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Big data and features it provides increasingly spread over all sorts of industries and niches, granting companies and entrepreneurs unprecedented process optimization, service quality boost, and conversion rates increase opportunities. Initially being the top innovative technology for highly important, complex work environments, big data is gradually shifting focus towards commercial fields of application.
Big data in e-commerce has already helped businesses worldwide save over $1 Trillion throughout 2020, while the retail sector is expected to get a 13.2% CAGR revenue boost by using big data in e-commerce. These statistics obviously indicate a rising number of big data investors among e-commerce market players in the nearest couple of years.
With that being said, let’s take a look at how big data is doing in the digital commerce industry right now and inspect the major trends and examples of big data in e-commerce, as well as how it can help you boost your own e-commerce.
If you still have questions as to why pay so much attention to big data technology in terms of e-commerce at all, we highlight more specific results of employing big data in the e-commerce industry. Big data has had its fair share of time to impact the e-commerce market, bringing some game-changer capabilities and opportunities to the table. Namely, the following ones.
Big data capacities are essential in predictive analytics practices, which help analyze user behavior patterns, optimize user experience accordingly, pinpoint and predict user demands, and conveniently shape the overall picture of the shopping experience you provide. Here, the technology allows for rapid, massive analysis of user-generated data that is gathered from actions users implement in one’s online store or marketplace.
This enables e-commerce providers to tailor products and services that really hit the spot for the target audience of customers. Amazon, for instance, employs intelligent big data-powered delivery routing algorithms that help both optimize the company’s logistics efforts and grant a higher level of user experience (also accelerating the underlying processes, which results in great cost savings).
Targeted advertising and various user personalization approaches are hugely relevant in the niche of e-commerce. And with big data, you get to implement big personalization — a set of practices aimed at tailoring advertising campaigns in direct accordance with the TA needs by thoroughly monitoring and gathering commercial user information (most frequent types of requests, browsing preferences, etc.).
This is a powerful method of user segmentation, targeting, and experience personalization. Through in-depth audience analysis, you can segment users by utterly narrowed down groups and patternelize their usual behavior traits to reach higher conversion rates.
The prime capability of big data to analyze massive sets of data enables payment processing engines to better pinpoint fraudulent activities within flows of online payments and cybercriminals are restricted in malicious manipulations. This grants an ultimately safer shopping experience. Big data-driven algorithms, for instance, are used by PayPal in order to employ the machine learning opportunities and make their system smart at detecting frauds among millions of transactions.
Big data analytics capacities can also be used to form prices balanced out in accordance with both your business plan and target audience demands. Yes, big data seems to be just the right tool for pinpointing that fine line between sustaining the budget and satisfying target customers’ pricing desires. Not mentioning the mass processing of data related to competitors’ operation in the market, customer profiling, and sales channels consolidation which affects the growth of general sales in the most positive way.
With the in-depth analysis of levels of customer satisfaction, detection of issues related to order processing and delivery, and other opportunities at defining points of customer satisfaction and perception, big data enables you to dynamically adjust to the relevant commercial situation. And if you know how to satisfy your customers properly, you can efficiently retain them, accumulating profits and sales growth accordingly.
As you can see, it is safe to say that big data’s impact on e-commerce is invaluable. More so, technology is currently among the main shaping “pillars” of e-commerce practices and approaches worldwide. Now that we know what it does and what it can do for e-commerce management and growth, let’s take a look at how it all works in real-life field practice.
The primary role of big data in e-commerce also concerns various marketing tasks and workflows. Thus, commercial big data processing spawns big regular volumes of invaluable marketing analytics assets. This helps make efficient marketing forecasts, optimize budgets based on specific market patterns, pick operational environments more efficiently, and target the most potentially profitable new audiences.
Last but not least important among big data use cases in e-commerce is the connection with automated AI-powered customer support chatbots. Such “technological collaboration” gives you yet another efficient way of collecting invaluable user data and honing your marketing approaches in real-time. This is where smart bots will help you gather data by the custom-set criteria and sort it right away accordingly, which saves time and effort in the long run.
How to use big data in e-commerce? One of the best ways is to learn from the examples of the top field players. Big data has been employed by some of the biggest players in the marketplace arena, which vividly emphasizes the potential and powers of the technology.
According to its size and scope of operations, this renowned online marketplace has to deal with a massive customer data turnover, servicing over 140 million active customers across multiple channels. This makes up 250 terabytes of data stored, and it is written/read about 5-6 million times each day. This is exactly why the company quickly adopted the rapid, mass data processing technology as soon as it had the chance. And you can see from those numbers alone how much big data helps the company cope with the market pressure.
On top of that, eBay also uses in-depth data analytics for a thorough understanding of user behavior, powers the ShopBot solution with big data capacities for improved shopping experience personalization, and adds the powers of AI for smart recommendations and search by images.
A major use case for big data in e-commerce, Amazon can never be left out of most existing e-commerce success tops and for a reason. For one thing, the company certainly knows what tech concepts to focus on to efficiently expand and maintain all running operations smoothly. And it excels at employing big data for e-commerce, too. Thus, the marketplace puts intricate data science principles into the core of the product recommendation system. Customers’ buying tendencies are analyzed through smart analytics, tracking the major needs and desires of the TA.
Predictive analysis is also employed across connected social media channels in order to better understand and predict customers’ shopping traits. On top of all that, big data and related tech concepts also power the upcoming drone delivery system of the company.
The biggest multinational retailer provider has been relying on the powers of big data since 2011 when Walmart first developed and integrated a real-time social media search and analysis solution for gaining in-depth user insights. We have no doubt that this decision was more than helpful as Walmart seems to know exactly how to keep the mass audience of customers satisfied and coming.
