Artificial intelligence in retail can transform your business for the good. By leveraging AI, you can make the best use of retail data to generate sales, ensure supply chain automation, and customize the overall consumer experience. AI for retailers seems futuristic and closer than you imagine. Based on the findings of Juniper Research, it’s expected that businesses would spend a whopping $7.3 billion on retail AI by the year 2022 in comparison to about $2 billion back in 2018.
Retail data analytics, AI, and machine learning technologies help retailers to imitate human behavior and ensure autonomous decisions. That is why AI is advanced than traditional software that needs a human to think of all the probable aspects that you may want to employ to generate sales and revenue.
Retailers today are expecting many benefits from AI in retail, but one of the greatest rewards is its impact on customer experience. Here is how businesses are using AI in retail to ensure customized experiences to the customers:
Personalized chatbots for enhanced customer service
Did you know that even physical retail stores have started using robots for multiple reasons? Whether it is a customer chat, shelf scanning, answering queries, providing directions, placing orders, or warehouse deliveries, physical robots can do all such tasks. The use of physical robots in brick-and-mortar stores will increase with the advancement of AI technology, thus transforming the customer shopping experience for the better.
For instance, if you cannot locate a product in a huge retail store, simply ask the robot. Are you looking for an Italian delicacy, just ask the chatbot what food you want to order. Do you want to know whether more items are available in your store inventory, the robot will answer your question.
The creator AI robot Pepper, Softbank cited some great numbers when it comes to enhanced foot traffic and revenue when quite a number of the pilots launched. The AI robot named Pepper can direct consumers, chat with them, as well as accept safe payments, thus creating a unique shopping experience for modern-day customers.
Targeted retail marketing promotions
Many times, retail businesses find it difficult to understand consumer interests just because of the poor timings of their marketing campaigns. Retail data analytics and machine learning algorithms filter via data silos of customer living conditions, demographics, likes, and preferences to initiate targeted marketing campaigns.
Machine learning methods such as customer churn prediction, segmentation, as well as loyalty analytics help retailers to create consumer-focused and omnichannel customer engagement strategies.
Let us cite an example. The AI team of Oodles developed a personalized advertising system, of late, for a major media house in Britain. The analytics-based system shows custom television ads instead of current advertisements by monitoring the data of consumer TV sets in real-time. If customers watch these targeted advertisements, they could earn loyal points, which are redeemable at any retail store. A self-benefiting marketing campaign like this helps retailers to build customer engagement effectually and improve retention and customer loyalty at the same time.
In-store shopping AI-powered assistants
IBM and Macy’s piloted the deployment of AI in a retail store, the two businesses piloting an in-store AI-powered shopping assistant, particularly IBM’s Watson. When a consumer accessed the bot using his or her smartphone, they can communicate with the mobile shopping assistant just as they do with a human store employee. With increases conversions, the bot became smarter and learned how to manage location-based FAQs quickly and effectively. It helped the customers get what they are looking for as soon as possible.
Usually, the bot will identify whether a shopper displayed frustrating emotions or perplexity. Once the bot understands the customer’s feelings, it will instantly offer a possible solution to resolve the issue. Just imagine if the store camera can identify customer stress signs or anger on their face and send an alert to store staff to help the customer right away. Such things are probable, real-time smart responses that provide a pleasing customer experience when people shop in a retail store.
Predictive analytics for retail business products
Several studies indicate that most retailers find it hard to collate, assess, and infer actionable insights from customer data. It happens because they do not have retail data analytics in place. Be it dealing with inventory budget, planning for seasonal product demand changes, enhancing operational effectiveness or performance, or improving the positioning of products, human efforts will not give you the best results.
AI technology improves retail performance with the use of data-oriented insights that tell businesses which items the consumers prefer and they will purchase in maximum numbers, how frequently, and when.
When it comes to predictive analytics, it addresses three crucial challenges. These are:
Intelligent stock management:
Predictive analytics applications powered by AI offers useful insights related to stock exceptions, irregularities, mobilization, as well as other aspects to make precise and informed inventory decisions.
Effective product assortment planning:
Did you know that machine-learning algorithms supersede human intelligence in boosting return on investment on stock investment by making accurate suggestions of product assortment options, worth, sizes, and much more?
Data-oriented analytics consider crucial factors such as customer behavior, the scope of business, rates of competitors, and consumer feedback to arrive at optimal prices of products. In simple words, AI helps smart price adjustments that benefit both the retailers and consumers. AI can help in pushing the best deal to boost sales or the best price to make consumers delighted.
Today, artificial intelligence in retail is a big game-changer to improve customer experiences. Customization across all sales mediums has become overly simple like never before in the history of retail business. Thanks to AI and data analytics. In this blog article, we have just listed a few ways how businesses are exploiting AI to improve overall customer experience concerning convenience shopping, smart pricing, inventory management, or just assisting customers in-store using intelligent robots and chatbots. If you want to learn more about how AI can generate more retail sales and customer engagement, call or email us now.