For the past year, more of life moved online—and so did brands, businesses, schools, and even government services. This created huge amounts of unstructured data from transactions, customer service inquiries, deliveries, video calls, and web traffic.

That data didn’t sit idle, though. Unstructured data became a currency of COVID-era business and will continue to be as we move forward and embrace digital transformation. You could say the circumstances of the last year kick-started the unstructured data revolution, and forward-thinking organizations will be the ones using it to their advantage to develop new products and experiences.

Here are six examples of how industries and organizations grew and innovated with unstructured data in the past year:

1) We Listened to (and Understood) Users Better Than Ever

Consumer companies often rely on qualitative consumer research to create new products and campaigns. When the last year made research through in-person focus groups or mystery shopping activities impossible, qualitative surveys and analytics that harnessed online chatter to gain insights were the advantage.

Consumers share their opinion on the products they use through social media and other online forums. Traditionally, very little of this data—besides quantifiable metrics like shares and likes—has been fully utilized. But thanks to improvements in unstructured data processing, companies are better able to tap into insights from the unstructured data contained in the content of social media posts.

Tools like sentiment analysis, for instance, help companies learn from consumers, create highly targeted messages, and understand how to reach consumers at the right place and time or alleviate grievances when something goes wrong. This was prevalent before, but became a critical capability in the last year.

Take meal delivery apps, for example, the top four of which doubled their combined revenue during shelter-in-place restrictions. Say a meal is ordered but never arrives. A customer may post online about her experience, and sentiment analysis can help to pinpoint that post and alert someone at the company to address the issue immediately. This improved continuity and issue resolution when demands were spiking.

2) We Improved Healthcare Systems

Unstructured data abounds in the healthcare industry, from doctor dictation to X-ray images to nursing notes to notes in the EHR about patient complaints, such as “my leg hurts.” This data can provide a wealth of insights that help caregivers deliver a higher quality of care to more people. Now more than ever, these are critical improvements, particularly to support the rise of telemedicine.

Parsing this complex data requires machine learning (ML) and other tools such as text mining and natural language processing (NLP), which enable computers to process and analyze data such as patient notes, uncover contextual layers, and extract insights for better decision making overall.

ML’s ability to rapidly dig through and analyze huge volumes of data helps healthcare organizations to identify and address anomalies and outliers more quickly. It empowers caregivers to respond immediately to care gaps and work on prevention, instead of only being able to provide care once a patient’s illness has gotten worse.

Using unstructured data more effectively in healthcare can lead not only to better patient outcomes, it can also streamline determination of insurance eligibility processes, make reimbursement reviews more accurate, and identify good candidates for clinical trials. It is also enabling modern approaches to healthcare such as predictive and precision medicines. In The AI in Healthcare Leadership Survey 2020, respondents said improving care is AI’s greatest benefit. Leaders said AI is helping to “highlight key findings from the depths of the EMR, identify declines in patient conditions earlier and improve chronic disease management. Cancer, heart disease and stroke are the disease states survey respondents see AI holding the greatest promise—the 2nd, 1st and 5th leading killer of Americans.”

3) We Streamlined How News and Information Was Shared with the World

For media organizations, unstructured data–in the form of articles, photos, videos, audio files, and more–is their business. And in 2020, as a global pandemic stalled the engines of industry and racial protests raged from coast to coast, more people were glued to the news than ever before.

As early as mid-March 2020, news page views were up 30% from the previous year. The amount of time people spent scrolling, reading, and clicking through articles was also up by 30%¹.

Even traditional television news had a record-breaking year. Fox News had its “most watched month ever” in February 2020–then broke that record in March and five more times by October. CNN and MSNBC also celebrated their “best month ever” over and over again throughout the year².

With a thirsty audience eager to consume ever-increasing volumes of information, media organizations used unstructured data to deliver the news in more targeted, effective ways. Artificial intelligence and machine learning helped improve how these organizations generate, produce, publish, and share information.

For example, AI systems are good at identifying the structure of real news content. They can quickly confirm information by finding additional sources and pinpoint patterns of misinformation to flag articles as potential fake news–which came in very handy for many reasons in 2020. News aggregator companies can employ “truth-checking links and sources” and rate news stories with a score to gauge the likelihood of being legitimate³.

Unstructured data can also help media organizations attract and expand their audiences. Consider TownNews, a content management platform that helps media organizations deliver the news and gain viewers while staying profitable. The platform processes and analyzes tens of billions of unstructured data points to deliver the insights that drive media to make well-informed decisions about their audiences and the types of news that keep them coming back.

4) We Made Remote Work (and School) a Reality

Internet traffic spiked during COVID lockdowns, as employees rapidly shifted to work-from-home environments4. The challenge for SaaS platforms serving enterprise customers was making data transfer efficient and maintaining the quality of their services, given the congested bandwidth.

This was especially true for video conferencing applications like Zoom, which saw dramatic increases in their user bases early on. Supporting this excess demand was made possible, in part, by the analysis of troves of data that helped providers make the best use of the bandwidth available.

These platforms’ adoption of data analysis improved worker mobility in other ways as well. Live monitoring of unstructured data from video feeds, for example, enabled Zoom to implement features like attendee attention tracking to allay employers’ fears amid an unprecedented workplace shift5.

Take Deakin University—with 60,000 students, 25% of whom attend classes online. They leveraged data to enhance and expand services. As part of a sweeping digital transformation, the university created a high-performance platform for new AI-powered apps, including a virtual assistant to help students manage their schedules.

5) We Learned to be Ready for the Unexpected

From the collection of raw materials to delivering the final product to consumers, supply chains can be long and notoriously complex. The last year put a major strain on global supply chains, which kept many industries on their toes. The Suez canal blockage, for example, proved how critical—and vulnerable—the global supply chain can be.

Organizations leveraging advanced analytics have a clear advantage over those that don’t. With robust forecasting models in place, companies can head off gridlock or other problems before they arise. It’s also easier to know when to pivot according to changing conditions, support strategic planning, and adjust procurement processes and vendors to quickly respond to global supply shortages.

6) We Put More Emphasis On Protecting Our Data

While this item is less of a growth initiative and more about prevention, there’s no ignoring the importance of data protection these days. Nothing cuts growth off at the knees like a malicious breach, and today’s hackers are definitely organized networks who are doing their homework.

Cybercrime increases every year, but during 2020 it increased by a shocking 600%. Many of the culprits capitalized on pandemic fears by posing as representatives from the Centers for Disease Control and Prevention (CDC) and World Health Organization (WHO)6. As an example, ransomware incidents also skyrocketed in 2020–some experts estimate it increased by 500%7.

Part of what leaves organizations so vulnerable to ransomware is the failure to adequately protect their unstructured data. It turns out that unstructured data8 is pretty easy for hackers to locate and encrypt. It’s critical that organizations: a) know where that unstructured data resides in their systems, b) delete data they don’t need, and c) make sure they strictly control who can access or modify it.

Harness the Power of Unstructured Data – and Thrive

While 2020 is now in the past, we’ll likely never return to what we considered business as usual in 2019. We’re smarter now about a lot of things, and the new normal in business is more focused on remote work, streamlined processes, and forging cautiously ahead to digital transformation.

How organizations use their unstructured data will be a critical element going forward and could be the difference between surviving and thriving in this new age of awareness. By harnessing the power of that data, organizations can gain an edge among competitors in satisfying customers and delivering the personalized experiences they demand today. Organizations can also work and collaborate more effectively, leading to ultimate growth and success for a long time to come.