Big Data In Action Ten Case Studies That Really Matter
Big Data technology has mostly been used for solving problems unique to organizations using the internet to generate their revenue streams. The under-mentioned case studies see Big data in action, appropriately characterized by its3 V”s—velocity, variety, and volume. These big data case studies are meant to instruct readers and bring about improvements in business performance. Here is a sketch of the 10 most significant Big Data case studies doing the rounds.
1. Real-time pricing by Macy's Inc.
Can it get bigger than this in recent times? In this case, the retailer ended up adjusting its pricing in nearly-real time for more than 73 million (!) items. Mary Inc. used the technology supplied by SAS Institute and based it pricing in line with the overall demand and inventory.
2. A Fast Food Giant(?) and training cameras
A fast food company of high repute (name not divulged) is focusing its camera lenses on different drive-through lanes to determine the items that need to be displayed on the digital menu boards, with the help of fast and reliable Big Data metrics, the board display products that require lesser time to be served when the lines are longer and higher-margin ones that require elaborate preparations at other times.
3. Search Options of Wal-Mart
Walmart.com has launched its latest search engine that incorporates semantic data. The mega-retailers search platform was designed in-house and relies on machine learning, text analysis, and synonym mining for delivering accurate and user-based search results. The addition of this semantic search option has improved upon the figures of shoppers going through with their purchases till the end by about 10% to 15%. In monetary terms, this converts into billions of dollars for Wal-Mart.
4. Usage of KXEN software by Tipp24 AG
Tipp24 AG, a popular platform reputed for placing bets on various European predictions and lotteries, uses the innovative KXEN software to analyze billions of online transactions, estimate customer attributes, personalize marketing messages, and develop predictive models for targeting customers in better ways. Careful incorporation of Big Data Analytics and other relevant tools has reduced the time taken for building predictive models by almost 90 percent. Here, it’s important to note that SAP is looking towards acquiring KXEN to fill its predictive analytics gap.
5. Brand recognition and Morton's
Big Data success attributed to The Steakhouse—a popular steakhouse chain based in Chicago—goes back to the time when a customer had jokingly tweeted and requested dinner at Newark airport. As he was recognized as a frequent customer ( a retweeter) by The Steakhouse, a takeaway was promptly organized and delivered by the hands of a tuxedo-clad delivery person. This publicity stunt obviously went viral and brought in a lot more for the steak-makers. Here, the question is, are most modern-day businesses capable of achieving something like this?
6. Repurposing of PredPol Inc.
Along with an organization named PredPol and a team of educators, the police departments of Santa Cruz and Los Angeles have tweaked an algorithm used for predicting earthquakes and have fed it crime data. This interesting Big Data backed software has the potential to predict the likelihood of crimes occurring right down to 500 square feet. With this in place, in LA alone, there has been a 21 percent reduction in violent crimes and a 33 percent reduction in burglaries, specifically in those areas in which this software has been implemented.
7. Business intelligence and American Express Co.
After AmEx realized that conventional BI [business intelligence] trailing and reporting indicators were failing to take their business as far as they wished, it went Big Data’s way. AmEx started implementing sophisticated predictive models and indicators for predicting loyalty. It developed new models for analyzing historical transactions, along with 115 variables for forecasting potential churn. Now, the Company is in an enviable position to identify 24 percent of its Australian accounts that were scheduled to close in the next quarter.
8. Performance efficiency of Tesco PLC
Tesco PLC, the supermarket chain, has fed over 70 million refrigerator-centric data points linked to its units into a dedicated Big Data warehouse. The data points were further analyzed for keeping better performance controls, gauging the timeframes for the maintenance acts on machines, and implementing worthy ways of reducing energy costs.
9. Product generation by Express Scripts Holding Co.
Express Scripts, with high credence in pharmaceutical claims, started working on its realization that most patients end up delaying or forgetting to make their regular medications. So they launched automated phone calls and medicine caps that beeped to remind patients about their next dose.
10. Dark data of Infinity Property & Casualty Corp
Dark data refers to underutilized information assets that have been accumulated for a singular purpose and collected for a single purpose and then archived. Knowing that this data was capable of being mined for more reasons, Infinity developed an algorithm for the same. For instance, the Company used its amassed volumes of adjusters' reports that were worthy of analysis and correlated the same to instances of fraud. As a result of this project and all the data in its possession, it managed to reap over $12 million in diverse subrogation recoveries.
Further research with regards to these Big Data case studies will help you get deeper insights with regards to how this technology can be applied to your current situation too.
Go for Big data; go for BIG results!