How to Boost Retail Sales with AI-Driven Applications 

AI is inspiringly disruptive, and the entire world is experiencing it with a revolutionary change across everything around us. From gaming, education, and shopping to online transactions and communication, artificial intelligence is leading the way with notable capabilities that simplify it for people to interact and engage. 

In a nutshell, artificial intelligence is the future of every brand looking toward a future-first business architecture. Among other prominent domains, retail is an industry where the impact of AI-driven applications can be leveraged on many scales. 

You must have heard or read about the majestic influence of these technologies being embraced by industry leaders to upscale their business presence and make profits. In the healthcare sector, tech suites like AR and VR are revolutionizing medical diagnosis, appointment booking, doctor-patient interactions, and so much more. 

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This tech-driven change is omnipresent including industries such as fintech, education, etc. which gives rise to the question, “How to boost retail sales with AI applications?” 

All it takes to adopt these cutting-edge technologies is to find the right software and app development agency with expertise in artificial intelligence and machine learning. With strategic planning and feature implementation, any retail brand can achieve success in terms of increased user engagement and ROI. 

In this post, we will focus on some crucial aspects of retail that can be optimized with AI to drive transition in the sales cycle effectively. Moreover, we will also explore some use cases to study how AI has been a game changer in the online shopping domain already and why businesses should invest in it! 

Boosting Retail Sales with AI Applications – Use Cases that Will Change Your Mind 

The raging market competitiveness accompanied by survey reports, analyses, and many expert opinions can create a lot of confusion, especially in terms of decision-making. 

However, the following use cases showing the lucrative effect of AI in retail success help you grasp the significance of embracing these technologies: 

1. Amazon – User Personalization, Demand Forecasting, & Logistics Planning 

Let’s start with Amazon! 

Amazon products can be found in every household around the globe. The e-commerce giant has remarkably used its supremacy to leverage its data and gain insights from the artificial intelligence tech suite for a broad array of functions. 

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Its shopping portal can now analyze user behavior with information from search and purchase history to recommend relevant products. 35% of the total revenue of Amazon comes from this feature. In addition, they have a demand algorithm to assess past sales data, inventory levels, search trends, and pricing fluctuations. 

In addition to inventory optimization, AI and machine learning allowed Amazon’s retail game to boost with powerful logistics planning. For maximum inventory optimization, it can now identify warehouse locations and plan distribution routes for hassle-free order delivery. 

2. Walmart – Chatbot Integration & In-Store Analytics 

Walmart is one of those popular shopping brands that thrive on consumer experience for seamless sales and buyer retention. Therefore, it decided to upgrade its architecture with chatbot implementation to get even better at servicing its target audiences. Now its customers can get answers to basic buying queries through AI. Human support only gets those queries that require more attention. 

In-store analytics is Walmart’s way to ensure that it can collect data based on its consumers’ preferences while they are inside the store. This in-store analytical system has an image recognition feature along with sensors to personalize the user experience and enhance the store layout for a more impactful product display. 

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3. Sephora – Virtual Try-On & Beauty Advisor 

Not being able to try on a product before buying online used to be one of the biggest challenges in the beauty commerce domain. It was difficult to pick the right shade of lip color or foundation without testing it on a particular skin tone.  

However, it remained a problem only until Sephora introduced its virtual try-on feature. An immensely powerful combination of AI with AR now allows its buyers to find the best makeup product as per their skin tone.  

The upscaling process of Sephora to boost its sales with AI applications didn’t stop at AR implementation. It also has a beauty advisor run by machine learning algorithms to help shoppers get personalized recommendations for products that will suit their skin type, skin tone, and face shape.  

4. Starbucks – Menu Setup & Supply Chain Forecasting 

Millions of people in the world start their day with Starbucks and rely on its services to get fresh beverages. To align itself with the changing market dynamics, it needed AI and natural language processing (NLP) to collect insights and utilize the data to optimize its menu. This way, the brand has gained an advantage in terms of launching new products successfully. 

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Apart from menu optimization, Starbucks is leveraging artificial intelligence technology to keep track of its inventory and prompt better supply planning with product demand forecasting. 

With these use cases, it is clear that AI applications help retail businesses manage their supply chain forecasting and enhance their consumer engagement process to eventually retain buyers and boost sales. 

Let’s move on to the part where you will learn about the areas that are impacted by the implementation of AI technology in a retail cycle. 

Benefits of AI that Simplify Retail Operations 

1. Demand Forecasting 

A retail business must concur with many responsibilities, and inventory management is one of them. Planning of available and out-of-stick products, selection of most bought products, and classification of customers are some areas that require constant attention and AI can be leveraged to improve this. 

Traditionally, stores relied on spreadsheets and other similar methods to keep track of their inventory, but it is vividly prone to data errors. The chances of mistakes are higher when the product range is higher, and the target buyers come from different groups. 

Fortunately, AI-driven analytical systems and demand forecasting features automate the process remarkably. While this feature doesn’t directly boost retail sales with AI applications, it enables top brands to focus on their sales cycle instead of wasting time and resources on inventory management. 

You can also read – How Did Starbucks Increase Sales by 14% with Its Mobile App? Let’s Find Out!

2. Personalized Shopping Experience 

Look at it this way!  

You’re looking for new cushions on a shopping portal for a week, but it fails to show you the right selection even after that. You will stop using that shopping app. However, you will instantly be drawn to an e-commerce platform that is showcasing similar products that you saw just a few hours back. 

This is the difference between an AI-powered application and a regular shopping portal. User personalization makes all the difference, and this is why almost every other online shopping app counts on cutting-edge technologies to understand user behavior, gather user data, and use it to recommend relevant products that buyers will be interested in. 

3. Supply Chain Optimization 

What will happen when you have enough leads but no efficient supply chain system? In that case, only an AI-backed application can help you manage the post-retail process from production to delivery. Other than demand forecasting, supply chain management is another aspect of retail that doesn’t involve any interaction with the buyer but affects sales by reducing costs and increasing efficiency. 

4. Inventory Management 

Retail inventory is a more complex procedure for established businesses that it appears as it consumes a lot of hours and manual labor to maintain the data based on the size and type of retail venture. Given other pre-sale and post-sale challenges, automation is certainly the key to streamline inventory management. 

Lowes, which is a home improvement retail brand, keeps small cameras at the top of shelves in the store to quickly assess what product is falling short in quantity. An AI-driven inventory management system can help retail stores leverage sensors and camera vision to tackle these challenges and maintain the inventory hassle-free.  

5. Quick Support for Buyers 

Your staff can’t always be present to answer the queries of your buyers, given the higher cost of maintaining round-the-clock human support. However, you can always trust AI-based chat support to revert your buyers and provide the answers that can persuade your target audiences to make an informed buying decision.  

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Global retail brands like Sephora use AI chatbots as reservation assistants to get orders when a new product launch is around the corner. This way, they manage to update their inventory and streamline the post-sales process without any delay. 

Why You Should Trust Zazz for AI Application Development 

Technology is here to help businesses get better with their approach to engaging with the target audiences and stakeholders. With AI, you can not only increase your presence on the web but also discover possibilities with which a brand can become future-ready. 

At Zazz, we can be your technology partner in building highly responsive and visually empowering AI applications that not only boost your retail sales but also help you align your inventory with your buyers’ favorite products. Our expertise in the latest suite of cutting-edge frameworks can help you reform your online shopping brand and increase outreach effectively. 

To learn more about our AI app development services, schedule a call with us now! 

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Explore the cutting-edge world of app development with Melissa Clarkson and her blogs on the latest trends and industry updates to fuel your tech journey.