Have you ever noticed how when you perform a Google search for a specific type of product, you start to see the same kind of goods in adverts from other businesses the next time you log in to your social network account? This is not by chance, but rather one of the outcomes of eCommerce marketing’s use of big data.
The rise of big data analytics is the new frontier of innovation and competition in the global eCommerce sector. This is also paving way for businesses to embark on their digital transformation journey. One of the key findings from the Global DataSphere forecast states that the amount of data created over the next three years will be more than the data created over the past 30 years, and the world will create more than three times the data over the next five years than it did in the previous five.
How is big data helping businesses?
To grow, every company organisation, large or little, requires useful data and insights. Big data is critical for having a deeper knowledge of your target audience and client preferences. It even assists you in anticipating their requirements. Data that is successfully presented and thoroughly examined can assist a company in achieving a variety of objectives.
Businesses are utilising current technology to harness the power of data science as data quantities continue to grow. Enterprise Data analytics services are being used by eCommerce enterprises to gain a better understanding of their customers and their shopping habits. They can customise all of their marketing efforts to their customers’ tastes, train staff on specialized customer service strategies to meet their customers’ wants, and create goods using the data they collect and analyse.
Let us have a look at how big data analytics has changed the eCommerce industry and will do so for the years to come:
#1 Improvement in customer analysis
You can sell your things more easily if you understand how clients think and what they want. Big data enables eCommerce business owners to have a better understanding of their consumers’ wants and needs, as well as which products are trending online and how to make their products more popular and improve sales. You can cater to the needs of the customers and stay ahead of the competition if you have this information.
In today’s world, social media has become a huge part of our lives. It affects not just the social aspects of human life, but also the commercial world. It can be utilised not only by business owners for marketing but also for analysis and sales improvement. In the years to come, businesses leveraging data analytics services companies can certainly benefit in areas like website optimization, sales, production selection, product placement, and advertising just to name a few.
#2 Impeccable customer service
Providing outstanding customer service is critical in the eCommerce market. Customers should be able to reach you as easily as possible to solve problems or ask questions. Poor customer service causes the majority of eCommerce customers to abandon a brand or website; whatever you can do to improve the UX will benefit your business. In the wake of the COVID-19 outbreak, as more and more customers are moving to online shopping, the push towards digital transformation during the pandemic has accelerated. Businesses must use big data to examine key indicators like how long it takes a customer to reach out to your customer care department or how long it takes for an email query to be answered.
Keep track of client satisfaction and delivery times. If you notice any issues or areas of improvement of your customer service, devote extra resources to this area and keep a close eye on it. Data analysis in customer services can help you better understand your customers’ wants and expectations.
#3 Personalized shopping experience
When it comes to providing a more personalised purchasing experience for customers, eCommerce enterprises are light years ahead of brick-and-mortar establishments. Providing a personalized shopping experience can be one of the major considerations in a digital transformation strategy. As a customer, it’s convenient when the retailer already knows what the customer wants and they don’t have to waste time selecting the services they require.
Big data makes it much easier for businesses to keep track of their users’ browsing history. Companies can quickly examine a customer’s preferences this way. Advertisements or emails sent out regularly to remind clients of tailored services can be used to customise product marketing. Numerous companies in the US offering enterprise data analytics services are helping businesses offer personalized shopping experience to their customers using big data.
#4 Streamlined operational activities
The use of big data resources has the potential to increase operational efficiency and processes. Algorithms that analyse client behaviour and shopping data can greatly assist operational processes. Predictive analytics can also be implemented using large data. eCommerce enterprises can also use big data algorithms to analyse market trends and supply networks. This component is particularly useful in determining the ideal inventory levels that warehouses should maintain for more efficient operations.
Here’s an example of how a digital transformation agency can help a business in improving its operational processes: Big data can be used to track customer activity, shipping information, and personal information. After that, the company can leverage big data and IoT to connect with manufacturers and track inventory to ensure that all orders are delivered on time.
#5 Jump in cross-border sales
People love to buy all over the world, and big data has allowed eCommerce companies to be more accommodating to adjacent countries. Big data can tell you where your items are competitive or unique based on the products you’re offering, and you can start selling them in that market.
#6 Provide more secure online payment options
Thanks to big data analytics, online payment operations are more secure. Companies employ big data algorithms to detect financial frauds and ensure secure payment on their websites because big data algorithms are adept at evaluating large volumes of data.
Large data resources can be used to facilitate machine learning techniques. These algorithms sift through billions of transactions to spot possibly fraudulent ones. Furthermore, big data may be used to determine which payment options are the most effective and popular among clients.
Companies are using data analytics services and solutions to analyse their customer satisfaction using a variety of measures and working hard to provide excellent client services and experiences. The ultimate purpose of organisations using big data resources is to delve deeper into the insights supplied by the data, not the data itself. To excel, you can extract the crucial pieces of information that will help you with big data technology.