How does e-commerce use big data?

big data e commerce

The use of big data in e-commerce is becoming increasingly popular, giving rise to a multi-billion dollar industry that is growing steadily year after year. It is showing no signs of slowing down in the short term. In fact, e-commerce sales are expected to reach $5.5 trillion worldwide by 2022.

This makes e-commerce a smart strategy for virtually any business, large or small. And now, with the power of big data and machine learning algorithms, you can be even more competitive in your specific niche market. If you are wondering how e-commerce uses big data, here are all the benefits that come with it.

Key benefits of big data

What is big data analytics in e-commerce? It is a very broad term with a wide array of applications. It can help to understand customer behavior, discover new business opportunities or forecast future trends, for example. In fact, there are many big data e-commerce case studies and retail. These are some of the most compelling benefits of its use:

  • Customer acquisition and retention. Companies use big data to observe consumer patterns, and tailor their products and services to specific customer needs.
  • Focused and targeted promotions. With big data, companies can analyze customer trends by monitoring online purchases and point-of-sale transactions. In this way, they can offer customized products.
  • Identification of potential risks. By using historical data, big data plays a key role in developing effective processes and strategies, allowing a glimpse into the future.
  • Innovation. Information about what others think of your products or services can help in the development of new proposals and can also be used to modify business strategies, improve marketing techniques and optimize customer service, among others.
  • Cost optimization. One of the most compelling benefits offered by big data tools include significant cost advantages for storing, processing and analyzing large volumes of data.

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Can you integrate big data into e-commerce?

As we have explored, data can be used in many different ways to improve your bottom line. However, firstly, you need to understand what data is available to you, as well as where you can find it.

Shopping analysis

Once you have a better understanding of data in e-commerce, you can begin to use it to its full potential.

These usually include information such as traffic sources, bounce rates or conversion rates, among others. This data can help you identify where your traffic comes from, how long they stay on your site or which pages they spend the most time on, for example. What is more, this can help you identify areas for improvement and see which pages are driving the most sales.

Customer service

Better customer service includes a timely response at the right time. With the help of data science and machine learning, even small problems can be tracked down and fixed as quickly as possible.

Another aspect of big data in its link to machine learning is that it improves customer service capabilities. From both, we have the help of chatbots, which could be deemed to be a critical AI tool for employing customer communication via mobile messaging. They are used to give predefined answers to customers based on the keywords used in the question.

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