Using Big Data in E-Commerce: How Big Data Improves eCommerce Customer Service

Founding an e-commerce store is an amazing idea: no connection to a place, no need to pay rent, and access to sales worldwide. Customers think so, too, and that’s why it is expected that there will be 2.14 billion digital buyers bringing 6.54 trillion in profit in 2023. However, you are not the only one to think that e-commerce is genius, especially with the pandemic hitting offline businesses.

Competition in e-commerce is huge. In fact, only 1 percent of e-commerce decision-makers say that there is no competition on the market, with 49 percent claiming that the competition is very tough. Therefore, marketers pay millions to get into shoppers’ minds and find out what they need to do to boost their sales.

And there is a way to do this. You may provide personalized goods and services to each client by analyzing his preferences with big data! According to “The 2017 State of Personalization Report,” 71 percent of U.S. consumers experience some level of frustration after an impersonal shopping experience. The report has also revealed that 44 percent of consumers are likely to become repeat buyers after being exposed to a personalized shopping experience with a particular company. 

So, e-commerce businesses need to integrate big data to provide consumers with a personalized shopping experience in order to stay competitive in the current market.

Find out what big data is, why you should start using it right now, how big data enable personalization in ecommerce, and in which ways it impacts customer experience and the e-commerce market overall.

What Is Big Data in E-Commerce and Why Do You Need It?

Finding the patterns in customer behavior is extremely difficult because every person is unique and has individual triggers for everything. Yet, on a larger scale, we are not that unique after all. And to get on that larger scale, big data is needed.

Big Data Definition

Big data is defined as enormously large data sets that businesses analyze to reveal complex behavioral patterns. It is not only about addresses and names but data from social media, geolocation, web browser histories, and all kinds of clicks on your e-commerce site. That is what makes big data big, but so much more useful at the same time.

Industries That Utilize Big Data 

Big data comes in handy in various industries, including the following:

• Banking and Securities
• Communications, Media, and Entertainment
• Healthcare Providers
• Education
• Manufacturing and Natural Resources
• Government
• Retail and Wholesale Trade
• Transportation
• Energy and Utilities

In the e-commerce business, big data is being utilized to the greatest extent because there are many unpredictable and complex things in this field. With trends and desires changing so fast, many e-commerce businesses cannot adapt on time and get kicked out of their niche before they can even figure out what has gone wrong.  

The Role of Big Data in E-Commerce

The ecommerce business using big data can analyze what trends and needs are, and predict how they will change and when. It gives you a competitive edge in the ever-changing and growing industry.

Big Data Market Worth 

Actually, 53 percent of companies already use big data for their needs, and 38 percent plan to do so in the future. Also, according to IDC, the value of the big data industry grew to $189 billion by 2019 and is expected to reach $247 billion by 2022. It is no wonder, since big data helps businesses worldwide to rearrange their methods to meet customer needs, boost sales significantly, enhance customer experience, and maximize their revenue. 

The Benefits of Using Big Data in E-Commerce

E-commerce can totally reshape the way you think about your business. Online retailers have never seen so many opportunities to get a glimpse into what customers are like outside the shop. However, let’s break this generic statement into five main benefits that big data in e-commerce has to offer:

Boosting Sales

The big data of ecommerce offers a lot of room for improvement, targeting the right audiences with the right advertisements, acquiring new customers, providing better customer experience, and more. All of these lead to a boost in sales and revenue growth. 

Optimizing Prices  

Price is important to customers: 18 percent describe it as the main factor when making decisions about buying products, and 47 percent put it in their top three. Customers do research to find the best price-to-quality ratio. You have to offer the most optimal and well-optimized prices, especially in today’s reality, where there are a lot of similar products being sold online. In order to do so, you have to become a data-driven business to adjust prices to the market. 

Moreover, prices drop and rise constantly, and you have to readjust your prices accordingly to avoid losing money or customers. Big data offers you a real-time situation so that you can react as quickly as possible.

