AI Driven Solutions Making Growth in Retail Business

Artificial Intelligence applications in retail are growing day by day. AI has brought extreme business opportunities by developing necessary tools and products like product recommendation system for e-commerce websites, image processing & pattern matching technique used in fingerprint matching and facial recognition for security, and Chatbots for customer services and interaction. Recommendation system developed by AI (Fashion, Product) helps retailers to understand the demand of the end user. This enables retailers to buy only those products which are in most demand. It won’t be wrong to say that through recommendation system revenue of the retailers will increase.

In the other perspective, AI has increased the sale through online business. To elaborate the above, Giant companies like Flipkart, Amazon are shifted fully on AI-based product recommendation system. Due to this, sales of these companies increased because long tail business got promoted. Indirectly these companies buy products from wholesalers and retailers. So this leads to the growth of the retail sector. That’s is the reason why retailers and business enterprises should prefer AI-enabled services rather than traditional ways of marketing.

Chatbots, supply chain optimization tactics, long-tail recommendation systems, marketing and fashion recommendation engines - all are AI products. A recommendation system recommends the similar item to a consumer, depending on their previous choice of shopping. It also provides the details of the recommended item like nearby addresses where the item is available and at which cost. By this way, Recommendation systems are making products or items handy and accessible. Through these products, AI is contributing in different fields of retail to provide higher sales and better customer engagement.

To understand how recommendation system works, the collection of data of customers for the past years is collected and is fed to the machine. Data scientist or programmer will perform the desired steps so that machine can learn the data in an optimum way. Such system once gets trained is now ready to perform the real-time analysis. It can be used to provide the prediction of a specific area future business growth and type of product which would be in demand or product which will remain outdated. Just imagine, it will save a lot of manpower and manufacturing cost. Not only retailers but also manufactures and wholesalers will be benefited from such.

Following use-cases will show how AI is transforming the retail industry:

• Customer Relation and Interaction: Customer interaction is the key point of any retail business. For building customers in retail industry it is necessary to maintain the interaction with buyers and suppliers. A good interaction will lead to attracting more shoppers and they become regular customers. For this sake, enterprises are preferring AI based marketing for better performance and customer engagement. It includes open C2C (Customer to Customer review), this makes shopper check the reviews of consumers; so that they can decide which product they should buy from which retailer. Good reviews of any enterprise bring new customers. A new method of interaction with customers is Customer Support Prediction. This technique uses auto prediction of customer’s problem. With the use of such, retailers provide auto-support messages or services to the consumers before they contact to customer support. It leads to better relations with the consumers and reviews as well. Better the CRM (Customer Relationship Management), more will be the sales lead.
• Product Recommendation: The online shopping has two ways, first is the old method of typing and searching a particular item but in the modern world, a purchase is done by the customer on the basis of a recommender system. E-commerce websites like Amazon, Flipkart, Myntra, Snapdeal and Paytm all are using it. While online shopping, we see the note of "You may also like” and customers are recommended with some similar things with respect to our searched product, it is what a recommendation system does. These strategies can be applied by online retailer to make their product visible at wider aspect. This strategy influences the demand prediction of online retailers and thus supply chain.
• Smart Purchase: Smart purchase is nowadays becoming very helpful for customers. In smart purchase retailers or sellers make advertisement of their products from different sites. In simple words, if anyone is looking for any dress they search the whole day in each shop and buy it. They have no idea of the real cost of the dress. But if they go for the smart purchase, there are many available apps or sites from where they can search by the name, colour, and brand of the item. It also provides the proper information of all the addresses where it is available and at what cost. A buyer can compare the price and go for the best one. In such way, AI-enabled service providers are attracting more shoppers than traditional retailers.
• Sales and Offers: As sales and offers always attract a shopper. Many E-commerce websites use this strategy to chase customers to buy more products. Latest technologies make an analysis of each customer's previous shopping and related data. For example, if anyone looks for a product online, it is saved in the backend in all activities of that person. This data is analysed and used to train the machine learning model on the basis of which further steps are taken. Offers or discounts are made by enterprises on the most likely searched products. When the customer sees the offer or discount on their favorite products they approach to buy that particular product. One of the most influencing examples for such is Google Adsense. Google is using AI to display the add relevant to the content of websites. For example, if you have applied for Adsense for your technology website and get approved, Google will pay adds related to technology and same is true for the product based website. More people will buy the products online and indirectly retailers or wholesalers will get the benefit because online companies buy these products from shops to deliver to customers. To relate this to the practical example, People are booking hotels on OYO app or booking rides on OLA, UBER. Both the drivers or hotels and app are benefited.