Thinking about using big data to help your company grow? Its a good moveyou can improve your ROI (return on investment) in several ways by leveraging the information youll gain with big data. However, getting a big data infrastructure set up can be costly and time consuming. Most retailers want evidence that theyll benefit from this investment by looking to others who have succeeded. The good news? You dont have to look far to find retailers who have made big money from big data. Here are just a few case studies of large companies showing how powerful predictive analytics can be for business growth and trimming unnecessary spending.
1. Staples
Social media feedback is important for any business. A large corporation like Staples gets a massive amount of incoming data from different social sources, which can make it difficult to sort the relevant messages from the irrelevant. Enter big data. The company used Dells technology to implement a big data solution for social media, which cut irrelevant data down by 75%. Because they were focusing on the messages that mattered, Staples was able to improve customer communication and evaluate marketing campaigns quickly, saving money on projects that werent worth the investment.
2. Wal-Mart
For many people, its strange to think of a natural disaster as a business opportunity, but thats exactly what Wal-Mart did back in 2004, when Hurricane Frances came roaring toward the United States. Customers came to the store in droves, picking up essentials like water, flashlights, andstrawberry Pop-Tarts. Wal-Marts data analysis showed that not only were Pop-Tarts selling at about 7 times their normal rate, but the top-selling item was beer. Using this information, the stores were able to stock accordingly.
Since then, Wal-Mart has continued to leverage big data for big profits. By designing and implementing the Polaris platform, which uses text analysis and machine learning, Wal-Mart was able to use semantic search to increase online sales. Customers now complete purchases 10-15% more often, which grows company profits immensely.
3. Amazon
Amazon always has several big data projects going, and these projects have been a boon to the companys bottom line. One project focused on fraud prevention, using tools which use a scoring approach. This program reduced credit card fraud by 50% within the first 6 months, an impressive ROI for the retailer. Amazon has also used data to drive sales, using customer browsing cookies and wish lists to suggest products that customers might buy based on prior action. Finally, many customers have noticed how Amazon prices fluctuate on a regular basis. This is due to their analytic systems, which dynamically changes prices based on the market. The system scans other sites and collects data from customers who scan items in stores, using this information to make adjustments to Amazons own pricing if necessary. This occurs once every two minutes, blowing other retailers out of the water, who only change prices every few months, typically.
4. Macys
Macys also uses dynamic pricing for their 73 million items, mostly considering supply and demand.
5. Kohls
Everyone loves a deal, and Kohls decided to use big data for real-time analysis to tailor coupons to prospective shoppers. Customers who used the Kohls app and website were often sent instant coupons for their favorite departments to boost sales.
6. Target
Taking predictive analysis to a whole new level was Target, which used its baby shower registry and guest ID program to target pregnant women at different stages of their pregnancy. Using data collected from existing customers, the retailer was able to identify popular products purchased during each trimester, and recommend those products to customers the data indicated were pregnant. When the program started in 2002, Target was bringing in $44 billion. By 2010, they were making $67 billion. While not all of this growth can be attributed to one program, this case study shows just how much insight can be gained using big data.
Boosting the Bottom Line
Each of these examples show the power of big data, and the versatility of these tools in boosting the bottom line. While every retailer has different priorities, big data allows these companies to pinpoint what is most important to their business, and use data to create more efficient processes and meet customer demands. With so many successful case studies in the retail space, theres more than enough evidence to show that big data is worth the investment.
