AI for Retail in 2024 Industry Trends, Prospects, and Challenges to Solve

AI for Retail in 2024: Industry Trends, Prospects, and Challenges to Solve

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The economy is stormy, and shoppers feel the consequences firsthand. To stay ahead, retailers must focus on efficiency. Artificial intelligence (AI) in the retail sector can become a silver bullet to help you succeed. Solid 48% of respondents believe AI technology will shape the domain in the next three to five years.

The adoption of artificial intelligence solutions is quickly becoming a hot trend, and if you avoid it, your market positions are at risk. Let us demonstrate use cases on how AI technology can step in to help you with the issues and process bottlenecks you face daily. 

This article is a part of the “AI in retail” series, where we showcase all aspects of AI adoption for businesses. Other articles on this topic include:

The Retail AI Market Overview: How Technologies Change the Shopping Industry

Retail is quickly moving to digital, and digitalization, in turn, drives fast AI adoption. The report shows that the value of artificial intelligence in the retail market has skyrocketed to an estimated 7.1 billion USD in 2023, marking a 29% increase in AI investments from just a year earlier.

A fresh survey shows that respondents outlined three reasons for the increasing implementation of AI technology in retail businesses:

  • enhance customer experience (59%);
  • channel productivity (49%);
  • achieving cost efficiencies and return on investment (44%).

Retail AI statistics

Sources: Honeywell, Fortune Business Insights

But is artificial intelligence a magic wand that can solve all business problems, or is it a short-lived hype?  Let us delve into real-life use cases of retail AI research technology development to find out.

AI Computer Vision and CHI Software: Our Insights and Case Studies

From the time we began working on artificial intelligence, we have worked on numerous projects that covered different aspects of this technology. Computer vision (CV) algorithms, generative AI, and machine learning are also in our toolkit. Let’s focus on our use cases in this article section.

CV-Powered Personal Recommendations: A Step-Change in Customer Engagement

Personal recommendations have always been the leading force behind sales in retail stores. Earlier, consumers typically sought advice from store assistants. But when COVID restrictions got tough and online shopping started gaining traction, keeping that personal connection became challenging. Yet, its significance never waned.

To explore new avenues, our client, one of the leading US retailers, came to us in the fall of 2020 with a novel concept of an AI-powered advisor. The solution was meant to be an expert in skincare recommendations online and in physical stores.

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The new product idea appeared in response to the pressing challenges of the time:

  • The rise of competitive e-commerce platforms; 
  • No strong competitive advantage over other companies in the eyes of consumers;
  • No personal approach to skincare recommendations on the client’s website;
  • Lack of properly trained personnel in the client’s physical stores.

To address the issues, the CHI Software team designed and developed an AI-powered mobile app enhanced with computer vision for face recognition and a GPT-based chatbot.

Computer vision solution with ChatGPT integration

The app flow works like this:

  1. A user takes a selfie; 
  2. Then, the algorithms identify a face on the photo and analyze the skin condition and potential problems; 
  3. When the problem is clear, the system recommends relevant products; 
  4. Users can add more input or ask for explanations by communicating with a GPT-based chatbot. 

The app delivers expert advice and 24/7 client support, so it is not surprising the solution was embraced with open arms on the market and led to stunning results:

  1. A remarkable 10% sales increase thanks to spot-on product recommendations driving higher order values.
  2. 10% of revenue growth through effective cross-selling and upselling.
  3. Stronger customer engagement resulted in 8% growth in customer retention rates.
  4. First-time shoppers joined the retailer’s audience thanks to positive word of mouth.

Read more about the retail mobile app development, technologies used, and potential benefits in our comprehensive case study. Let’s see what AI use cases you can find in our portfolio. 

A Blend of CV and Augmented Reality: Beauty Try-On for Outstanding Experience

When it comes to purchasing cosmetics, customers have two options. The first one is to spend hours in a physical store trying to find the perfect item. The second one is to buy items online without knowing how the result will look.

This creates a problem for cosmetic businesses and their clients. Customers will always prefer the convenience of shopping online, and retailers have to find a way to adapt if they want to stay ahead. This is the exact problem our client from the US wanted to solve.

In the past, they prioritized training a vast team of consultants to provide the desired level of personalization and fit. However, the company quickly realized how unoptimized this process was, especially during lockdowns, so they came up with a new idea – an AI-powered makeup recommendation solution.

Computer vision solution with try-on features by CHI Software

The CHI team divided the project into six phases, which were the milestones of our work. Here they are.

Phase 1: Marketplace improvement ideas

We assessed the client’s solution, identified technical limitations, and explored integrations. After that, we presented suggestions for marketplace enhancement.

Phase 2: AI discovery

To lower operational costs without sacrificing the quality of customer experiences, we proposed implementing several AI features at once. You might think that it’s challenging, and you’re right! So, we divided our workflow into four iterations. It allowed us to thoroughly plan our work and carefully test each part of the project.

1 iteration: Building a mobile app with face analysis;

2 iteration: Developing a recommendation system;

3 iteration: Providing an AR-based fitting room;

4 iteration: Implementing a ChatGPT-powered chatbot.