The company uses various data science approaches to achieve well-structured assortment segmentation, delivery routing optimization, supply chain management, inventory tracking and management, and other crucial workflow aspects.
A hugely popular handmade marketplace has followed trends of big data in e-shops to ultimately improve their website. All in all, the platform is working with around 800,000 vendors offering products and services to over 40 million monthly visitors. And it needs to provide the proper tech support and user experience for both sides of the bargain. This is where big data acts as the major pillar. With such a huge marketing turnover, the company benefits even from integrating big data processing methods with regular buttons here and there (which later results in valuable calculations of user action metrics).
This huge international online marketplace is yet another proof of big data’s efficient application in industries apart from finance, healthcare, and such.
Ultimately, the technology allows the platform to carry out its primary mission — providing ground for contactless deals between sellers/service providers and buyers/clients. Big data principles here help handle all interactions, reinforce the security of online payments, and safely store all the related data. In the long run, this seems to be helping Alibaba keep up with operational costs and avoid serious risks just fine.
The above two sections should be pretty sufficient highlights of big data’s ultimate use and potential. But now, let’s find out where it moves and what new opportunities it poses.
As much as the technology already provides some unprecedented capacities for commercial businesses, we are looking at more major growth and expansion directions for big data in the nearest future. Thus, dedicated specialists combine big data processing powers with the capacities of other advanced technologies, such as cloud computing, IoT, AI, ML, etc. Other prominent use trends of big data in e-commerce include the following.
Expanding cloud capacities can efficiently serve as the backing up force behind big data, which will only be growing more extensive and massive. The main selling point of cloud solutions is that their storage capacities can be easily scaled and expanded almost indefinitely.
And this scaling is dynamic and never gets in the way of the overall performance of the running application or platform. This is why numerous companies and entrepreneurs are already looking to purchase or set up their own dedicated cloud repositories today. This way, they get market-defining cloud powers to use as they see fit.
Another closely related technology — the Internet of Things — is looking at its advent in the next few years, and this will spawn even more need for more data to be processed and analyzed faster and at more in-depth levels.
Integrated with such advanced tech concepts as artificial intelligence, the Internet of Things, etc., big data will process information at an astoundingly high level of quality, helping facilities big and small in any industry boost internal processes and cut data management costs dramatically.
Workflow, interactions, and other types of automation are currently focused on across all types of industries where manual, routine, and plain extra costs-consuming tasks can be replaced with alternative automated approaches. This especially concerns all-around available customer support, chatbots, and content translation for the convenience of users.
One of the main future trends in the use of big data in e-commerce is granting automated customer support that works without downtime while presenting efficient ways to handle particular tasks. It will help cut a lot of unnecessary expenses without undermining the quality of service. The same goes for chatbots, while autonomous data translation and visualization should help providers worldwide achieve the next level of shopping experience.
Many people already got used to the fact that many devices, programs, and websites from their daily life seem to know exactly what they need or desire to purchase at the moment. And this intricate personalization will go even deeper in the following couple of years. Ideally, due to the advanced features of expanded data science, every other customer will be visiting online stores as though they were a celebrity and the store is opened just for them.
Up-to-date e-commerce providers of the near future should be able to dynamically adjust to the needs and preferences of every individual customer. For providers, this should help motivate potential buyers to move further the sales funnel and reflect on conversion rates most positively.
With all the benefits big data brings in terms of personalization and the overall convenience of online shopping, as potential customers will be motivated to make more purchases online, the demand for guaranteed personal and business data security will only grow. The ultimate result of the whole progress of big data in e-shops is an utterly hassle-free, comfortable experience for every customer out there.
This will make customers use their personal and business data more willingly online. And if the next level of security isn’t timely granted, you may as well be looking at a multitude of court cases.
The importance of big data in e-commerce mustn’t be underestimated. It is surely among the main drivers of the modern e-commerce market, enabling capabilities that boost the performance rates in companies small and large, with any type of workflow and purpose. What is the ultimate future of big data?
We can already say for sure that the technology is looking at significant upgrades all across the board — the next generation of big data will provide more depth and preciseness to data analytics, more security for sensible data storing, and more convenience for both providers and customers in the e-commerce niche.
With that being said, you should definitely pay attention to this and related technologies if you want to keep in line with the relevant tendencies of modern e-commerce. If you have a project in mind (or already in blueprint), contact NIX United to hire profiled specialists that will help you reach the best results.
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As we can see from the examples of hugely popular market players employing big data for commercial purposes, the technology can find many uses in the industry. The most relevant ones include customer behavior data analytics that helps tailor products and offers according to exact demands and desires, customer support automation, intelligent recommendations (which works great for cross- and upselling practices), and payments security reinforcement.
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Global and local e-commerce sectors generate huge amounts of data across multiple data segments. This includes standard registration and order information as well as a bit more complex data assets related to user behavior and metrics tracking. Thus, the main source of big data is customers that cooperate with providers, followed by lots of internal data assets (related to supply chain management, inventory management, etc.).
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In a nutshell, the main trends of using big data in e-commerce are focused on expanding the functional capabilities of the technology through combination with other progressive tech concepts, its wider accessibility, and more opportunities in terms of personalization, data security, and predictive analytics. The technology is looking at some major merges with IoT, AI, and others.
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Big data is more than relevant in the niche of e-commerce, and this is well proven by the market names actively employing the technology. Namely, these are Amazon, eBay, Alibaba, Walmart, Etsy, and many others.
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