The continuing growth of e-commerce across the globe means that competition is rising among retailers, sellers, and online shopping platforms, among others, in retaining their respective customers and gaining new ones.
Some of the parameters of effective online selling such as excellent products, above-average customer service, and perks (such as free shipping, discounts, etc.) are still very important. But if an e-commerce business wants to really stand out, then looking at and carefully studying “big data” becomes necessary.
One of the most practical uses of big data is that it can allow e-commerce businesses to actually have a pretty accurate “prediction” of how an individual customer might behave, particularly when it comes to personal preferences and purchasing decisions.
Big data thus is a very important tool if an e-commerce business truly wants to get a leg up on the competition.
What is big data?
First, let’s define big data. If we can simplify its meaning, ‘big data’ basically means huge amounts of data that will be difficult to manage if you are using old or traditional data analysis and data management tools. One major characteristic of big data is that it continues to grow exponentially in volume and complexity, thus, basic database tools might not be sufficient to “process” big data.
So how do companies usually handle big data? There are quite a few processes that need to be done: data capture, data storage, data search, and data analysis, among others.
How “big” is big data? There really is no magic number to consider when it comes to big data. However, there are many examples that we can cite to show or paint a picture of what big data is.
One example that is often cited is the telecommunications industry. Here you have millions of subscribers. A telecom company might have personal information of its regular subscribers (particularly post-paid, monthly, quarterly, yearly subscribers, etc.) along with pre-paid subscribers who may have to disclose less information than post-paid subscribers.
On top of the basic customer information, big data comes in because the telecom company needs to track minutes of usage, the capacity of the mobile network, records of usage, logs or records on the telco’s servers or computers, billings, as well as mobile internet usage, including tracking of websites, e-wallets, mobile and online payments, etc. Tracking, analysis, and monitoring are often done on a regular and real-time basis.
Put all these processes together, and we can have a clearer picture of the amount of data that telcos handle every single day, 24×7, and 365 days a year.
Most of today’s businesses define big data based on a few criteria, including volume, variety, velocity, veracity, and value. These categories may sound technical, but let’s try to simplify them. “Volume” basically is the size of the data, and although there is no “magic” number or figure, big data is “big” once traditional software applications or other tools can no longer process the volume of data. When we speak of “variety,” we are looking at how diverse and how complex data is. Data can be audio, text, video, etc., and may come from different sources, including social media, business transactions, etc.
“Velocity” means the speed at which data is processed and the capacity of today’s companies to process data. In terms of e-commerce, an example would be how fast can an e-commerce platform process millions of millions of sales on a daily basis?
Next is “veracity,” which simply means the quality of data. Is there useless information (or “noise”?) How do companies determine useful and useless data? How can a company take advantage of “quality” data? Last is “value,” which simply means the value that companies can give to customers from the data gathered.
Big data and e-commerce
Now that we have a clear picture of what big data is, we can see that it can also be an important feature when it comes to e-commerce.
For an e-commerce website, information such as visitors’ profiles, log-in times, duration of visit to the website, browsing behavior, page views, unique visits, etc. all need to be tracked and studied.
By analyzing these data sets, you can then have a pretty accurate prediction or idea of the behavior or tendencies of your customers.
We can only imagine how powerful big data is because now you can also have that valuable insight into what products will likely sell, what customers prefer, and what customers expect.
Having a feedback mechanism also allows an e-commerce company to react, enhance, and improve customer services.
You can narrow it and refine it further, and through data analysis by comparing data using comparison charts, an e-commerce company can personalize its products and service to fit individual customers (but more on this later.)
Advantages of big data in e-commerce
We’ve already discussed a few of the major advantages or importance of big data, but let’s take a deeper look at a few more:
- A 360-degree view
We’ve already discussed how big data can work in providing personalized services but it goes deeper. Personalization goes beyond what a customer might like, the services which will appeal to him or her, the websites or web pages she visited, etc.
A 360-view provides a much clearer picture of what a customer likes or dislikes. How do they interact on social media? How active are they on social media platforms, and do they have a social media presence? Are they likely to listen to celebrities on Facebook, Twitter, etc. when making purchasing decisions? What are their preferred payment options? Are they likely to “spread the word” if they are satisfied with products or services?
These are just a few of the insights that a retailer or e-commerce might be able to determine through big data.
Let’s look at an example. Say an e-commerce company sells shoes and slippers. Big data might come in handy to allow the retailer to know the customer’s shoe size, preferred colors, preferred style, etc.
