Big data and Ecommerce
Businesses that value big data analytics indeed have a leg up on the competition. And eCommerce businesses by far out-pace their physical counterparts in benefiting from big data analytics. Here are a few reasons why:
- Ecommerce retailers are just a click away from the global market, with access to information that brick-and-mortars don’t have. From social clicks to mobile transactions, eCommerce generates an almost infinite amount of data from online customer activities. And as the E-commerce landscape expands with constantly changing consumer behaviour, so does the data it generates.
- E-commerce businesses are more agile and can respond faster to perishable insights from big data analytics.
Trends in eCommerce during the Pandemic
Following the COVID-19 pandemic, more people are connecting with eCommerce than ever before in the history of the internet. This is both good and bad news. Here are some emerging trends in eCommerce.
- Increase in the use of Artificial Intelligence-powered solutions
Self-service kiosks in supermarkets and video surveillance at airports are examples of how AI is integrating into everyday life.In eCommerce, more retailers are catching on, with over 77% of retailers planning to invest in AI and IoT by 2021. And with tech giants like Amazon and Microsoft investing heavily in AI/ML projects, AI is set to become the new normal. The pandemic may have even turbocharged those plans. As social distancing affects physical human presence, places like China and Russia, are deploying AI-powered robots to meet labour shortages. Shelf stocking, goods delivery and essential cleaning are a few examples of how these robots are being put to use.
- Increase in online shopping
With lockdown, businesses started experiencing record growth in pure eCommerce revenue. Most physical stores were forced to close and fully resort to an online presence. Many c
- Increase in price-savvy shopping
44% of consumers globally now compare prices across different stores more often than they did a year ago. 61% of shoppers say that price influences their decision to buy certain products.
- Increase in volatile demand for products online
With COVID-19, the world saw the demand for everyday essentials like toilet rolls and hand sanitisers skyrocket overnight. Market demand and supply chain conditions have never been ‘normal’, even in normal times. But the pandemic simply compounded an issue that was already complex, to begin with – the challenge of meeting the ever-shifting demands of customers.
- Increase in cybercrime
In the heat of COVID-19, the FBI registered a 300% increase in cyberattack reports while Atlas VPN also reported a 350% increase in active phishing websites within the same period.
How Big Data can help businesses in post-pandemic eCommerce
- Omnichannel Analytics
Would trends in eCommerce go back to normal as society weans itself off lockdown? Or is society now experiencing a new normal?
Whatever the case, AI/ML technologies will continue to help retailers seamlessly sell and service customers across offline and online channels. For example, a person can place an order to a virtual barista on the AI-powered Starbucks mobile app. The virtual barista relays the order to a nearby store so the customer can bypass long queues.
But AI is only as intelligent as the data it is fed, and the current limitation many retailers face is working with a smart data strategy. Businesses will find success in collecting quality data and investing in robust predictive analysis.
- Automated Demand sensing
To meet increasingly volatile demand, businesses need to foresee where demand will occur and efficiently stock the right quantity of products to meet this demand. Traditionally, retailers rely on historical data and market trends to predict and meet such demand. But one challenge with this approach is that such retailers cannot respond quickly to perishable insights.
Pairing big data analytics and AI/ML technologies with real-time data can enable retailers to be on the ball when it comes to rapidly changing demands.
- AI-powered Cybersecurity
With the pandemic, cybersecurity faces its biggest risks ever and the need for AI/ML technologies in cybersecurity has never been so urgent. While it was relatively easier to protect IT systems and employees within a secure IT environment, remote working took away that protection. IT departments have had to relax security protocols that prevent work-from-home employees from meeting work targets. And suddenly faced with a shortage of IT assets for such staff, BYOD (Bring Your Own Device) has become a hasty solution. These are just a few ways the pandemic has helped increase the attack surface for cyber threats. One can only wonder: is there a way businesses can proactively predict similar security emergencies and prepare adequately for them?
Machine Learning promises a way forward. Businesses can use advanced predictive analytics and quality big data to model potential cybersecurity scenarios and plan accordingly.
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