For example, Amazon uses the dynamic pricing approach that automatically analyzes the data about competitors’ prices, the customer’s willingness to buy, and available inventory to make an informed decision on the item’s cost. Amazon changes product prices about 2.5 million times daily in order to serve the company’s and customer’s needs in the best way.

Improving Product Research

If you plan to launch a new product on your e-commerce platform, conducting profound product research would help you make a well-informed decision. By analyzing customer behavior and preferences with big data, you would be able to answer the following questions:

• Would a product be successful?
• What is the best way to manufacture or source the product?
• Who are your competitors? 

After analyzing these aspects, you would know how adding a certain product to your assortment would influence the overall performance of your
e-commerce business.

Meeting Customer Expectations

Customer service receives a lot of complaints, questions, and reviews of the products that are essential for businesses. However, knowledge transfer does not happen. Customer service keeps getting the same questions and complaints, and no one does anything to add frequently-asked questions or fix the products or a website.

Companies using big data in ecommerce gather and analyze information on every kind of feedback — in emails, on social media, or from chats with customer service — all in one place to see a big picture of what should be changed and improved. It is not a secret that better products attract more customers.

Making Better Decisions

Without seeing a real-time picture, we just blindly try everything out until something works. It may cost your business a lot of money, and when you finally find the right decision, it can be too late. With big data, it becomes pretty obvious which decision is the right one. 

If sales are not going well, you can analyze every step of the customer journey and see where things start to go wrong. No more guessing — look at solid numbers, analyze them, and get your decisions ready. 

Source: paymill.com 

How Big Data Improves the E-Commerce Customer Experience

You are probably willing to learn how exactly you get all these benefits. But what are exactly the ways ecommerce marketers collect big data and analyze it afterwards?? We’ve got you covered — here are seven tips for making your e-commerce business successful with big data.

Analyzing the Shopper’s Behavior

While building a customer journey and buyer personas, we can assume a lot, and these assumptions do not really fit into reality. However, big data is about a different approach to shopper analysis. It gathers information and, based on it, marketers generalize it, put it in several categories, and go from there to better engage with customers. So instead of imagining how things work and then trying different approaches, they take into consideration the current state of affairs and find approaches that might work for this or that customer or their journey. 

Basically, retailers get to know such information as gender, location, age, preferences, etc., and shape the business according to this data.

Improving Customer Service 

In 2018, 62 percent of customers contacted customer service in the United States. This fact makes it clear that businesses should make it their priority to improve customer service in ecommerce using big data. Fifty-six percent of people worldwide dropped their connection with a business because of poor customer service, and this means that customer service has to be good if you want a good retention and customer loyalty rate. 

The question of what makes good customer service is asked way too often. It turns out that measuring the “good” is done with big data. You gather feedback from the customers, and measure speed, abandonment rates, net promoter score, resolution time, and other metrics. This is the ultimate way how big data improve ecommerce customer service: you can find out whether you need to improve the team and what the problem is exactly. Measuring the quality of customer service with big data can help you boost your revenue by 4–8 percent. 

Personalizing Customer Experience

Businesses can boost their revenue by 15 percent through personalization alone. But how can you personalize the shopper’s experience if you do not have direct contact with them, as in physical stores, and your target audience is way too diverse?

Here comes big data as well! Here is how big data help in ecommerce personalization:

• categorizing customers
• sending customized emails 
• personalizing subject lines (such emails are 26 percent more likely to be opened)
• creating different ads for different target groups 
• up-selling or cross-selling 

Revealing Upselling and Cross-Selling Opportunities

Upselling and cross-selling have a great impact on sales. According to Marketing Metrics, the probability of selling to an existing customer is 60–70 percent, while the probability of selling to a newly acquired prospect is only 5–20 percent. So, you will want to get everything you can out of the existing customer. 

• Big data helps you to analyze whether a customer is able or likely to go for upselling, and what they will buy in addition to what they have already put in their cart. 
• You can cross-sell by getting information about customer browser history or suggesting goods that other customers buy with this product. 

