The SMART Way to Use Big Data for Retail Businesses
The democratization of information and the quick access to the Internet have transformed most markets by making them transparent and extremely competitive. The current way of comparing prices and sellers resembles the one described in economic textbooks. Reaching that equilibrium is just a few clicks away.
But when price is no longer an advantage, companies need to create new ways to attract and retain customers, and those are closely linked to experiences. This is where Big Data comes into play, offering the necessary insights by tapping into BI consulting.
Managers are used to the SMART goals system for defining achievable targets. The same acronym, with minor changes, could be used to remember the key benefits of using Big Data for retail.
Transaction data, social media buzz, customer feedback, website logs – all help a company answer some particular questions and take guessing out of the equation by replacing it with data. You can now give accurate answers to inquiries like “Where do our most profitable customers live? How much did they spend this year compared to last year? What is the most likely item they will buy next considering their history and preferences?” Having information at this atomic level gives a company great flexibility and speed of reaction.
Performance management is all about defining the right KPIs. Big Data brings a whole new dimension by allowing unstructured data to be distilled into KPIs. With the help of this new tool, organizations can detect trends before these hit the market and adjust their offer accordingly. For example, a high traffic volume on certain search words related to a popular TV series could indicate an excellent lead for merchandise with that theme. Adding information about users from their profiles narrows down the list of articles even more and creates best sellers.
The use of Big Data for analysis to enhance knowledge in retail can unfold on multiple levels:
To convert Big Data into big business, you need to select those insights that are giving hints about the clients’ behaviors in the long term. The relevance factor is best revealed by answering the question: Is this information going to help someone take a better course of action?
The self-service dimension enhances the relevance of a particular set of well-organized data by giving power to the employees in the front line.
Customers have preferred times to shop, and even something as simple as weather could boost or sink sales.
