In-built facial recognition and natural language processing
(NLP) capabilities enable a fleet of virtual agents to greet shoppers personally, provide directions and anticipate orders. Machine Learning
(ML) personalises promotions to match shoppers’ current mood and past spending preferences; in-store beacons send offers to their smartphones as they navigate through the store. Computer vision with deep learning identifi¬es items added to the shopping cart. Adding data through sensors, Artificial Intelligence
(AI) allows non-stop checkout and automatic payment
with autonomous drones completing last-mile delivery at shoppers’ doorsteps.
As whimsical as these innovations may sound, none are hypothetical. These technologies are being tested for roll-outs in the coming few years. For those that believe Intelligent Automation
is just a hype, consider that 85 per cent of transactions in retail will be managed by IA
technologies by 2020.
Retailers are not only leveraging Intelligent Automation
(IA) technologies to create retail stores of the future, they are beginning to apply Robotics Process Automation
(RPA), ML, NLP
and AIin major functions across the value chain? supply chain, marketing, finance and customer experience. The use of IA
in retail can generate compelling benefits. First, it helps retailers make smarter decisions, with accurate and real-time forecasting. Right forecasts can help optimise supply chain, design impactful marketing campaigns, and improve assortment and pricing for better customer experience. Second, IA
can make operations more efficient, thanks to a combination of automation with process optimisation. IA
can aid companies in increasing average spending-per-customer by reinventing shopping experiences.
‘Digital-first’ companies including e-commerce players have set the ball rolling by capitalising on huge data collected online and massive AI investments to predict trends, improve inventory forecasts, automate customer operations and offer targeted marketing. Some plan to go a step further and fully pre-empt customers’ orders and ship goods without waiting for a purchase confirmation. Traditional retailers, on the other hand, are taking advantage of best of both the worlds — brick-and-mortar stores and their online experience — to develop intelligent retail technology that catapults sales, transforms retail operations and customer experience. But before we delve on who will be the winner, let’s explore powerful use-cases where IA
investments have the potential to create value in the retail ecosystem.
Warehousing and distribution are ideal candidates for IA
can help reduce logistics complexities by ensuring the right product-warehouse mapping. Robotics help transform operations at distribution centres and improve order pickup accuracy. Retailers are already using ML to optimise the delivery routes for home deliveries to customers. In store, ML-enhanced RPA can help optimise merchandise and minimise stock-outs by collating and cleansing historical sales information (from multiple ERP platforms) and subsequently, create new forecasts for better demand planning.
can also help retailers predict future store performance and understand profitability drivers when picking a new location for expansion.
Rising smartphone penetration accentuates the need for seamless experience between what customers do online and what they do in stores. IA
can help update, optimise and tailor that experience for each shopper in real time. IA
can be the keyto marketers trying to reach hyperconnected consumers who continuously seek more value by comparing prices online.
For instance, retailers send a discount code to shoppers’ smartphones as they approach a store, adding more based on how long the shopper stays. The discount and merchandise to offerare determined by AI program that is able to predict what the customer will like based on data (past purchases, age, web browsing etc.). This kind of insights-based selling,including personalised promotions, optimised assortment, and tailored displays can help drive sales. In store, virtual assistants could identify customers, analyse them to make intelligent recommendations, all this while communicating in a conversational way.
can help deliver service on time and at lower cost. Offline retail provides convenience to customers however it also puts burden of transactions — keeping stock updated, billing, returns and interaction with suppliers. These transactions involve several hand-offs as well as significant time of the staff. Deployment of IA
across transaction chain will allow companies to focus their staff’s time in more customer analysis and interactions. Off-line retailer can offer similar experience to its suppliers and staff as an on-line retailer currently offers and driving efficiency in operations.
Keeping up with the competition in this retail revolution is as challenging as it is rewarding. There is no ‘winner takes it all’ in this race. Success will hinge on evaluating a good fit? Design a system that solves the problem at hand, while taking into account the process, its maturity, existing skills, maintenance requirements and data sets. Shifting to a collaborative mind set will be the need of the hour. Partnerships within the ecosystem (retailers and suppliers) and cross-industry (banks) will evolve to improve supply chain, operations, finance processes and marketing and create better customer insights.
(Views are personal)