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7 Amazing Examples of How Retailers Are Leveraging the Power of Big Data

Big data is undoubtedly are changing the way business gets done across several industries. The retail market is at the forefront of it. The use of advanced analytics and predictive analytics is changing the face of retail.

Worldwide, retailers are leveraging Big Data analytics to improve every stage of the retail process – this includes trends prediction, demand forecast, price optimization, targeted marketing, and improvement in the overall sales process.

According to McKinsey Global Institute, retailers leveraging the full power of big data can increase their operating margins by as much as 60%.

Let us have a look at how the major retailers around the world are leveraging big data and analytics –


The biggest retailer, Walmart, has a soft corner for big data. The company processes 2.5 petabyte of data every hour and to simplify this task, it has built a Data Café.  The retail giant combines both internal and public data and uses it to capture the attention of the target audience by sending hyper-targeted messages. Once, when the retailer’s team was not able to understand the reason for the drop in sales of a particular product, the Data Cafe analysts were able to pinpoint that the drop in sales was due to a pricing error. Once the error was rectified, sales picked up again.


The American luxury department store, Nordstrom, captures data from various sources, including website, social media and customer rewards program. Their big data analytics system effectively keeps track of the customer behavior including the time taken to shop, which section of the department store receives the maximum footfall, and the time of the day when customers stay in the store. Such behavioral analytics helps Nordstrom to promote products according to the preference of the customers. The company is leaving no stone unturned to provide a personalized experience to the customers using big data.

Procter and Gamble

P&G has been at the forefront of using big data analytics and data visualization to monitor all the possible touch points of the customers – right from online, in-store, social or on television. This helps the company in quickly detecting key indicators which are used to create new predictive models and this data is used in the marketing of new products. The company has ensured that using the right tools and technology, the right people have access to the right data and the company is working on building a data-driven culture within the organization.


The school and office supply retailer uses big data to process more than 10 million transactions to accurately forecast the sales. The forecast is then used to effectively target the audience and promote the products in the market. Interestingly, with the help of big data and retail analytics, the company was capable of cutting down the marketing cost by more than 25%.


Today, Amazon is the leader in collecting, storing, processing and analyzing data. The company uses predictive analysis to enhance the customer loyalty and build a long-term relationship with the customers. The company uses big data systems for selecting the warehouse closest to the location of the vendor and the customer, thereby cutting down the shipping cost by 10-40%. It also uses big data for on-the-fly price optimization wherein; the product prices are set according to the user’s activity on the website.  


Macy’s main goal is to be customer-centric. The company aims to create a very personalized and localized customer experience across various channels. It gathers data through various data points including price promotions, out-of-stock rates, and combine these with specific product SKU data at a certain location. The company then combines this complete information with specific customer data which helps them optimize their product variety in specific locations based on the customer preferences. Apart from this, Macy’s also gathers data about customers’ visits, style preferences, online behaviors to understand their personal motivations and then uses it to create a personalized experience with customized offers at checkouts.


Costco, like all other major retailers, gathers a tremendous amount of data about its customers and their buying habits and patterns. Apart from targeted advertising and marketing, once the company used this data for something very unique which helped it in building more loyal customers. Once, a fruit packing company sent out a warning to Costco about the possibility of listeria contamination in its fruits. Instead of sending a mass mailer to all its customers, Costco took care of the specific customers who had purchased those particular items by notifying them about the possible contamination, first by phone and followed up with a letter. This gesture was obviously well appreciated across various social media channels.

When there are thousands of retailers looking for customers’ attention, how do you stand out from the crowd? Well, the answer is big data and analytics – retailers have no option but to harp on the power of data to deepen their relationships with their customers and turn customers into brand advocates.


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