Big Data Changing the FMCG Ecosystem

FMCG, Fast Moving Consumer Goods are products that are sold quickly and at a low cost. These include goods such as soft drinks, toiletries, over the counter drugs, toys, vegetables etc. Quickly changing tastes of consumers plays a vital role for example the change of coffee being a favorite to green tea taking its place. To succeed in a business, one should have a thorough knowledge about the product, its competitors and the changing trends. The FMCG industry has used the power of Big Data to gain success and speed up their businesses in various aspects.

Big Data helps FMCG companies to be more responsive and responsible towards customers. By combining customer data with purchase data, retailers can segment their customers in fine detail. They can also target their customers with personalized marketing and targeting.

The current challenges faced by the FMCG industry include: optimizing the spend, rapid new product innovation, improving sales and marketing effectiveness, integration of various data source, evaluation of various scenarios and visibility of supply chains. Keeping in mind the complexities, FMCG industries need better tools that can help in planning, management, measurement and improve the operational and financial performance of the company.

Business Intelligence and Big Data analytics comes to the rescue of such companies helping them organize and compete with the deliver quality and shipment value. Big data has a positive impact on the FMCG industries. Printing unique codes on packs unlocks the enormous potential Big Data holds for FMCG brands. As consumers register and enter codes, it enables brands to collect high quality behavioral and individual purchase data in a single view. They are then perfectly placed to engage consumers in a highly relevant and unique way.
Big data can help in enabling more intelligent promotions which is the key to driving sales.

With Big Data and Business Intelligence we can help FMCG companies grow by answering the following: Who are my most profitable customers? How can I optimize my pricing structure? How can I analyze inventory turns to improve sales? How can I predict customer buying patterns?