With the data volumes skyrocketing, businesses are applying modern technologies to harvest the power of data science.
More e-commerce executives agree on the following: big data holds the key to the amazing future of the e-commerce industry.
Big data enables e-commerce companies to improve decision making, gain a competitive advantage, enhance their performance, products, and operational processes. It also allows customer behavior analysis and prompts the discovery of actionable insights.
Although big data resources are becoming more accessible, it’s easy for e-commerce companies to get overwhelmed with big data. Big data-enabled tools can already help businesses create coupons, manage blog names, and detect fraudulent behaviors in real-time. While many business aspects from operational processes and budgeting to marketing can be optimized with the help of the big data technology, many e-commerce executives are still struggling to use data science for revolutionizing their businesses.
Predictive analysis, lead scoring, and targeted personalization are just a few concepts closely related to big data. If you’re new to these terms, it’s important to cover the basics before moving on.
The volume, velocity, and variety (the 3Vs) are what make the technology called big. With the 3Vs of big data, companies have access to all sorts of information about customers’ experiences, financial transactions, and the competitiveness of the marketplace.
But how can e-commerce businesses pull all of this data to work? How can they take the right information and put it to use so that it can be valuable, actionable, and make the company work better?
To help you find answers to these questions, we’ve gathered everything you need to know about the ways big data transforms the marketplaces. After reading this article, you’ll get a better perspective of the benefits empowered by big data, and the major ways data science has impacted the e-commerce industry.
According to a study published by BARC, there are four major ways e-commerce corporations benefit from big data: the strategic decision making (69%), improved control of operational processes (54%), a better understanding of the customers (52%), and cost reductions (47%). Let’s take a closer look at each of the benefits, so you can get a better perspective of how big data transforms e-commerce marketplaces.
In the times when e-commerce businesses must truly understand customer behavior to grow, it’s paramount to adopt big data resources and analysis. The big data technologies provide colossal means to analyze customer behavior, needs, and experiences.
Companies can use data analysis to identify and predict which offerings will better suit customer needs in the future. A better understanding of customer needs and expectations will also increase customer satisfaction and retention, and as a result, will help more e-commerce businesses grow.
Big data allows you to inform your marketing strategy by analyzing search results trends. You can see which results are trending and craft your SEO and marketing efforts accordingly. Additionally, this will help you better understand customer behavior as you can analyze which search results are popular amongst your customers.
“To better understand your customers, it’s helpful to use additional resources to analyze search results and the potential scope of your competition,” says Domantas Gudeliauskas, a Marketing Manager at Hostinger.
Operational cost cutting is another benefit big data brings to e-commerce corporations. Big data resources allow advancements in every aspect of business strategy and planning, from customer experiences to marketing and supply chains. These advancements bring key changes in budgeting as they reduce operational costs. This way, e-commerce organizations can invest in third-party logistics and leverage the economies of scale. This allows to reduce cost per team and optimize the overall operational methods.
With the help of top big data companies, e-commerce companies can make more strategic and clever managing decisions. In fact, about 50% of the structured data collected from the internet of things (IoT) is already used in decision making. The very same analytical tools that help marketers better understand their customers can be used to improve corporate decision-making.
E-commerce executives can leverage big data and real-time analytics to make more informed and strategic decisions. For example, when e-commerce executives know which customers have the highest long-term value, they can spend more money acquiring, targeting, and later retaining these customers. This way, the budgeting decision is strategic and well-informed as it’s based on the analytics enabled by big data resources.
Lastly, big data resources have the potential to improve operational processes and efficiency. Operational processes can largely benefit from algorithms analyzing customer behavior and their shopping data. Also, big data enables the implementation of predictive analytics. For instance, companies can use predictive analytics to calculate the average checkout wait time. Later, this data can be used to improve customer experiences and, as a result, get a better checkout wait time.
Also, big data algorithms assist e-commerce companies in analyzing market trends and supply chains. This factor is especially helpful in identifying the optimum inventory levels warehouses need to maintain for more effective operations.
Amazon is a great example of how big data can transform operational processes. The company uses big data to monitor customer behavior, shipping details, and personal information. Then, Amazon uses big data and IoT to link with manufacturers and track inventory to make sure all orders are shipped quickly.
Special algorithms select an Amazon’s fulfillment center (warehouse) closest to the customer and figure out the fastest route to deliver goods. This process allows operational processes optimization and cost cutting by 10-40%.
