Why Retailers Have It Easier When It Comes To Big Data
When executives think about Big Data, they usually think about predicting the future while relying on technology. A future related to understanding their customers and discovering new relationships and correlations that would otherwise not be apparent to the human eye. Big data is indeed promising but, if there’s an industry that has it “easier”, retail certainly does. Why? Because finding raw data to work with isn’t a problem.
A deeper look into big data shows that retailers of all sizes are actually the best equipped to handle this rising movement.
Retailers collect data every day
Retailers, both on and offline, have the advantage of having customers voluntarily sharing information about themselves that research companies for other industries pay thousands of dollars for. This information comes from:
• Rewards and loyalty cards
• Purchase history
• Browsing behavior on their webpage
• Email marketing campaigns
• Social media interaction
All of these sources provide retailers with data that allows them to get a better idea of how to market their products by analyzing behavior patterns, promoting hot products and even predicting in-store sales based on weather patterns.
Customers see the benefits of giving data to retailers
Retailers are great at explaining the benefits customers receive when they give their personal information. Offering to send out coupons in exchange for an email address or promising a more customized shopping experience when using your bonus card are very non-threatening methods of collecting data. This makes the process much easier and also helps ensure the data being collected is accurate.
When you can explain that the customer will get some sort of value by giving you their information, they are much more likely to oblige. Kerem Tomak, Vice President of Analytics for Macys.com, explains that “customers share a lot of information with us – their likes and dislikes – and our task is to support them in return for their loyalty by providing them with what they want, instantly.”
Big data is more cost effective for retailers
Due to the fact that retailers don’t have to make as much of an effort to gather data, the entire process is much cheaper than an IT firm or app developer, for example. Other industries have to budget large portions of their marketing dollars towards creating a campaign to gather email addresses or even purchasing customer data from a database.
Also, retailers tend to get a great ROI on big data analytics. One of the chief concerns of big data for retailers is whether they can afford to invest in database management, whether they have the talent and resources to take care of it, or whether it’s even worth the money. This concern is understandable, but with the money that can be saved by gathering customer data, retailers save thousands on purchasing unnecessary inventory and ineffective advertisements.
How retailers should handle big data
Collecting the data might be an easier task, but effectively storing and utilizing it is another beast entirely. There are NoSQL Retail Solutions available that help retailers keep up with the pace in which big data is collected. For instance, if a retailer wants to cross-correlate buying behavior between purchase records at the store and through their site, they need a database solution that can quickly add the data and sort it within a matter of seconds.
Whether you are using Hadoop, SAS, MongoDB, or other applications to build your analytics application for report automation, the difference in companies staying ahead of their competition will be how they are using the data to benefit their consumers.
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