Big Data for Retail

Retailers are no longer confined to traditional brick-and-mortar stores or local business hours. And neither is the source of their data. Product inquiries, browsing, sales and customer interaction are occurring every minute of every day well beyond the traditional geographic limitations of a single store, or even national chain or stores.

Making sense of this data is crucial in staying ahead in the highly competitive retail field. It is about engaging customers on a more individualized level and correlating consumer behavior for more targeted business solutions that drives growth in an ever changing world. This means understanding the semi-structured and unstructured data in the backdrop of transactional data.

Business Intelligence From A Diversity Of Data

The internet boom has driven ecommerce to heights that even innovative retail solutions of yesteryear, like mail order and home shopping, could never fathom. With the information age comes the sheer volume of data both on the sales floor and beyond that allows for highly individualized and time relevant insight for creating solutions that can be implemented on the fly.

Even if a retailer is not heavily dependent on online sales, the streaming social media data, customer reviews, call center logs and emails contain a wealth of information that often underutilized. It is of little business value until it can be provide key insights. This means that it has to be correlated with transactional data and it requires the right tools to make this happen. Big data solutions are able to do just this.

Ultimately it translates into a better understanding of the market with solutions that are based on insight rather than guesswork, business acumen or historical perspective. It is intended to drive sales, improve inventory, reduce costs and maximize profitability in an industry that often works on small profit margins and is dependent on high turnover.

Big Data In The Retail Sector

Until now, correlating and analyzing data from a variety of sources was not possible. Or it was impractical requiring specialized staff and other resources that detracted from the feasibility of such endeavors. This plethora of data both from structured, semi-structured and unstructured sources is known as big data.

It requires tools that can extract, transform and load data from diverse sources so that it can be analyzed, reported and visualized for business intelligence solutions. In a market where time is of the essence, big data can provide key insights on the fly to accelerate practical business solutions while it is still relevant.

The value of big data extends from the sales floor to the boardroom by assisting with predicting seasonal demand, guiding optimal pricing, identifying product opportunities, highlighting the best marketing channels and optimizing inventory. It can strengthen after sales service and increase customer retention by understanding customer concerns through the analysis of data that may have little value on its own.