Artificial intelligence in retail

Phase 3: Computer Vision module

To provide clients with products tailored to their needs, we needed more individual information. So, we decided on a CV system. The user takes a selfie and inputs some of their preferences. Then, an AI facial recognition system analyzes the photo to determine the user’s skin type, color, the presence of wrinkles, acne, etc.

Phase 4: Recommendation system module

The previous phase laid a foundation for this one. Based on the gathered information, the solution provides users with personalized product recommendations

Sometimes, users may be asked to add additional preferences. This will help artificial intelligence (AI) better understand the client’s needs, enhancing the solution’s capabilities. With the same thinking, we decided to add advice on hair care with product recommendations and ideas for styling.

Phase 5: Augmented Reality (AR) module

To decide which item to buy from a cosmetic retailer, the customer needs to try on the product before buying it. But how can a business provide that option without customers being in the store? 

Our answer to this issue is augmented reality. Let’s see what users can do within this beauty platform:

  • Try out different products and colors to see what works best;
  • Capture photos or videos to show off the different styles;
  • Use the app to make changes and personalize the look;
  • Save favorite images or videos to share later on social media or for personal reference.

Phase 6: Chatbot module

In the final development phase, we created a personalized AI chatbot. It serves as a recommendation system that can also answer FAQs. We also added information about current trends, new products, and styles.

To increase user engagement, the chatbot offers tips and step-by-step tutorials on how to achieve a specific look. Additionally, it has video demos and explanations of makeup techniques.

As a result of this collaboration, our client has increased their sales and customer satisfaction. But that’s not the only positive impact that happened:

  • The customer retention rate grew by 10%;
  • An 8% reduction of inventory costs after analyzing customer preferences and optimizing storage; 
  • By leveraging the power of personalized recommendations, our client can promote higher-value and complementary products. With this strategy, they expect to raise revenue by 10%.

This project was an exciting journey, indeed, as it gave us an opportunity to show off the best of our artificial intelligence and augmented reality expertise. To learn more about it, read our case study in full.

More Challenges for Artificial Intelligence in Retail Businesses

Retail and artificial intelligence are a perfect match. Retailers deal with vast amounts of data daily, and AI algorithms quickly analyze this data to support management decisions. That is exactly why artificial intelligence for retailers shines across many use cases – from beefing up security and enhancing customer service to fine-tuning demand planning and optimizing in-store operations.

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How to use AI in e-commerce? Check out these seven use cases

Competitive Pricing Challenges

In times of rampant inflation, shoppers are on the hunt for better value for money. The report shows that 43% of customers admit they recently stopped buying from their favorite retailers because of a rise in price.

In the dynamic world of retail, setting the right price is essential for providing customers with great shopping experiences. It is the sweet spot between driving profit and keeping customers returning for more. Generative AI analyzes large amounts of internal and external data to determine the perfect price point. 

Challenges in Forecasting and Demand Planning

Analyzing trends and figuring out what products, when, and where will be needed are complex tasks that require a lot of data and many hours of analysis. The price of error is high. That is when AI forecasting tools come into play. Machine learning technology can help make informed decisions for better financial results.

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Cybersecurity Challenges

The retail sector is the number one target for cyber attacks. The report shows that only in 2023, 69% of retailers experienced ransomware attacks aimed at customers’ sensitive data. AI-driven security tools, unlike humans, quickly analyze large amounts of data, identify suspicious system behavior in seconds, and respond to real-time security threats to data privacy.

Localization Challenges

Localization challenges for retailers

Do you know that 65% of customers prefer content written in their native language, and 40% of respondents will not buy a thing from a site in a foreign language? Adjusting to local markets has become a challenge during retail overseas expansion, but you have a solution. AI translation and personalization tools help enhance customer experience by adapting content and senses to cultural preferences. This will help you strengthen your business’ understanding by new customers.

Future of AI in the Retail Industry: Trends to Watch in 2025

In 2024, retail is buzzing with one word (or two, to be precise): artificial intelligence. Why? Because the quest for enhanced customer experiences, boost in productivity, and savvy cost efficiency is real. And these driving forces are not just a passing trend. They aim to continue to shape the industry in the coming years. So, let’s look at some AI trends in retail:

AI for Hyper-Personalization

71% of shoppers expect companies to know them well enough to offer only relevant content and products. A highly personal approach in mass business is a tall order, but artificial intelligence is stepping up to the plate. Generative AI algorithms get a better understanding of customers by analyzing shoppers’ data and serving up personalized suggestions. So, tailored shopping is not a luxury. It is the future that will enhance customer experiences.

AI-Powered Virtual Assistants for Stunning Customer Service

Round-the-clock and always alert, generative AI-powered chatbots are the new frontrunners in customer support. With time, they are not just responding but evolving into top-tier virtual assistants that understand natural queries and perform various tasks.

