Updated: Jan 1, 2021
Today digital transformation reshapes shopping, online experiences, and even customer expectations of physical stores. The COVID-19 outbreak changed not only our everyday life but also the way of doing business. But by turning the world upside down, it also brought many technological innovations.
Being involved with software development companies, over the past seven years, we have found a number of technological trends having a future potential. This article describes seven tech trends that may extremely reshape the future of the retail industry over the next few years.
Trend 1: E-Commerce-Friendly POS Systems
During the COVID-19 pandemic, many business owners use e-commerce platforms trying to optimize online sales processes.
One of the SaaS providers of a cloud-based ERP solution for retailers shared his monitoring of the growing demand for a fully integrated POS and e-commerce solution. Excluding all the bells and whistles, retailers choose those e-commerce systems allowing them to sell online no worse than in physical stores.
If looking ahead, after the pandemic business owners having multiple sales channels, including both brick-and-mortar and e-stores, will need to sync both online and offline transactions, inventory, and promotions. Thus, e-commerce and POS integration will be an optimal solution both during and after the pandemic.
Trend 2: Machine Learning for Demand Forecasting
The important question many retailers are going to ask now is, “How will the world pandemic of COVID-19 impact customer demand and how to predict shifts?”
Since many retail businesses are looking to use big data, demand forecasting powered by machine learning became one of the innovative methods to optimize customer and supplier relationship management, logistics and manufacturing processes, and running smart marketing campaigns.
Compared to traditional forecasting methods, machine learning approaches are more adaptable to changes and faster to implement. This feature makes ML-based demand forecasting applicable to today’s reality.
By optimizing demand forecasting systems with NLP and cascade models, short-term POS data, and recent data from external resources (exchange rates, market states, economic factors, and others), it’s possible to enhance demand forecasting accuracy. That is what makes ML-powered demand forecasting become a valued contribution to smart retail.
Trend 3: Augmented Shopping
The isolation due to COVID-19 quarantine has rapidly increased the demand for AR systems. Being guided by the “try-before-you-buy” approach, augmented shopping attracts customers by allowing them to interact with products online.
Several brands embraced AR long before the pandemic. Lacoste, American Apparel, and Uniqlo opened virtual showrooms and fitting rooms to allow customers to try products in virtual spaces.
Apple’s LIDAR scanner launched not so long ago, has significant potential for augmented shopping and AR in general. Shoppers will be able to place virtual items on the physical surfaces with millimetric precision, close off virtual objects with real ones, recognize physical objects, and provide realistic interactions between real and virtual goods.
Trend 4: Data Science-Based Personal Interaction
Data Science and machine learning technologies have made great progress in today’s personalization tools. DS and ML-powered engines can make personal recommendations to customers before they know what they want themselves.
According to Amazon, 35% of its sales are driven by its recommendation engine.
Rather than annoy people to download an app, the recommendation engine uses incentives based on consumer desires and needs. By applying machine learning methods, the recommendation system collects information about similar customers and develops shopping profiles. Then, the system tailor calls to action to specific users and speeds the buying experience along.
In-store options are catching up to online and app-based ones quickly. The driver of this advancement is Bluetooth Low Energy and RFID, deploying low-power consumption solutions throughout stores.
Fashion AI, a technology built by Alibaba Group, generates personalized mix-and-match apparel recommendations for shoppers as they move around stores. They can then quickly find items that will fit their tastes.
And of course, it’s worth mentioning NLP-driven chatbots that are getting smarter day-by-day and deliver personalized experiences. Even outside the retail sphere, chatbots are expected to be the biggest word in customer service, offering deals and recommendations, providing easy navigation, and tracking orders.
Trend 5: Staff-Free and Cashier-Less Stores
Since social distancing is an efficient measure to prevent coronavirus infection, cashier-less and staff-free stores are expected to re-imagine the retail landscape. A provider of weighing technologies – Shekel Brainweigh Ltd. – surveyed customers to identify shifts in shopping habits due to the COVID-19 pandemic. The survey revealed that 87% of customers would likely choose stores with contactless or self-checkout options.
Tools that will allow this digital transformation include RFID tags, computer vision systems, machine learning, IoT devices, and facial recognition.
Not so long ago, Amazon developed the cashier-less Just Walk Out system. It is powered by computer vision, sensor fusion, and deep learning, which allows customers to come to the store using a credit card. This system doesn’t require any account or app to be installed. Customers can put items into a physical shopping cart, while an IoT-based system tracks them in a virtual cart. When the shopping is completed, all purchases will be automatically paid once the customer leaves the store.
The underlying technology of the Just Walk Out system is the Amazon Go Grocery model. Including RFID and Bluetooth, this model can perform check-out free shopping experiences. But taking it one step further, it’s also possible to develop a touch-free shopping system. By scanning bar codes and QR codes, customers can receive information about desired products through a smartphone, thus, reducing direct interactions in-store.
Trend 6: Voice Commerce
Artificial intelligence and NLP are dynamically progressing year by year. And now we have Alexa, Bixby, Siri, Microsoft Cortana, and Google Home Assistant. No need to open any screen-based app or browser to interact with voice assistants – these smart applications can understand your speech and react to the sound of your voice.
The survey made by NPR and Edison Research showed that 60 million people now have at least one smart speaker system at home. Thus, we can expect to see many more products that will bear the label “Alexa-enabled.” The underlying idea comes from the Internet of Things products like smart mirrors, which engagingly deliver varied content.
In retail and e-commerce, voice-assisted technologies help to make sales through voice recognition technology. It’s called “voice commerce” now, which concept is close to e-commerce. But instead of typing in a search query, customers use voice commands to find products or any required information.
Driven by voice recognition technology, Walmart created the Walmart Voice Ordering service. The technology concept is simple – you can place orders by using voice commands. Customers can use any devices and platform powered by Google Assistant or Siri. Everything you need is to say: “Hey Siri/Google, add to Walmart,” and add products to the cart by naming them. Once the order is placed, Walmart workers gather selected items and deliver by the method you have chosen when placing the order.
7-Eleven Inc. launched a Voice Ordering feature to their 7NOW Delivery app. By using Google Assistant or Amazon’s Alexa, customers can open a 7NOW app with the phrase “Hey, Alexa! / OK, Google! Open 7NOW.”, and place goods into the cart through the voice commands. Once the voice order is paid, customers have their products delivered within 30 minutes.