Wednesday, December 30, 2015

How to Operate Big Data in Retail

In today’s business environment retail data analysis is a key to increasing productivity and gaining competitive advantage. Big data as the way companies connect with customers is especially promising for retailers. Regular merchandising audits allow companies to better understand their business processes and get insights for successful marketing strategies.

Gaining acceptance for big data can be less challenging for a company with a proper type of merchandising software. Although today there is great variety of merchandising software solutions on the market, not all of them offer equal capabilities to users.

To maximize the value of retail merchandising audits, a company should look for a comprehensive type of merchandising solution, which includes analytic capabilities. The most sophisticated merchandising software solutions provide instant data analysis and reporting through Web-based dashboards along with export/import features to integrate your data with third-party software if necessary.

The up-to-date merchandising software allows gathering various types of retail data including:
  • Customer data (retailers’ location, contact information, price-lists, history of orders and returns, feedback, and brand loyalty)
  • Product data (product location at store and on the shelf, quantitative parameters of the layout, pricing, order amounts, inventory levels, and out-of-stocks)
  • Competitor data (competitors’ products, prices, marketing strategies, market share, and customer profile)

Each type of data provides specific insights to build brands and improve company’s bottom line. For example, by capturing and analyzing customer data companies are able to:
  • Better understand consumers’ needs and requirements
  • Identify highly profitable/troublesome customers
  • Specify promotions and product offerings to each customer
  • Design personalized marketing
  • Detect “lost” or dormant customers to win them back
  • Make sales forecast for the future.

Product data analysis allows:
  • Getting insights on how different products are selling in different locations
  • Achieving optimal inventory levels across stores leading to improved efficiency at the supply chain level
  • Evaluating the product demand at points of sale
  • Adjusting your products to better fit each location
  • Finding optimal mix of product types and quantities via each store. 
  • Having the information on which products are sold faster than others 
  • Identifying most profitable products
  • Predicting potential out-of-stock situations
  • Maintaining proper inventory levels at each store

Competitor analysis as a substantial part of marketing strategy allows getting a good indication of industry leaders’ marketing strategies. When analyzing competitors’ data, companies are able to:
  • Assess their competitor’s strengths and weaknesses
  • Develop effective strategies to improve competitive advantage
  • Use targeted marketing when competing with those surrounding brands

To get more information on retail data analytics, visit or book a free live demo to see how retail data analytics works on VisitBasis merchandising software.

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