analytics (aka predicting the future) – Data scientists use data from the past in order to build complex models that help predict future behavior across a multitude of use cases.

Except – the past became irrelevant.

Imagine waking up at night and needing a glass of water. The apartment is dark, and turning on the lights will wake everyone up. So just get out of bed, walk past the living room and into the kitchen, take a glass and pour a cup. 5% vision, 95% visual memory.

Now, imagine that someone came in and rearranged the furniture and swapped the glasses and plates around. Suddenly, visual memory can't be trusted. The lights have to be turned on. With the new input, visual memory can be retrained, and sleep-walking can resume in a matter of days.

COVID-19 put the whole world of data at a crossroads. ML models instantly stopped working, and BI and analytics stopped making sense. The world changed overnight, industries collapsed against all odds and no past conclusions could have been used in an actionable way.

Large retailers, for example, have used ML models to predict sales and stock shortages based on date, time, day of week, previous purchases and many other parameters. Suddenly, their whole supply chain plan halted because we don’t know what type of stay-at-home orders are in each specific state or region, and which stores can remain open.

Turning on the lights – Broad is the new deep

What do people do when they can’t count on their memory? They make assumptions based on every bit of information you can from the present. In essence, they turn on the lights, gather as much as possible, and use the new information to navigate through the new world.

On the wings of the COVID-19 crisis, companies have began expanding their horizons to collect and acquire as much data as possible to help them make sense of the situation. Financial institutions have expanded the search for alternative data, CPG and retail companies went on a hunt for any data that will help them decide when to open and how to deliver, and governments, institutes (academia, NGOs and others) and healthcare companies started sharing and collecting as much data as possible about the virus, its spread and government and personal reaction. Companies offering alternative data types such as foot traffic, web traffic, and live company and industry data were well positioned to help the business world understand how to react, and solutions for processing, enriching and translating this data to actionability are often sought out.

What’s next

Companies that made the right investment in data starting early on in the COVID-19 Crisis will come out of it with a much broader, better, and more accurate set of data to analyze in the future. Data professionals often bemoan the state of their company's data, wishing to start over and build the whole thing from scratch. Well, COVID is the reset button, and now is the time to start rebuilding. If 2020 was spent building up company data infrastructure and pairing it with the right external data, 2021 will be successful as the world goes COVID-free. If not – it’s not too late. Data Hunters can help.

Data Hunters is an online community for data seekers, analysts, scientists, and business professionals. As big data and AI technologies grow exponentially and their implementation in various industries become increasingly mandatory, it can be hard for individuals to know which data sets or data providers to trust. Data Hunters provides a community for people to ask and answer data questions, write reviews of data vendors, and read about data categories and use cases.

Share article on social media or email:

View article via:

Pdf Print

Contact Author

Eli Adry
Visit website