Four E-Commerce Applications of Big Data

While big data has proven beneficial to brick and mortar stores, it is especially well suited for e-commerce. Unlike the offline world, change is effected more rapidly online in response to information input. For example, the prices of e-commerce products and the types of products displayed, can be instantly adjusted according to the specifics of each visitor viewing the page.

Here are four ways that online retailers can benefit from big data:

Demand Prediction

Social media is an enormous pool of unstructured data on consumer preferences, opinions, and sentiment. Meaningful use of social media on a large scale is a big data problem. Back in 2010, HP Labs successfully predicted movie box-office revenue by analyzing the tweet patterns of Twitter. An e-commerce store with such a capability can build up inventory on box office hit products such as toys, well before the competition. Fashion trends have also been predicted from social data. This has an obvious application to e-commerce stores that sell apparel.


Because of big data, each customer’s online retail experience can be tailored according to his or her past purchasing patterns. For example, a person’s pattern of purchasing is very revealing of their life style and life stage. Product offers and deals can reflect this to increase the conversion rates of visitors. Repeat customers can be rewarded for their loyalty while new visitors incentivized to make their first purchase.

Dynamic Pricing

Online consumers do a lot of comparison shopping. Online stores should dynamically adjust their pricing by using data from competing stores. In addition, each customer has “their price” which persuades them to purchase a product. This is useful when suggesting an additional related product at the checkout page. The customer is more likely to acquiesce to the suggestion if the “price is right.”

Better Inventory Management

Too much inventory means lost money in clearance sales. Too little means lost sales and lost customers who go elsewhere for their purchases when popular items are out of stock. Getting your inventory levels just right depends on how well you can anticipate demand. This ties into the demand prediction capability of big data discussed previously.

The other side to inventory is effectively managing your suppliers and monitoring the supply chains beyond them to anticipate possible disruptions. Supply chains are affected by the internal problems of each business as well as external factors such as natural disasters and weather events. Big data techniques allow you to look further up increasingly complicated supply chains.

Applying big data to e-commerce is a win-win situation for both the online retailer and the customer. For more information on big data and our data storage facilities, contact us.

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