Ecommerce, on top of being more convenient in many regards than brick-and-mortar retail, has an advantage because of its natural ecosystem of customer data. Meanwhile, physical retail suffers from a data deficit.
When customers shop online, they generate useful behavioral data that can be applied again and again towards actionable operational insights. These analytics are shaping ecommerce, changing the ways we engage with and target marketing to consumers.
But big data analytics can be complicated. Understanding the ways this data applies to ecommerce plays a direct role in how well you can build an ecommerce model that drives business growth long-term.
How big data is being applied to ecommerce
Big data is one of the most significant currencies of the modern age. This business tool has the power to reshape business processes and hone customer understanding to its finest point. However, the success of your big data application depends entirely on the tools and strategies you use in your ecommerce approach. Big data can be an unwieldy tool. Yet its application can make a world of difference in terms of marketing, inventory management, and even shipping efficiency.
In the aftermath of the coronavirus pandemic, the digital economy will continue to grow. For your ecommerce business, this makes generating and analyzing big data an absolute must. There are three areas this digital shift will require you to apply your big data. These are:
- Marketing campaigns
- Payment systems
- Artificial intelligence
Customers require a convenient and secure virtual transaction space where they can easily shop for what they need. The growth of the digital economy also guarantees that your competitors will be out there offering similar experiences. Big data, then, is the tool you need to empower these three systems to reshape your virtual store.
In marketing, big data is there to represent customer behaviors, challenges, and needs. From your website’s bounce rates to traffic sources, data will inform how and where your customers are finding you, as well as how they are engaging with your content. By analyzing this data, you can create more highly targeted customer personas derived from data rather than assumptions.
Additionally, the risks of the virtual economy require secure payment systems. This is another area where ecommerce businesses have had success in applying big data. Big data allows for the modeling of cyber attacks to produce insights into how better to protect online payment systems. This is one of the functions of AI tools coming to dominate the e-commerce space.
Artificial intelligence is the incredibly powerful function of a computer system to apply data points in executing functions that typically required human decision-making processes. Machine learning is an aspect of AI that learns the more data is fed into the system. Machine learning makes use of neural networks to derive predictive insights, and it powers everything from smart home systems to autonomous vehicles.
In ecommerce, AI and machine learning are allowing for the personalization of customer product recommendations, marketing strategies, and customer service tools like chatbots. All of these features make digital shopping a more ideal experience.
Ecommerce models for the future
The potential of big data is as vast as the information collected over the internet on a daily basis. Modern e-commerce businesses are using this data to restructure operations for new e-commerce approaches. Here are a few examples:
Brick and click
With the help of big data, classically brick-and-mortar retailers are supplementing their business operations with an ecommerce approach. These brick-and-click business models allow physical retailers to also participate in the data game, generating more accurate customer preferences through loyalty programs, omni-channel marketing, and online order fulfillment.
However, these models are only as good as the quality of the data you collect. Focus on quality over quantity to ensure you are making the most of your ecommerce insights.
Mobile accessibility
Modern shoppers use their phones all the time. Building mobile accessibility into your site — from page loading speeds to layout — is a great way to improve your ecommerce audience. Additionally, specially designed mobile applications are taking off as a popular tool for increasing both sales revenue and big data gathering.
With 50% of ecommerce traffic coming from mobile apps, this business model can mean a substantial boost to your sales. Meanwhile, the capabilities of mobile apps can lead to better quality data. Bluetooth Low Energy (BLE) beacons and other proximity features, for example, can lend valuable data insights to both brick-and-click operations and ecommerce mobile applications.
IoT insights
On the inventory and shipping logistics side of ecommerce, big data is also an invaluable tool in enhancing operational efficiency. The Internet of Things (IoT) brings connected sensors and monitoring equipment all into a connected network, giving businesses unprecedented transparency into shipping needs.
IoT devices collect vast amounts of data around operational processes. Big data analytics then come in to inform businesses where they can improve everything from inventory tracking to route management.
Driving future ecommerce growth
With business models like these possible through the application of big data, it is no wonder data is the foundation of retail in the modern era. These features have enabled companies to adapt to the complications of the COVID-19 pandemic while offering shoppers greater flexibility and choice. Ultimately, this led to a 44% growth rate in US ecommerce business in 2020 alone.
Big data gives ecommerce businesses the tools to streamline their operations, from marketing to shipping. Explore all the ways big data analytics can assist your own endeavors, then integrate big data to fit your business model.
Ecommerce, on top of being more convenient in many regards than brick-and-mortar retail, has an advantage because of its natural ecosystem of customer data. Meanwhile, physical retail suffers from a data deficit.
