These are dark times for retail. The second wave of the COVID-19 has hit Europe, and many countries have started to implement a second lockdown to combat the highly infectious virus. A complete lockdown has forced people across the world to shop online for everything. Supply chain disruption made people rethink their buying behaviour. In India, for the longest period of time, only essential items were available. It compelled people to understand the value of frugal living for a couple of months. This, coupled with the economic uncertainty arising from the loss of jobs in several sectors, did not bode well for the retail industry.
The boom of e-commerce caused brick and mortar stores to struggle for survival, leading many to shut down shops completely. With the sudden lockdown that was extended for a significant period, a huge waste of inventory became an immediate reality. It is harder to ascertain the extent of damage caused because much of the retail segment is unorganised.
If there is a lesson to be learned from this pandemic, it is that, in order to survive, the brick and mortar stores should turn to artificial intelligence. The integration of innovative solutions in their business plan would help them thrive in these difficult times. AI helps in knowing the customer and helps a retail store provide a personalised experience.
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AI-Powered Solutions: Have The Right Inventory. At The Right Place. At The Right Price.
Artificial intelligence-based Video Analytics solution can provide insights about shoppers, employees, assets and activity within the premises. Computer vision solutions can be plugged into existing CCTV networks and do not require infrastructure overhaul.
An AI solution provides demographic details about the customer like age and gender. This data is correlated with insights about the time spent in the store. Peak time walk-ins, average time spent by shoppers and the percentage of non-conversions can help the retailer in gaining a better understanding of their consumers. Heat maps on areas most visited would also help stores in better design of display counters/racks. Smart cameras alert the store manager in real-time about stock-outs, thereby creating a good consumer experience. The customer won’t have to go to the counter and enquire about a product or in some cases- stop frequenting the store because the required item is not on display.
Computer vision solutions are now being deployed in department stores, warehouses, malls and smaller stores. AI solutions are particularly helpful for stand-alone stores, small cafes and restaurants, salons and boutique stores that often have employees with high attrition rates. AI can provide details about the customer to any store staff that logs in the system, helping them provide the same level of personalisation that a repeat customer looks forward to. Facial recognition technologies are now also being deployed to find out about the emotional experience of the customer as well. The advent of iPhones with Face ID made people comfortable with the idea of being scanned for financial transactions. Many stores are experimenting with providing a more personal shopping experience to the customer based on accurate profiling done by AI.
Cyberlink’s smart retail solution, FaceMe, helps them identify VIP customers and shoplifters by running facial recognition against a database. The staff gets a notification about a VIP shopper, helping them provide a better shopping experience. It also provides a blocklist marking system that can identify people with a shoplifting record. When the camera recognises a blacklisted person, the staff and security are alerted immediately and act according to a predefined protocol.
Showrooming is a trend where a shopper will check out a product in a retail outlet and buy the product online. Often, they will search online portals to find out the cost of the same item and delivery timing. If there is too much of a price difference and a short delivery time they will prefer to buy it online. Using AI and Electronic shelf edge labels, a retailer can have dynamic pricing in the store. Machine learning algorithms can utilise information on competitors and help a retailer automate setting the price of each item. A retailer can choose slash rates, introduce promotions and bundle products to ensure that a customer buys a product when in-store. Machine learning algorithms can detect patterns based on past data and predict the best price.
The reason no one pays attention to promotional messages is that they are targeted at a wide demographic and often bombard people with useless information about objects they are not interested in. A retail store using AI and facial recognition can understand its customers better and promote products that are already being used by the customer and suggest products that they will most likely buy. A retail store that gives limited but specific discounts, personalised to each customer has a more chance of being frequented and achieve higher sales also.
The future has many unknown variables. Retail stores will thrive only if they are able to adjust quickly and give the customer an experience they will not forget. AI models become better at prediction, according to the data fed to them. The customer will start to expect the highest level of personalisation and a faster shopping experience catered to him. For survival, the real and virtual need to come together to create unique shopping experiences that the customer loves to go back to. A retail store has to embody what’s missing in online shopping — the experience and joy of shopping. It can create an environment using the right colours, lighting, aromas and provide interactive elements across the shopping space. This creates a win-win situation for everyone as happy shoppers shop more.