Updated: Apr 28
Written by Olivia Klayman, Marketing & Corporate Communications Analyst at Systech
To the dismay of many who are of the belief that money is the root of all evil, money makes the world go ‘round. As data availability and its demand continues to increase exponentially, it’s more important than ever to capitalize on data monetization opportunities. These are Systech Solutions’ top four picks of industries that should take advantage of this boom!
Healthcare. Data is an essential component of the healthcare field. Whether it be lab results or general patient information, data touches this industry in every respect, and it would be an opportunity wasted to not derive insights and further explore the ability to monetize it. Profiting from healthcare data vastly supersedes appointment confirmation, automated outpatient updates and virtual consultations. 23andMe, for example, publicly announced a partnership with GlaxoSmithKline (HFMA). In exchange for a $300M investment, 23andMe will deliver generic information on all 5 millions of their customers that GSK will then be able to accelerate treatments and cures for (HFMA). While this prompts a series of questions like, “who should financially profit off health-centric data? The corporation or individual?” there are other examples that are a no-brainer. Customers, for example, can now leverage data to get lower premiums for life insurance. As a result of the monetization of healthcare, data on illnesses like diabetes could be bolstered to track compliance to personalized regimens for all patients, alike. Healthcare data monetization has more pros than cons in the near future.
Automotive. According to a 2020 McKinsey & Company study, “37% of consumers would switch to car brands that offered enhanced connectivity” (McKinsey & Company). In fact, they also discovered the “overall revenue pool from car data monetization, at a global scale, could total $450 — $750 billion by 2030” (Intellias). The applications of automotive data are endless. They could analyze data geolocation, vehicle popularity, vehicle performance, machine operation troubleshooting, driver behavior, biometrics data, and more (Deloitte). In December 2020, Blackberry and Amazon curated and executed a “cloud-based software platform designed to help automakers and suppliers standardize vehicle data and speed deployment of new revenue-generating features and services” (Reuters). This intelligent vehicle data platform — “IVY” — is said to have been designed to “compress the time to build, deploy and monetize in-vehicle applications and connected services across multiple brands and models, making it easier for automakers to collaborate with a wider pool of developers to accelerate development of apps and services” in over 175 million vehicles, internationally (Reuters). While “IVY” is a few years away from becoming a standard platform across the auto industry, it serves as one of many examples to come where data monetization has joined forces with the ingenuity and innovation of this world’s thinkers, financers, and action-takers.
Retail. Retail has experienced an unprecedented data boom in recent years. Take Warby Parker, for example. Warby Parker — a household staple over the course of the last ten years, or so — is often applauded for the way they disrupted the prescription eyewear industry. With offerings such as their “Home Try-On Program,” and unmatched prices, it’s no wonder. But what does data have to do with this powerhouse? WP first identifies where their customers typically live. This helps them determine what locations they’d like to open shop, population density of prospective clients, and the current sales of competitors nearby (DEVTRIBE). WP keeps track of their own customer behavior data, as well as their proprietary statistical model (DEVTRIBE). They are even bold enough to purchase cell carrier data in order to track movement, considering that many don’t live where they buy (DEVTRIBE). In every capacity, WP is a data-driven organization, connecting to their customers in every physical and virtual capacity available today. Foursquare is also making headway with all their data endeavors. A self-proclaimed location technology company, Foursquare has recently announced its collaboration with several companies on pilot program “to deploy the extensive data in Foursquare’s arsenal — including foot traffic by time of day and demographic info from more than 140 countries — on a real-time basis” (DEVTRIBE). This means that Top hedge funds, for example, may be able to predict publicly traded company earnings, with a newfound ability to process it. Instacart is another prime example of an organization that uses data science to address business problems. With half of American households utilizing Instacart to get food from their favorite grocery stores like Costco and Whole Foods, the next logical step would be to inquire about where all their data goes (Towards). Instacart makes money from delivery fees, sure, but a sizeable portion of revenue comes from the stores that Instacart boosts traffic to, incidentally about 30% of all Instacart purchases go to advertised products (Towards). While it’s obvious that this serves as a rich resource for data science purposes, it’s impressive to note the diverse data applications for a four-sided marketplace, with a platform that serves and learns from customers, shoppers, stores, and product advertisers alike (Towards). They’re able to gain invaluable insights on customer behavior, such as the impact of weather, demand of certain products, delivery fulfillment times, and customer mapping routes. With half of the nation’s dated accounted for in some capacity, it goes without saying that the future of data science within retail are far from realized. Companies like Warby Parker and Instacart are championing the data mining and science efforts for all future data-driven platforms and companies to come.
Music. Music touches every element of pop culture, even in ways you may not have noticed. Whether it be a TV jingle, a radio hit, the soundtrack of your favorite show, it has already infiltrated every aspect of life. The way that money changes hands in the industry is completely different from the Motown days. For both businessmen and artists, music is a numbers game. There are the more obvious ways to make money in music — like merchandise and ticket sales — and the more nuanced streams of revenue like TV & Film Syndication placement. From a talent perspective, large record companies no longer invest money to develop talent. Instead, social media and streaming stats are a larger contributing of whether someone is signed or not. In fact, streaming revenue in the USA, “continues to grow at 30% per year, [with] the growth of new artists and content is significantly higher [with] over 14.6 million new tracks upload to Spotify every year” (Medium). On the flip side, the advent of data metrics may be conducive to the creation of an equal playing field for both independent and signed artists. Data monetization will also impact areas of the industry like the democratization of music creation, increase artist ad revenue, machine learning, the crossover between gaming and music, and increased exposure from Tik Tok (Soundcharts). The possibilities of data in the music industry are endless.
In many ways, a clear knowledge of “data” parallels that of “DNA” and the scientific community. There is so much value and information that can be squeezed from an intricate understanding and application of both, alike. The investigation of both fields is profitable, sure, but data analytics will continue to shape our everyday reality more and more so as the days go on.
Healthcare, the automotive industry, retail, and music are four industries that could tremendously benefit from the monetization of their data. Every day they go without doing so is at their own detriment.
The Systech Solutions, Inc. Blog Series is designed to showcase ongoing innovations in the data and analytics space. If you have any suggestions for an upcoming article, or would like to volunteer to be interviewed, please contact Olivia Klayman at email@example.com.