When customers shop online, they generate useful behavioral data that can be applied again and again towards actionable operational insights. These analytics are shaping ecommerce, changing the ways we engage with and target marketing to consumers.
But big data analytics can be complicated. Understanding the ways this data applies to ecommerce plays a direct role in how well you can build an ecommerce model that drives business growth long-term.
How big data is being applied to ecommerce
Big data is one of the most significant currencies of the modern age. This business tool has the power to reshape business processes and hone customer understanding to its finest point. However, the success of your big data application depends entirely on the tools and strategies you use in your ecommerce approach. Big data can be an unwieldy tool. Yet its application can make a world of difference in terms of marketing, inventory management, and even shipping efficiency.
In the aftermath of the coronavirus pandemic, the digital economy will continue to grow. For your ecommerce business, this makes generating and analyzing big data an absolute must. There are three areas this digital shift will require you to apply your big data. These are:
- Marketing campaigns
- Payment systems
- Artificial intelligence
Customers require a convenient and secure virtual transaction space where they can easily shop for what they need. The growth of the digital economy also guarantees that your competitors will be out there offering similar experiences. Big data, then, is the tool you need to empower these three systems to reshape your virtual store.
In marketing, big data is there to represent customer behaviors, challenges, and needs. From your website’s bounce rates to traffic sources, data will inform how and where your customers are finding you, as well as how they are engaging with your content. By analyzing this data, you can create more highly targeted customer personas derived from data rather than assumptions.
Additionally, the risks of the virtual economy require secure payment systems. This is another area where ecommerce businesses have had success in applying big data. Big data allows for the modeling of cyber attacks to produce insights into how better to protect online payment systems. This is one of the functions of AI tools coming to dominate the e-commerce space.
Artificial intelligence is the incredibly powerful function of a computer system to apply data points in executing functions that typically required human decision-making processes. Machine learning is an aspect of AI that learns the more data is fed into the system. Machine learning makes use of neural networks to derive predictive insights, and it powers everything from smart home systems to autonomous vehicles.
In ecommerce, AI and machine learning are allowing for the personalization of customer product recommendations, marketing strategies, and customer service tools like chatbots. All of these features make digital shopping a more ideal experience.
Ecommerce models for the future
The potential of big data is as vast as the information collected over the internet on a daily basis. Modern e-commerce businesses are using this data to restructure operations for new e-commerce approaches. Here are a few examples:
Brick and click
With the help of big data, classically brick-and-mortar retailers are supplementing their business operations with an ecommerce approach. These brick-and-click business models allow physical retailers to also participate in the data game, generating more accurate customer preferences through loyalty programs, omni-channel marketing, and online order fulfillment.
However, these models are only as good as the quality of the data you collect. Focus on quality over quantity to ensure you are making the most of your ecommerce insights.
Mobile accessibility
Modern shoppers use their phones all the time. Building mobile accessibility into your site — from page loading speeds to layout — is a great way to improve your ecommerce audience. Additionally, specially designed mobile applications are taking off as a popular tool for increasing both sales revenue and big data gathering.
With 50% of ecommerce traffic coming from mobile apps, this business model can mean a substantial boost to your sales. Meanwhile, the capabilities of mobile apps can lead to better quality data. Bluetooth Low Energy (BLE) beacons and other proximity features, for example, can lend valuable data insights to both brick-and-click operations and ecommerce mobile applications.
IoT insights
On the inventory and shipping logistics side of ecommerce, big data is also an invaluable tool in enhancing operational efficiency. The Internet of Things (IoT) brings connected sensors and monitoring equipment all into a connected network, giving businesses unprecedented transparency into shipping needs.
IoT devices collect vast amounts of data around operational processes. Big data analytics then come in to inform businesses where they can improve everything from inventory tracking to route management.
Driving future ecommerce growth
With business models like these possible through the application of big data, it is no wonder data is the foundation of retail in the modern era. These features have enabled companies to adapt to the complications of the COVID-19 pandemic while offering shoppers greater flexibility and choice. Ultimately, this led to a 44% growth rate in US ecommerce business in 2020 alone.
Big data gives ecommerce businesses the tools to streamline their operations, from marketing to shipping. Explore all the ways big data analytics can assist your own endeavors, then integrate big data to fit your business model.
Luke Smith is a writer and researcher turned blogger. Since finishing college he is trying his hand at being a freelance writer. He enjoys writing on a variety of topics but technology and digital marketing topics are his favorite. When he isn’t writing you can find him traveling, hiking, or gaming.
