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Big Data: The Growing demand of the Retail Industry

Data in Retail Industry

Big Data: The Growing demand of the Retail Industry


Every online business, no matter small or big, values its customer's data. It's the only way to understand the buyer's interest and act on it thoroughly. Big data anticipates the potential buyer's need and improves the business targets.

With the growing competition in the Retail industry, it's getting difficult for a business to provide the right product at the right time. Thanks to big data, brick-and-mortar chains have experienced a significant surge in sales. Big data analytics is applicable at all stages of retail processes. From restocking the popular products to forecasting demands, optimizing price range, and understanding the customer interest, others help businesses stay up to date.

Here are some of the ways big data helps in the retail industry :

  • Predict Trends : Online retailers have a wide range of tools to inform them about the "high-demand" items often sold out, whether that be shoes, designer jewelry, or clothes. Predicting trends algorithms apply to social media posts and web browsing to understand what creates a buzz in the market. Ad-buying data is studied to apply what marketing departments push at such an hour. Using "sentimental analysis," an advanced algorithm, retailers feed the idea of a product, including their cut, color, and pricing, to predict if it will be a hit among customers or not.
  • Estimate Demands : Based on a different season, online retailers anticipate a rise in particular demand for a product. For instance, there's a growing demand for books in the winter season in Russia, so the retailers advertise more books during this time. Using the demographic data and economic indicators, online retailers can forecast the spending habits across the targeted market. Forecasting demand helps retailers react faster to competition, market shifts, and other micro-environmental factors to understand the growing demand in sales. Retailers with these data can use them to allocate SKUs to store where the need is present, bring them maximum gross margin.
  • Manage the Pricing : Walmart, the US biggest retailer, spent millions building the world's most giant private cloud to track millions of transactions that happen every day. The algorithms trace demands, inventory levels, competitor analysis, and market changes in real-time. This process helps retailers to take action based on the insights. Big data helps to determine when the pricing to be increased or dropped. Before the infusion of analytics, retailers only lowered their pricing for products at the end of buying season when the demand is gone. However, analytics have estimated the gradual price reduction from the time the markets start to slow, leading to revenue growth. People also anticipate lower pricing for products that they won't be buying within a few weeks or months, making them more likely to purchase the product.
  • Understanding the Customers : By studying shopper buying behavior, customer service history, and response to discounts, promotions, and social media engagement, retailers can get insight into individual needs and preferences. Big data helps online retailers, especially the fast-fashion ones, to tweak their promotions based on their customer level and narrow it to target the tempted buyers.

With big data, retailers stay one step ahead using the forecasting data that has proven to drive the retailing decisions. It also helps online retailers to adapt to the market condition and use secret strategy by understanding the data. Using big data, Aximind allows businesses to determine the profitable intelligently and less-risky action in terms of product, prices, promotions, and markdown at any given time.

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