Big data is undeniably a buzzword in the business world. It’s a lot more than jargon, though — asking the right questions of the right data can yield invaluable results. As more industries look to gather insights from the vast amounts of available data, more interesting applications of data analytics become apparent. These stories offer excellent examples of big data improving interactions in a variety of markets.
Determining Buyer Intent with Big Data
Marketing professionals have been using the building blocks of predictive analytics for a few years now. However, cookies enabling personalized ads and early online analytics have grown into comprehensive predictive analytics tools, including in-depth search, social and browser history analysis. If a person is a potential buyer the data trail they leave behind is called intent data, and 67 percent of marketers think it can give them a competitive edge, according to Forrester Research on Forbes. Using past behaviors to predict a person’s intent to buy is the latest frontier in marketing, hoping to achieve an ideal marketing feat — serving up the right product before the user even has to look. The catch? Effectively finding and using intent data is not a one man job, and requires top notch tools and a data-driven team.
Predictive Marketing Makes Better Mobile Games
Proving the strength of predictive analytics, a new predictive marketing tool from Swrve is delivering promising results to mobile game developers, according to VentureBeat. Swrve predicts the appropriate time to prompt a player with certain promotions based on their own and other users’ data. Careful targeting and analysis resulted in a 50 percent increase in revenue from players, which is crucial to the freemium model adopted by many mobile games. By using the right data to deliver the right message, predictive analytics improves engagement, which is a boon for any industry.
Big Data Takes Off for the Travel Industry
The travel industry logs more than a billion transactional data points each day between transport and lodging reservations. Now, like many industries before it, travel companies are becoming increasingly dependent on big data analytics, according to Information Age. In addition to transactional data, the travel industry can gain insights from social media, review pages and even weather patterns. By taking note of trends a travel company can devise an impromptu promotion based on a spike in destination searches or find a perfect locale for expansion. The advantages of an effective analytical model can ensure travel campaigns are well timed and go the distance.
Improving Public Health with Predictive Analytics
An inventive new tool developed by the city of Chicago lends the power of advanced analytics to the Department of Public Health, GCN reports. After deploying a tool to schedule health inspections based on tweets about food poisoning and a predictive model to cut off a growing rodent population, the department has developed another predictive model to reduce foodborne illness. The city now updates a database of calls to its 311 Service Request hotline and assorted public data, including social reviews, daily. It then determines which restaurants should take high priority appointments for inspections. Using big data to improve day-to-day life is a healthy goal, and we’d like to see more cities make smart moves like this.