Overall, you will be able to respond to the individual needs of your customers, which increases the possibility of selling online. 

Monitoring the New Tendencies

Big data gathers results from the browser history, social media searches, and reviews, and helps you to analyze historical data. You will know immediately if your customers start to buy or search for some product frequently, so you can create an alternative from your brand. Find out the most popular colors, materials, and functions as well to hit just the right spot of customer’s needs. 

It is obvious that other factors such as weather, holidays, and events affect sales, and tendencies as well. With big data, you will be able to determine exactly how these factors change customer behavior so you can be ready with the right products and ads at the right time.

Managing Logistics

Logistics in e-commerce is quite unpredictable as well. The disconnect between supply and demand can cause losses of potential sales or excess products sold below market rates. In order to avoid these situations, use big data to forecast the market trends, and put a stop to the production and delivery of unneeded goods.

Source: bytekeen.com 

How Big Data Is Changing eCommerce

Big data in the e-commerce market globally was valued at $2.69 billion in 2019 and is forecasted to reach $6.2 billion by 2025. So, let’s take a look at how the popular e-commerce brands are already reaping the benefits of big data.

Aldo Case – Dynamic Customer Service

Aldo, the Canadian luxury shoe retail brand, has leveraged the power of big data and found out that shoppers often wish to try products on before making the purchase. So, Aldo decided to have beacons that detect when a person is near their offline store and send notifications to their device inviting them to look at a product they viewed online. 

How Does Big Data Influence Aldo?

Implementation of such an omnichannel approach has led to the offline stores acting more as showrooms and caused a 131 percent increase in conversions to sales from store visits.

Amazon Case – Personalized Recommendation System

Amazon is a leader in applying a collaborative filtering engine (CFE). CFE is a method that analyzes the preferences of a group of shoppers with similar behavioral patterns and recommends products based on this analysis. For example, Amazon suggests reviewing phone cases and phone chargers after a shopper purchases a mobile phone. 

How Does Big Data Influence Amazon?

By using the power of big data, Amazon encourages impulsive purchases, so no wonder that in 2018 Amazon was generating 49.1 percent of all online retail spend in the United States.

Groupon Case – Analyzing a Terabyte of Data per Day

Groupon is an e-commerce platform that gives its subscribers access to discounts on a wide range of products and services. To provide its users with a personalized customer experience and offer them the most relevant discounts, they use the power of big data.

How Does Big Data Influence Groupon?

Groupon analyzes over one terabyte of raw data on a daily basis to help identify trends as they emerge.

Our Experience  

Langate has cooperated with Bunddler to help them create a global multi-store web and mobile marketplace that connects online shopping assistants and shoppers who need their help. Our main task was to create a highly scalable and efficient platform that would meet all the modern e-commerce requirements, including high load, stability, and personalized shopping experience.

Langate developed a platform that has a catalog of shopping assistants with customer reviews and ratings, a list of coupons and deals in popular online stores, and a directory of online stores with descriptions translated into customer’s languages. With the power of big data, the system analyzes a shopper’s behavior to present him only with relevant sellers and products.

Such a custom application development helped Bunddler to achieve a high level of personalization and adherence to shoppers’ needs. As a result, Bunddler managed to gather an audience of 500,000 customers performing two million sessions per month.

Conclusion

Big Data has become an essential part of e-commerce business. It is no wonder, since they offer a variety of benefits such as sales boosts, better strategic decisions and product research, price optimization, and, finally, meeting and exceeding customer expectations. 

The phenomenon of big data is changing e-commerce as we know it. It enables companies to discover new ways to improve and personalize the online shopping experience. As a result, e-commerce platforms successfully serve shoppers’ needs while meeting business goals.

If you want to get access to all the benefits ofBig Data application development and have a competitive edge in the cutthroat e-commerce industry, do not hesitate to contact Langate. Our professionals have rich experience in managing big data and will offer you the best service possible at a reasonable price.