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AI for Smooth Omnichannel Experience

9 of 10 e-commerce websites in the US are backed by brick-and-mortar retailers. And generative AI helps weave online and offline retail worlds together. Artificial intelligence tools harness insights from various shopping channels to create unified customer experiences.

AI Robots for Cost Effectiveness

AI robots for cost effectiveness

Think of AI as the turbo boost for manual operations. Not only does it accelerate tasks, but it also cuts costs and supercharges efficiency. 

Automated cashiers are on 24/7 with no coffee breaks needed. Amazon’s warehouse robots move, pick, and sort packages, increasing the efficiency of the shipment process. And in Walmart stores, cleaning robots scrub floors and check inventories on the shelves.  

AI for Product Visualization

AI-driven augmented reality (AR) and virtual reality (VR) technologies adoption will become prominent throughout the retailers. They will help elevate customer experiences, as well as understand what they are buying and make the right choice. 

By utilizing AR and VR, customers can virtually try on clothes and visualize furniture in their households. They can also see how the product will look in different environments. All of this combined creates an opportunity to enhance customer experiences and improve customer satisfaction.

Predictive AI for Forecasting

This technology can generate insights that will aid the decision-making process by analyzing market trends, customer preferences, and retrospective data. 

Thanks to predictive analytics of generative AI, retailers can anticipate demand and possible market changes. This helps businesses avoid stockouts and provide clients with the perfect product they need. 

Generative AI for Automated Checkouts

We expect the retail sector to adopt generative AI to make the checkout process faster. By utilizing natural language processing, automated checkouts can understand customer speech and respond appropriately.

On top of that, generative AI can suggest relevant upsells and cross-sells, generating more value for the business out of each customer. Combine all this with voice activation and you get a checkout experience that is practically identical to the regular one, just faster. 

AI for Inventory Management

Inventory management can be done solely by artificial intelligence. Its ability to analyze information overshadows any human. This comes especially handy for demand forecasting. By applying AI technology this way, you can forget about ever going out of stock or other extreme – overstocking. 

Additionally, this technology can optimize routes and supply chains. Not only can it deduce optimal inventory levels for each item, but it also can find the optimal route from the distribution center to the store. 

AI for Product Discovery

Artificial intelligence is exceptionally great at product discovery. The analytical power of AI is practically limitless. It can analyze customer trends and market data, providing your business with valuable insights into customer preferences.

If you’re interested in discovering market gaps to fill with merchandising, AI is here for you, too. AI adoption is a top priority for anyone who’s looking to elevate customer’s shopping experiences to the next level.

Conclusion

The retail horizon is rapidly widening thanks to AI adoption. Intelligent technology helps businesses, big or small, enhance customer shopping experiences while optimizing productivity and cost-efficiency. With 97% of retailers embracing AI technology today, you should join the bandwagon, too.

Wondering where to begin adoption? What challenges would you like to address with a new solution? These are the basic questions to ask yourself. Luckily, you have the CHI Software team to discuss the essentials with. 

Whether you have a well-shaped idea or just consider possible retail software development, let us meet and talk. You do not have to “start somewhere”. Start smart. Start with us.

FAQs

  • What are the main trends for AI in retail business? arrow

    In retail AI research and development, the main trends include personalizing customer experiences through AI-powered recommendation systems, integrating AI in retail mobile app development, and using in-store technologies like smart shelves and facial recognition for better customer service. Additionally, artificial intelligence in retail business increasingly focuses on supply chain optimization and predictive analytics for inventory management.

  • What challenges can artificial intelligence solve in the retail industry? arrow

    Artificial intelligence in the retail industry can improve customer experience through personalized interactions and recommendations. It also streamlines inventory management, helps in accurate demand forecasting, and enhances operational efficiency. Finally, AI solutions are pivotal in managing complex data analysis, leading to more effective marketing strategies.

  • What are the perspectives of artificial intelligence solutions for retail? arrow

    The perspectives of artificial intelligence solutions for retail include advancements in custom software development to provide more tailored and efficient customer service, the use of AI for more accurate demand forecasting and inventory management, and enhancing customer shopping experience through AI-driven personalization. There is also a growing trend in using AI for sustainable practices in retail, such as optimizing logistics to reduce carbon footprints.

  • Will chatbots be relevant for the retail industry in 2024? arrow

    Chatbots are expected to remain highly relevant in the retail industry in 2024. Their capabilities in providing efficient customer service, handling queries, and offering personalized shopping assistance make them invaluable. Retail software development service providers are continuously improving chatbot technologies to make them more intuitive and human-like, further solidifying their role in enhancing customer engagement and satisfaction in retail.

  • What is the role of artificial intelligence in retail business? arrow

    AI enhances customer experience through personalized recommendations, improves supply chain efficiency, and optimizes inventory management. AI in retail business also plays a key role in analyzing consumer data for better market insights, aiding in decision-making processes, and automating routine tasks, thereby increasing overall operational efficiency.

About the author
Alex Shatalov Data Scientist & ML Engineer

Alex is a Data Scientist & ML Engineer with an NLP specialization. He is passionate about AI-related technologies, fond of science, and participated in many international scientific conferences.

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