Forward-thinking retailers are using AI to transform the customer experience. Here are five examples of innovative retail AI in action.
Technology is often seen as a disruptive force in the retail industry, a force that has contributed to the shift to ecommerce and the decline of brick-and-mortar stores. But where there’s disruption, there’s opportunity for forward-thinking organizations.
By making the most of new technologies like AI, machine learning, and deep learning, analysts predict that retailers will be able to cut annual retail costs by $340 billion by 2022, and increase profitability by 60% by 2040.
And it’s not just a future prediction. Retailers are already finding exciting use cases for AI that are transforming the customer experience and helping turn these theoretical benefits into real competitive advantages. Here are five examples of how AI is transforming the customer journey – from the manufacturing floor to the storefront.
Personalised shopping now in store
For years now, ecommerce sites have collected data on what users are buying (and what they’re not). This data is gold dust for any retailer, but it’s been suspiciously absent in brick-and-mortar stores. Until recently.
In 2017, luxury fashion retailer Farfetch launched its Store of the Future. One of the major technologies it houses is a smart mirror that uses augmented reality technology to help shoppers see how clothes would look in alternate colors and styles.
More importantly, these smart mirrors can send data back to Farfetch about what kinds of styles shoppers favor and what they choose to buy or leave on the shelves. By collecting this data and passing it through machine learning algorithms, Farfetch can predict and get ahead of upcoming fashion trends – while also offering shoppers a unique retail experience.
The rise of robot sales assistants
SoftBank’s telecom division teamed up with robotic manufacturer Aldebaran to develop Pepper: a robot that can fluently interact with people. Since then, Softbank has deployed Pepper to help greet, inform, and entertain customers in over 140 stores.
Using AI, image recognition, and machine learning technologies, Pepper has delivered significant benefits to retailers. For instance, apparel store Ave saw a 98% increase in customer interactions, a 20% increase in foot traffic, and a 300% increase in revenue after using Pepper in store.
Predictive analytics in manufacturing
AI isn’t just powering the modern store; it’s also becoming a mainstay on the manufacturing line and across the supply chain. By leveraging AI at this crucial production stage, brands can manufacture goods more efficiently to reduce the risks of running out of stock and leaving customers unsatisfied.
One example of AI in manufacturing is General Electric’s Proficy solution suite, which combines sensors and AI to help businesses extract, process, and use machine data to cut costs and improve efficiency.
By taking data from manufacturing equipment and passing it through AI algorithms, plant managers can get predictive insights into common equipment defects and issues long before they impact the production line.
It helps reduce defect rates and extend equipment life and gives managers all their insights through a single dashboard – so they can focus on keeping the manufacturing line at peak productivity. And for customers, the reduced defect rates lead to a greater likelihood of getting high-quality, satisfying products – building trust and reducing the need for frequent ecommerce returns.
Smarter, faster ecommerce order fulfilment
AI can help process warehouse data at high speeds, but it can also do much more. As part of the EU-funded SecondHands project, British online grocery retailer Ocado is applying machine learning to develop humanoid robotics that assist maintenance technicians and accelerate order fulfilment.
Powering its robotics AI with NVIDIA GPUs, Ocado is implementing advanced computer vision so warehouse robots can automatically classify images and identify products. These two capabilities mean Ocado can fulfil orders without having to rely on manual barcode scanning. This ensures orders are filled faster and more consistently—helping deliver a better, more consistent customer experience.
The future of delivery
Autonomous delivery is hailed by all kinds of ecommerce retailers as a cheaper, faster, automated alternative to human delivery. Now it seems the fast food industry is coming to the same conclusion, with the on-demand delivery company Postmates prototyping a delivery robot powered by AI and the NVIDIA® Jetson AGX Xavier™ module.
AI touches almost every part of the Domino’s Robotic Unit (DRU). From managing temperature across compartments to keep both cold and hot items at their best, to mapping routes and navigating hazards, artificial intelligence powers all kinds of features in DRU prototypes.
It all adds up to a home delivery future that puts an even bigger smile on customers’ faces. And one that helps restaurants keep delivery costs down.
The future of retail looks bright with AI
From enhanced consumer engagement to smart stores and warehouses, AI will help retail improve a vast array of processes and systems, cutting costs and improving profitability. But while AI promises much, retailers must understand what’s needed to take advantage of these opportunities.
It requires technology designed specifically for AI with the compute power and speed necessary to drive real-time insights, consumer engagement, and autonomous machines.
Partnering with one leading compute provider can get you the kind of foundation you need to use AI. Partnering with two providers helps you run AI and outmaneuver the competition.
That’s exactly what you get with NVIDIA GPUs and Google Cloud. With the Power of Two, you can benefit from exponential gains in power, innovation, and competitive advantage.