If you’re still not sure whether you should employ the big data resources into your e-commerce business or not, take the time to think through what research has to say. Studies show that 99.5% of all collected data never gets used or analyzed. Now, imagine how many potential resources and opportunities for business growth these data contain!
To help you make sense of the potential of the big data technologies in e-commerce, we have gathered the major six ways big data impacted (and continues to impact) the e-commerce industry.
Big data unlocks access to enhanced shopping experiences. Big data and analytics allow e-commerce professionals to better understand their customers and tailor product offerings concerning each customer’s needs, pain points, and expectations. This leaves companies thriving as their customers feel more satisfied with their shopping experiences.
Amazon’s use of big data is a great example of how strategic use of algorithms can improve customer shopping experiences. By allowing algorithms to figure out the best way to deliver items, Amazon doesn’t only optimize their logistics but also enhance the shopping process for its customers. In this case, big data allows Amazon to deliver products faster with a minimum chance of misplaced packages.
Delivery drones are another big data-enabled technology that is predicted to become mainstream in the nearest future. Amazon is currently testing different drones to figure out a way to enhance customer experiences with faster delivery.
Alternatively, e-commerce companies can use big data algorithms to analyze net promoter score (NPS) surveys and customer reviews. Later, this feedback can be analyzed to tailor better shopping experiences.
Personalization and targeted advertising are likely the biggest trends in e-commerce marketing. Marketers who understand the importance of timely, relevant, and personalized experiences already employ big data technology to deliver more targeted ads.
Big data enables big personalization. By monitoring user information, like browsing requests and preferences, e-commerce professionals can shape marketing campaigns around each customers’ needs. This way, corporations can deliver more personalized experiences and focus on per-customer profitability.
Artificial intelligence (AI) algorithms and machine learning software can predict what your customers will buy and when! Many companies, including Amazon, Sephora, and Netflix, are already applying big data to track user behavior in hopes to understand customer mindset. In fact, Amazon’s product recommendation engine (that is based on predictive analytics) drives 35% of cumulative company revenue.
Predictive algorithms (just like Amazon's product recommendation engine) track everything, from customer needs to their personal information (like contact details or even their income level) to better understand which products will resonate the best with a particular customer.
Additionally, many e-commerce executives successfully implement big data tools to enable predictive lead scoring. Lead scoring includes analyzing the behavior of prospective customers to determine whether the prospects are valid. And if they are, ranking them based on their value.
Big data enables automation of predictive lead scoring algorithms. This is certainly helpful for e-commerce businesses as they can predict which prospects are more likely to convert into paying customers.
Big data technologies have the potential to revolutionize customer service. With big data, corporations can analyze the report data through email letters, social media campaigns, and online self-service tools. All of the collected data can be analyzed to identify possible customer service drawbacks.
Knowing what does not work well enables change and further improvement of customer service. Also, the collected data can be translated into reports and educational materials for customer service representatives.
Big data analytics enable greater security of online payment processes. Since big data algorithms are effective in analyzing huge sets of information, companies use these capabilities to detect banking frauds and ensure safe payment on their websites.
For example, PayPal is using big data resources to enable machine learning algorithms. These algorithms analyze billions of transactions to identify potentially fraudulent transactions. Additionally, big data can be used to view which payment methods are working best and are the most popular amongst customers.
Data-backed price management proves to be extremely effective in e-commerce. In fact, research shows that data-driven price management initiatives facilitate considerable results in the short-term perspective, including a 2%-7% growth in business margins and a 200%-350% average growth in ROI over a one year period.
So, how does big data enable e-commerce companies to optimize product pricing? The answer is by analyzing large quantities of data, including previous purchases, cookies, clickstream, as well as enterprise resource planning systems. Thorough analysis helps to set prices dynamically concerning the real-time data.
Besides, big data and automation tools can provide live analytics showing your team how discounting will impact your profitability or how likely your audience is to respond to particular discounts.
Back in 2018, it was estimated that 2.5 quintillion bytes of data are produced every day, and the scale of the data is predicted to increase exponentially. The immense power of data analytics plays a central role in facilitating the growth of the e-commerce sector.
Before you go, let’s quickly wrap up what you’ve learned today about big data in e-commerce.
The bottom line is that the ultimate goal of businesses applying the big data resources is not the data itself, but digging deeper into the insights provided by the data. With big data technologies, you can break through all of the customer data that you’re collecting to bring out the key pieces of information that will help your business grow.
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