Artificial intelligence is already widely available. Retailers worldwide are already putting the technology to great use to improve their businesses. A quick look at the retail industry shows how the capabilities of machine learning are helping retailers to understand their customers better, connect with them and createÂ superior customer experiences.
AI relies on a continual technological learning process that enables machines to continually adopt new, improved models based on data acquired and analyzed over time about specific subjects. It can discover and produceÂ actionable information about the business, its inventory, and customers â that is not usually obvious to the retailer.
There are lots of ways in which AI models are benefiting retailers worldwide. Here are some. Â
1. AI makes more informed consumer product recommendations using predictive analytics
AI can study customersâ behavior and come up with more intelligent recommendations to the consumers. While this is mostly a trial and error approach, the solutions couldnât be any more accurate. The technology learns what regular customers might be interested in based on data that it accumulates and evaluates over time.
Think of it much like the way online retailers would flag products similar to, or closely related to the ones youâre browsing through on their websites. The general assumption is that you might be looking for the products or services in the same range.
AI is refining this method into a fine art, relying on accurate and timely analytics and more criteria to make suggestions. It would, for instance, further consider necessary information that a sales assistant would ignore â such as the profitability of the product for the retailer and real-time product availability, and not just the consumerâs shopping or browsing history alone.
2. Consumer segmentation is easier, resulting in more personalized services
Customers have better shopping experiences where there is personalized service. The process addresses their specific needs more accurately, resulting in more satisfaction with not just the product but the shopping experience as well.
AI is convenient in this. It collects customer data and creates a broader and more complete image of the customersâ needs and preferences. This makes it much easier for the retailer to satisfy those requirements.
In a study, IBM recently revealed that consumers expect their retailers to provide them with personalized options, with 48 percent wanting such options online and 45 percent in store. Due to a large number of products available online, many shoppers rely on customised lists of products, especially inÂ specialized niches such as gaming laptops, to find the best recommendations. In this case, advanced AI would allow retailers to recommend the best gaming laptops automatically, without requiring additional research by the user.
The North Face,Â an outdoor apparel retailer, is an excellent example of businesses that apply artificial intelligence to offer personalized retailing. The company uses IBMâs question-answering computer system Watson to personalize shopping for buyers on its website.
The system has natural language processing capabilities enabling it to analyze a consumerâs responses to a series of questions to help them find the products they want.
eBay is another retailer thatâs making leaps in the AI direction to personalize shopping. The company uses a tailored shopping assistant ShopBot to help customers discover the best deals from the retail websiteâs many listings.
With these chatbots, customers can get what they want fast, while the retailer enjoys a quicker selling process and accelerated revenue.
3. Retailers can make more intelligent and accurate forecasting
Based on the data gathered, artificial intelligence models can develop far more accurate pictures of product types, quantities, and colors that are likely to sell within a given time. The technology analyses multiple real-time scenarios including customer behavior, fashion trends, weather and more that retailers can use to determine what to expect in future.
This is a significant departure from the previous scenario where retailers would make blind predictions based on intuition and past sales data. Still, most of this forecast would be purely focused on the quantities of products to stock.
4. Accurate and real-time stock monitoring
Since AI models such as RFID tagging systems can analyze different scenarios including customer behavior, fashion trends, and weather patterns in real time, it becomes easier for retailers to make informed decisions regarding their supply chain management.
The retailer can decide to automate every aspect of their inventory management since AI capabilities offer near 100-percent inventory accuracy.
Otto, a German web retailer, relies on AI to make accurate purchasing decisions by predicting what will sell within the next thirty days with a 90-percent accuracy. The company reports reducing the amount of excess stock in its stores by up to a fifth. Due to high accuracy levels, the retailer uses AI system toÂ purchase 200,000 items a month from third party suppliersÂ utterly free of human intervention.
5. Thereâs a significant reduction in labor costs for retailers
If the example of Germanyâs Otto above is anything to go by, then itâs clear that companies will have the ability to make better use of their human capital. However, letâs not forget that the implementation of Ai in retail will, first of all, create better user experiences.
Artificial Intelligence system works like the human brain to execute tasks more intelligently through constant learning; only it does it far better. Why? Because it has unlimited learning capacity and is not affected by tedious, repetitive tasks. This way, AI is likely to standardize tasks and perform enormous amounts of work that would have required a large number of resources to complete.
6. Facilitating customer purchases with retail virtual agents
There are some AI systems including chatbots and other sophisticated systems that are designed to interact more personally with humans.
This makes it possible to automate customer service, with chatbots currently in use to offer reliable customer service and support.
A lot of companies already use chatbots to help their customers make purchases just like a retail agent would. Examples of such companies include Whole Foods, Starbucks, Staples and Pizza Hut. This is particularly an area that holds much promise for the future of artificial intelligence since it provides room for the chatbots to track customer behavior to improve their purchasing experiences. One way to apply the data gathered would be to recommend products or services more accurately based on that information.
One company that has made significant strides in this direction is Niki.ai. Niki is a personal AI chatbot that simplifies customersâ shopping experience via chatting. More companies are working on developing proprietary chatbots and conversational interfaces that will significantly impact the marketing and retail process.
7. Image recognition
Artificial intelligence enables consumers to search for products online using images. Tagalys, CamFind, and Italian online retailer YNAP are some of the companies that have experimented with machine vision capabilities to enable shoppers to find products in their online stores by merely uploading similar pictures.
All youâd need to do is take a picture of a product and using your smartphone camera and upload to the internet via Google. The technology would recognize the image and search for the product online for you with all the details you wish to know.
8. Safety and security
One of the biggest threats any business or organization faces today is cyber-attack. The current defense against cyber attack involves being on the lookout always to anticipate what bad actors may do next. To make this possible, security experts must filter through and keep analyzing vast amounts of information that include computer usage at different times, user logins, and activity on system infrastructure. Given the determination of cybercriminals, these security measures are always vulnerable to infiltrations as people are unable to keep up with all the data.
AI, on the other hand, can handle any volume of data quickly, seamlessly and effortlessly on a nonstop basis. With the machine learning technology, AI systems can be trained to learn existing patterns and identify any deviation in it and report it in real time. Even better, AI can be trained to go a step further and improve its approaches and functions based on data gathered over time â creating an airtight security that cannot be breached.
9. Scene understanding
One of the ways through which businesses can improve customer experience and boost sales is by observing their shopping habits or in-store behavior. While salespeople may be limited in their observation and interpretations, AI systems supported by the CCTV technology can be trained to understand intricate trends in complex retail scenes and build accurate relations between shopper behavior and product layout in retail stores.
With machine learning, intelligent systems can analyze trends over time and relate various product arrangements with purchases, then build recommendations on how better to lay out the stores to improve customer experiences and boost sales. Better product layouts can improve how shoppers interact with products, while also subtly and effectively marketing and cross-selling closely related products.
With more retailers joining their peers in experimenting with various AI features to improve customer experience, we can only expect to see more of the technology in the future. Despite arguments against automation, AI capabilities are going to bring more good than harm.