Post Pandemic Technology Trends to Change Retail Industry

1.
Trend #1: E-Commerce-Friendly POS Systems
Trend #2: Machine Learning for Demand Forecasting
Trend #3: Augmented Shopping
Trend #4: Data Science-Based Personal Interaction
Trend #5: Staff-Free and Cashier-Less Stores
Trend #6: Voice Commerce
Trend #7: Robotic
7 Post-Pandemic Technology Trends to Change Retail Industry ​0

2. Today digital transformation reshapes shopping, online experiences, and even
customer expectations of physical stores. The COVID-19 outbreak changed not
only our every-day life but also the way of doing business. But by turning the
world upside down, it also brought many technological innovations.
Being involved in software development, over the past three months, 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 our ​clients​, whose business is a B2B 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
sifts?” 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.
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3. 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
It’s a funny fact, but Gartner, who ​indicated​ in a 2019’s predictions report that by
2020 up to 100 million consumers are expected to use ​augmented reality​ in their
shopping experiences, ​was right.
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.
IKEA​ and ​Amazon​ are using ​ARKit​-based apps to help customers visualize what
new furniture will look like by moving their smartphone cameras around the
room in real-time.
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.
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4. 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.
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5. 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.
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6. 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.
Walmart and 7-Eleven's voice ordering systems are just one way how retailers
can enhance the customer experience. Smart speakers and voice commerce are
becoming more advanced day-by-day, thus, continuing to revolutionize the
future of retail.
Trend #7: Robotic
Cleaning, moving goods from shelves, tracking, and analysis of shelf inventory,
last-mile delivery - these tasks are not just for humans anymore. Robots, in
conjunction with artificial intelligence, are expected to help retailers cut costs
and improve store operations.
For example, autonomous last-mile delivery robots, like ​Amazon Scout​, will
deliver products directly to a customer’s door.
Aerial drones​ and ​shelf auditing robots,​ powered by AI-powered computer
vision, will scan and sense shelves, providing autonomous monitoring for
inventory management and pricing of products within the store.
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7. Customer service in-store robots, like​ LoweBot​ and ​Pepper​, will provide
personalized answers to questions, help to find goods, navigate customers
within the store, and even gather data for a better understanding of customers’
preferences.
Safety robots, like ​Millie​, will not only find and clean up spills but also alert about
safety hazards.
Computer vision and machine learning-powered robots, like ​SmartSight​, will find
any inventory issues and report about their location and nature to a human.
Many retailers will likely use robots in the future for the improvement of in-store
operations, a load reduction of store employees, and gathering data about
customers. Robots are well-suited for social distancing, which makes them the
right solution during the pandemic.
Regardless of what challenges the COVID-19 pandemic brings to us, we can think
about it as an opportunity for improvement. Maybe that’s the bottom line of any
problem.
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