How Emerging Industries are Using Big Data to their Advantage

Its exciting to watch a new industry figure out ways to use big data. There are so many ways different industries put data to work for them and for their audience. For example, Google is using RankBrain to determine search results.

This is exciting because its a very real example of Artificial Intelligence employing data to affect what you see in front of you every day. Go ahead, try typing an unusual query into Google. RankBrain will help determine the result based on similar and unconnected searches, your own searches, and the data generated by clicks in those searches, and it will do this in real-time.

In other words, machine learning will use big data to personalize the result of each search for you. And in the world of Google updates and SEO, the mysterious, exciting thing is that there was an Unnamed Major Update in May. Was that change a full-scale takeover by AI? We wont know until theres an announcement.

So Google is something of a juggernaut and a pioneer in the big data world. Internet giants like Google were at the forefront of Big Datas emergence to the public eye in 2010, which has ushered in Analytics 3.0. This is a time in which Big Data yields predictive and prescriptive insights, and helps businesses make both internal and external decisions.   

In the Big Data 3.0 era, there are emerging industries that understand the importance of data as a tool and are using it to get, or expand, their foothold. Lets take a look at some exciting cases.

Legal Cannabis Industry

As youre doubtlessly aware, theres a legal cannabis business going on in multiple states. And its huge. Recreational marijuana sales are averaging $123 million monthly, with a projected gross intake of $1.5 billion for 2016. In Washington, sales were slow at the beginning of 2016, but have grown about 5 percent a month since then.

Startups in the marijuana industry arent just operating in the short-term, with a view dominated by state legalization. Theyre looking forward with data-based decisions.

Wholesale company Cannabese is partnering with several software firms to automate the wholesale business. The partnership is also intended to create a network connecting buyers and sellers nationwide. Once marijuana is legalized at the federal level, the network can be quickly and compliantly united, says Amy Poinsett, co-founder and CEO of MJ Freeway.

According to Marijuana Business Daily, MJFreeway and BioTrackTHC are software solutions for tracking and gathering data on the seed-to-sale pipeline. Their partnership with Cannabese will harness data to:

• Improve transactions using data in real-time
• Improve product and price transparency
• Improve the supply and sales network

These types of improvements are what almost any business can look to do with data as the possibilities continue to unfold. In terms of inventory management, POS systems offer analytics, and can send you alerts when youre running low on something. Over the long-term, data analytics are fantastic for tracking trends and determining which of your offerings need more marketing or an overhaul.  

Fantasy Sports

According to Washington State University, the $1.4 billion fantasy sports industry is expected to grow more than 7 percent a year to $2 billion by 2020. Fantasy sports betting now has an all new level of complexity and realism to it, thanks to Big Data and digital platforms such as FanDuel, DraftKings, and Oulala.

Simply put, FS players have a great deal of statistical information on players at their fingertips, and that information is constantly updated as games progress. The amount of insight available allows FS players who are highly skilled to predict a winning lineup with high accuracy. Moreover, the live-coaching feature mimics a real coaching experience through advanced data tracking and transmission, so that FS players can make on-the-fly changes to their lineup and formations based on real-time data.       

FS platforms such as Oulala, which takes 70 different statistics into account when delivering insights, are   a great example of predictive analytics at work. That is, data analysis comes in an informative package that helps FS players predict the outcome of events. Similarly, CRM helps businesses make decisions based on analysis of customer data, which help you decide your next step when it comes to marketing and sales.     

Sharing Economy Services

Uber, AirBnB, TaskRabbitall operate on a data-sharing model. According to Forbes contributor H.O. Maycotte, Data underlies the capacity calculations, social media integrations and digital technology interactions that together make on-demand access to things possible. For example, Uber uses a constant stream of driver-location data to determine which ride to connect you with. To turn a larger profit, it uses data on peak use times to adjust prices.

AirBnB is able to provide recommendations on vacation rentals from a huge database of properties. The program uses an advanced algorithm to sort through listings based on criteria you provide. Further, it tracks hotel prices algorithmically. This feature ensures that AirBnB listings will beat or compete with the cost of a comparable hotel room in a given location.

There are tons of sharing apps emerging as we speak. Theyre giving away data that is provided by users, using it to create value for the user. Yes, for Uber and AirBnB the ride or the room are the service. But in a sense data delivery is the service. A digital platform serves as an access point to a physical service. The platform makes the service available through data analytics. All-in-all, the person who uses the service and the person who provides it both get value through sharing their data on a platform.

Your business can also do this by creating an app that makes data-sharing valuable. To do so, use analytics to find out where supply is low and demand high. Then, create an app that facilitates sharing, and refresh data consistently, so that users are getting an updated and fast experience.