By analyzing these data sets, an e-commerce company can then be proactive and make suggestions based on the insights into customer preferences. In a way, e-commerce companies can have an accurate look at what a customer may like, even before the customer knows it. Big data basically gives ideas on a customer’s motivations and interests, and from these, suggestions can then be made which will result in a positive reaction (or a sale) from the customer.
To some, notifications might be quite annoying. But to others, being notified of the latest shoe or slipper, or a sale, or a discount, etc. can offer convenience and can save time. Marketing efforts can also be further improved, such as email campaigns, and customized discounts for specific products targeted to a specific audience.
- Keywords and SEO
Knowing the web pages or websites, or sections (like product pages) of a website can also provide valuable insight for e-commerce companies. Big data allows companies to analyze what customers are looking for. Thus, companies can make sure to update these preferred product pages so that these products appear at the top, whenever a customer searches online. The key here is constantly updating web pages and using search engine optimization (SEO) based on customer insights.
Speaking of product pages, big data even allows companies to predict the reasons why a customer might not be clicking that “buy now” button, perhaps because of unclear product descriptions, long loading times (particularly for product images or videos, etc.). In a way, e-commerce companies can then have an insight into which landing pages or product pages are generating the most sales, and enhance these landing pages even more with keywords and SEO.
- Enhancing customer experiences
Aside from allowing e-commerce companies to predict customer shopping habits and requirements, big data can even go deeper and provide insights into customer service and satisfaction. E-commerce might already know what customers want, and when they want it. Customer feedback can be processed to know the level of satisfaction of customers and predictive analytics can even “predict” how customers will behave the next time they visit the e-commerce site. Data from the number of clicks per page, the number of products customers add to their shopping carts, and the average time customers spend before making a purchase, can all be processed through big data.
E-commerce companies can even customize rewards or subscription schemes to target a specific demographic or age group.
- Securing online payment
One of the main concerns of e-commerce or online selling is the security of payments. Rightfully so, customers are required to provide credit card numbers, e-wallet details, mobile phone numbers, etc. when making online purchases. Besides big data, it is essential to install an SSL certificate on the server. For example, you can choose a wildcard SSL certificate for to keep e-commerce payments secure.
Thankfully, big data can help in the area of security. Big data actually allows e-e-commerce companies to detect “unusual” payments that might be fraudulent. Big data can scour the payment histories and look for anomalous or suspicious transactions. For example, it is not very common that a series of different purchases to be made using a single credit card within a short time frame. This might indicate that the credit card is being used somewhere else and in different online stores. Another unusual scenario is when multiple payment methods are used by only one IP address.
“Hacking,” perhaps the most dreaded word when it comes to online payments, is always a threat.
Big data analytics can detect these suspicious transactions and immediately notify customers. Big data also analyzes a customer’s preferred payment method, and so anything out of the ordinary is often noticed. Aside from monitoring unusual activities, when it comes to payment, big data can also provide an e-commerce company to provide the most preferred payment method or methods that customers may want.
Trends in big data
Now that we have a few ideas of what big data is and how it works, let’s look at some of the encouraging trends in big data and how these trends might impact global e-commerce.
- Huge yearly growth—Industry experts expect big data in retail will grow at an annual rate of more than 35 percent. In 2020, it was reported that big data in retail grew close to $3 billion, from a mere $400 million in 2013. However, the overall value of global e-commerce reached $4 trillion in 2021.
- Zettabyte growth—The research firm IDC estimated that the “digital universe” will grow 61 percent to 175 zettabytes by 2025. To give an idea of how big a single zettabyte is, it is approximately equal to ”a thousand exabytes, a billion terabytes, or a trillion gigabytes.” IDC further predicted that e-commerce will get a large chunk of this digital universe, with information such as customers’ social media activities, geolocation services, web browser histories, and abandoned online shopping carts, among just a few big data sets within e-commerce.
- Personalization will be the key—Another industry report estimated that the current trends in big data are also already making a huge splash in global e-commerce. A whopping 86 percent of online buyers or customers now say that personalization plays a huge part in their purchasing decisions. A side note: it was reported that millennials make up most of the customers wanting personalization. This age group is also most likely to expect to receive personalized suggestions from e-commerce platforms.
- Big data is a necessity—It is believed that more than 90 percent of all purchases across the globe will be made via e-commerce in 2040. Thus, e-commerce companies need big data to prepare for the inevitable and these companies need big data to be able to cope with the rising e-commerce trends.
It is safe to say that big data is here to stay and will grow even bigger. The question then is how can e-commerce companies continue to take advantage of big data in order to keep up with the ever-expanding and ever-growing global e-commerce.
