Every day, we send 294 billion emails, 500 million tweets, and 65 Cases billion messages over WhatsApp alone. These numbers are humongous to the point of being unimaginable.


The question is, what can ecommerce companies do with that rising sea of information? This article offers some answers.

Big Data Is Instrumental to Ecommerce Growth

The analytical capabilities that big data brings to the table are disrupting all industries, including ecommerce. Online vendors engage ecommerce development services to weave big data analytics tools into their e-shops and marketplaces and tap the ensuing benefits that include:

  • Optimization of back-office processes
  • Enhancement of customer-facing operations
  • Streamlined supply chain management
  • Fraud identification and prevention in customer transactions
  • Increased competitiveness with dynamic pricing

Let’s dive into how ecommerce vendors can attain these goals with big data.

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The Application of Big Data in Ecommerce

Let’s take a look at some of the most relevant and promising applications of advanced analytics and big data in ecommerce. These big data use cases can help ecommerce companies like yours drive operational change and inspire some future implementations.

1. Demand Forecasting

At the core of big data lies data analytics, i.e. the practice of utilizing data analysis technologies and statistical models to create predictions and evaluations underlying informed decision-making.

Predictive analytics is used to assess the likelihood of various events occurring in the future based on a variety of factors, but big data systems can also provide insights into past events (through descriptive analytics), enhance decision-making by collating predictions and possible outcomes, and come up with the suggested course of action (prescriptive analytics).

Data analytics has a wide range of applications, covering clinical decision support systems, enhancement of marketing campaigns, fraud detection, and project management. In ecommerce, big data is the cornerstone of demand forecasting.

2. Pricing Optimization

Price is one of the main factors driving purchase decisions among online shoppers, which makes it one of the key success enablers for ecommerce companies. The right pricing can be determined based on different analytical techniques, including market segmentation, competitor analysis, or targeting strategy. In order for these approaches to work and bring more profit, they have to rely on tangible data. The larger the data pool, the greater the chances of hitting the bull’s eye with pricing.

By extending big data’s predictive capabilities, digital retailers can find their pricing sweet spot. Big data analysis engines extract price-affecting data from a variety of consumer touchpoints and other sources to calculate the price that offers customers the best deals while maintaining the highest possible margin. They do these calculations automatically and in real time based on defined algorithms and parameters, which helps e-store owners make more strategic, data-backed pricing decisions.

3. Supply Chain Management

Today, supply management wouldn’t exist without big data, as supply chain operations are becoming more complex and involve an increasing number of products, processes, and agents. This is especially true for ecommerce businesses that operate in the global market, as their supply chain gets stretched in time and complexity. Thanks to its powerful ability to draw meaningful insights from overwhelming datasets, big data solutions provide a wealth of process improvement opportunities for ecommerce in the area of supply chain management.

4. Customer Experience

There’s no doubt that personalized experience is critical to positive customer perception of any ecommerce store. Businesses that meet or, even better, exceed, customer expectations, demonstrate higher retention and conversion scores and drive greater profit. The competition in the ecommerce market is stifling, and it is encouraging more sophisticated consumer demands. Online brands that excel at engaging their buyers and prospects are the ones that precisely know what consumers need and deliver that to them quickly. To achieve that aim, they need to gather, analyze, and understand relevant data.

Tools delivering customer insights have been around since the beginning of marketing (surveys, interviews, questionnaires, focus groups), yet they traditionally involved various challenges, such as sample size and selection bias. Big data solutions allow companies to eliminate these inefficiencies and capture customer needs, feedback, and expectations competently and automatically.

5. Secure Online Payments

Ecommerce vendors do their best to make buying online easier than ever for consumers. They add new purchase channels, such as mobile apps or social media marketplaces, to reach out to their audiences wherever they are. They also strive to simplify the buying process by investing in user-friendly interfaces, reducing the number of steps to finalize the purchase, and providing support for diverse payment methods.

Unfortunately, along with these innovations comes an increasing number of associated threats. The broader choice of paying options creates more opportunities for cybercriminals to find weak spots and vulnerabilities.

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The Bottom Line

The success of any retail enterprise, be it offline or online, has always depended on data-centricity. Only by knowing what exactly customers expect and understanding how their organizations work in every aspect, can e-vendors offer the right products to the right people at the right time.

Big data took data analysis to a whole different level: from manual to automated; from small batches of data at a time to massive data volumes handled within minutes; from arduous and error-prone manual processes to almost instant and highly-reliant insights and feedback.