5 min read

Big Data for E-commerce.

The year 2020 was full of challenges in many areas, and in many companies and organizations.  Often, it was necessary to introduce radical changes or face bankruptcy. The e-commerce sector is no exception.  Due to lockdown, most life activities, both social and business, have moved to online reality, and it was no different in the case of shopping. The coronavirus pandemic forced e-commerce businesses to face a completely new reality - for example in 2020 consumers in the U.S spent over $861.12 billion online, which’s 44.0% more than in 2019. 

The situation is both great development opportunities for e-commerce and a serious threat. The increased number of consumers also means an increased number of inquiries, the need to process huge amounts of data not only from sales but also from marketing or service maintenance (including anomaly detection and fraud prevention).

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These opportunities and threats are the more important reasons why Big Data for E-commerce has been named the game-changer for 2021.

Why e-commerce needs Big Data?

So how Big Data can help e-commerce? 

To start, the Big Data ecosystem has tools to help you deal with large amounts of collected data and turn them into real assets, instead of real problems. Data analysis, monitoring, and concluding are the basis for optimizing the functioning of the e-commerce business, and for building a data-driven approach to its sales and marketing. Below I will show you, why there is no future e-commerce without Big Data:

  1. Sales and marketing optimization  - one of the main goals of every e-commerce organization is the optimization of their sales and marketing processes. That's where Big Data tools come in. Thanks to the collection of information and its analysis, organizations can provide customers with the best solutions and the most interesting products for them, as well as select and develop the best-functioning marketing channels. The more knowledge about customers, the easier the e-commerce business will be able to offer them the most personalized products. 
  2. Anomalies and fraud detection - Thanks to the tool enabling real-time analytics, the detection of anomalies, e.g. in customer behavior, helps to react quickly and implement appropriate solutions. In the same way, organizations can respond to fraud attempts by detecting suspicious activity in the data stream (check how real-time analytics helped telco companies to detect anomalies). it is extremely important for e-commerce due to the increasing numbers of on-line payments.
  3. Predictive analysis - thanks to Machine Learning algorithms and other Big Data tools, organizations can predict customers’ behavior and in this way prepare an offer to meet the needs of a specific time of the year, events, or other circumstances. Store supplies, promotion dates, or strengthening PR activities, as well as the momentum of introducing new products, are optimized thanks to the possibilities of Big Data tools, it is possible to enhance not only external but also internal organizational processes.

As you can see, well-used Big Data tools are able to improve the functioning of e-commerce companies. Of course, building a Big Data infrastructure itself can be long-lasting, but the possibilities of using cloud solutions, Machine Learning algorithms, or analytical platforms supporting Business Intelligence cannot be overestimated. The ability to manage data so that it brings as much information as possible that can be used by marketers, resellers, graphic designers, and application developers is already giving many market players a huge advantage over the competition. This is just the beginning.

Why there is no future e-commerce without Big Data?

It may seem that the above three areas are only related to the possibilities offered by Big Data tools. However, they are also a warning which, when received too late, can turn into a real problem for e-commerce businesses. There has been a lot of discussions about Big Data as the future of e-commerce in recent years, but it was theoretical and rarely implemented.coronavirus lockdowns around the world mean that theory will have to turn into practice very quickly. All three aspects discussed earlier, when viewed in reverse, give a rise to concern:

  1. Sales and marketing problems - without the possibility of processing and drawing conclusions from an increasing amount of generated data, there will be no real possibility of optimizing sales or marketing processes to the same extent as competitors using appropriate analytical and Machine Learning algorithms
  2. More frauds and anomalies - more customer actions, the greater possibility of anomalies and problems, which will negatively affect sales. Along with the development of the market, not only the number but also types of payments frauds increases, and customers buying online are very sensitive about the security of their money and data. Without the right tools that can react in real-time, large players will not be able to maintain order stability and customer trust.
  3. Inability to predict the future - of course, this is not about a crystal ball, but the lack of tools that can predict customer behavior and analyze past events that will indicate future trends. Without this knowledge, it will be difficult not only to make a new product introduced to the market meet customer needs or make decisions about future activities.

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Towards the data-driven e-commerce

Therefore, e-commerce based on a data-driven approach is something that must happen (if you are interested in how to take the first steps to such an approach, check "Towards the data-driven organization" post. The future belongs to data, and it becomes obvious every day.

If you have questions about the possibilities of individual Big Data tools, or solutions that will develop your e-commerce company, do not hesitate and contact us. We are happy to advise you in choosing the best solution for your company.

big data
analytics
technology
business intelligence
big data project
11 March 2021

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