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Using predictive analytics and big data in e-commerce

Big data has undoubtedly revolutionized the world of digital intelligence. The beauty of big data, especially in thriving digital industries like e-commerce, is that it allows us to have access to an abundance of information that drives data-driven decision-making. Predictive analytics and big data have transformed e-commerce by placing consumer needs first and helping marketplaces stay ahead of the game. This has been a proven game-changer across e-commerce giants like Amazon and eBay. Similarly, big data and predictive analytics can play a significant role in generating revenue for online businesses.

Moving forward, what does this mean for e-retailers? How can big data be leveraged to make better business decisions and enhance operations?

Every day, we generate up to 2.5 quintillion bytes of data (that’s 18 zeros!) In a market that is built to scale, e-commerce platforms have to attract customers from multiple demographics and geographical locations. However, it can be nearly impossible to collect data on every single customer using traditional data processing, let alone analyze it. That’s where the role of big data comes in. In a nutshell, big data allows e-commerce platforms to access large sets of data, which reveal consumer information and habits. These can be analyzed using innovative technologies and machine learning capabilities to provide predictive models.

What is Big Data?

Big data refers to large volume, complex sets of data, unstructured or structured, that are difficult to process using traditional data processing. According to industry analyst Doug Laney, big data is defined by three components: volume, velocity, and variety. Businesses have long relied on the collection and analysis of data to run operations. But given the growth of the Internet-of-Things, data collection now happens more frequently and on a more detailed level. 

As data continues to be generated at an astronomical speed, it can be costly and inefficient to store, manage and access such copious amounts of information. Big data addresses the inefficiencies in traditional data management and plugs the gap between businesses and their consumer data. In the past, the e-commerce industry has been slow to adopt the technology, perhaps due to unfamiliarity or affordability. However, as technology progresses in the field, big data has grown to be a viable and valuable solution for online marketplaces.

What can Big Data do for e-commerce?

Before discussing the benefits of big data, it’s crucial to establish the role of predictive analytics in the online marketplace. Predictive analytics enables e-commerce platforms to gain a deeper understanding of their consumers based on past activity and preferences, in order to deliver highly personalized experiences and tailored solutions. 

Predictive models are built on real-time search activity that looks at things like click-through behaviors, shopping history, product searches, preferences, and more. All these happen through a cloud-based capability that analyzes actions in real-time and continuously. Thus, e-commerce retailers are able to receive the most up-to-date reflections of their consumers and alter their strategies accordingly. With the help of machine learning technology, these online platforms are able to display relevant results and personalized recommendations to shoppers.

In a highly dynamic environment like the e-commerce space, millions of users are conducting searches for new products every day. Last year, the global e-commerce market generated a whopping 4.28 trillion dollars in sales. In order to run target campaigns using predictive analytics, businesses need a solution that enables the capturing and processing of large sets of consumer data. This way, e-commerce retailers can cater to a larger market and respond to opportunities at a faster speed. 

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The Benefits of Big Data in e-commerce

Drive strategic and knowledgeable business decisions

Any successful business owner will know the importance of a good strategy. A business strategy lays out the foundation for business decisions. Leveraging on big data and predictive analytics can drive retailers’ decision-making through actionable insights and an understanding of their customers. For instance, e-commerce retailers can take a look at visitor preferences and habits to craft effective targeted campaigns as a marketing strategy. Big data also helps in pricing strategy. By tracking competitor prices and demand, sellers are able to tweak their prices accordingly to fit the market.

Beat out competition

Brands that leverage analytics and big data can capitalize on personalization as a competitive advantage. By gaining a deeper understanding of their consumers, they can better attract, engage and retain customers by catering to their individual preferences and motivations. Business tools can be used to collect data on customer complaints and continuously enhance the customer experience. 47% of customers turn to Amazon if the brand they’re shopping with doesn’t provide their desired product recommendations. If anything, this shows the power of e-commerce marketplaces that rely on personalization as a differentiating factor.

Work together with predictive analytics to enhance operations

With machine learning capabilities, big data provides large data sets that can be assessed to identify emerging trends. Predictive models can be used to map out best-performing products, product sale potential, opportunities and potential customer profiles, and popular marketing channels. 

Leverage on a customer-first approach

70% of customers have stated that they get frustrated when a brand sends irrelevant ads or messaging. In today’s retail space, it is crucial to attend to customer needs before anything else. This is made highly possible with the use of consumer data.

Forecasting for better planning

Seamless operations are vital to business success. They ensure that operations are running smoothly and at an optimal speed. Data allows retailers to make forecasts of future demand. For instance, demand for certain products may surge during peak periods like Christmas or Black Friday. In order to meet this demand, retailers can leverage on sale numbers from the previous year to stock up inventory.

Best Practices for Big Data and Predictive Analytics for retailers

As useful as it is, big data and predictive analytics are valuable tools only when used right. When it comes to any technology, it is important to keep in mind the best practices in order to gain a fruitful experience.

Focus on business goals

It’s easy to be distracted by the latest technology, as with the most innovative tech tools in the market right now. Beyond the IT infrastructure and function, the bottom line that defines every business is its goals and needs. The first step to beginning the digital intelligence journey is to map out business objectives. What is your business trying to achieve? Are you trying to spread brand awareness, generate more sales, or retain your customer base? What are the metrics that can measure whether the initiatives are effective? By defining your business goals, you can determine the type of technology and provider that will best support your needs.

Determine the type of data you need

An important step to making your data intelligence work for you is by determining the type of data you need. More often than not, businesses plunge into big data and analytics headfirst, storing, collecting, and analyzing just about any type of data. As much as it is beneficial to have access to large and complex data, it can be counterproductive (time-wise and financially) to store information that is irrelevant to your business. 

Continuously update your strategies

As mentioned, strategy is key to building a successful business in e-commerce. However, in such a dynamic environment, practices and trends are constantly emerging. It’s best to rely on predictive analytics to identify upcoming trends and alter strategies accordingly. While business strategy sets a precedent for all business decisions, there may be a time where it is essential to course correct. And that is completely normal.

Keep an eye on compliance

Given the sensitivity around data collection and privacy, it is vital to business continuity that retailers pay attention to data privacy and compliance. Overlooking this aspect can lead to litigation issues and a loss of brand reputation. When engaging with any marketplace tool, it’s important to check that they are equipped with the necessary knowledge surrounding data regulations. 

Find the right provider

How effective big data and analytics is for businesses depends on how well retailers work with the IT infrastructure to make things happen. This is based on individual business requirements. For instance, many retailers will find that batch processing doesn’t work as well as real-time actionable insights in a continuously-changing e-commerce environment. It’s crucial to check the features of each marketplace solution to ensure that it applies to your business.

Driving better business decisions with e-tailize

Whether it is keeping up with emerging trends or analyzing past patterns, e-tailize is a one-stop solution for e-commerce businesses to acquire, manage and store customer data for accurate decision making. Understand your customers on a deeper level using our database and extensive data analytics features right on your dashboard. Find out more about e-tailize features for sellers today.

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