Content Writer: Polina Sukhostavets

Retail has been using traditional methods in analytics and customer relations for decades. But it won’t last forever.

What retailers (including your business) do need now is deep insights, allowing them to compete and grow their loyal audience. The best way to get it is to deploy innovative technologies, such as artificial intelligence (AI) and machine learning (ML). And it’s not just a random opinion.

With 35% CAGR – this is how the market of AI in retail will be growing up to 2027 (according to Market Study Report). Valued at 1.80 billion USD in 2020, the market is expected to reach 14.71 billion USD in 2027. What a breakthrough, right? There must be reasons for that.

Right now, we’re shedding light on the whole issue. What AI technologies are retailers using at the moment? What benefits are they getting? We’re answering these questions and covering market trends and successful use cases.

AI and Retail: How Artificial Intelligence Impacts the Retail Industry

What do we know about the niche itself? Let’s take an in-depth look at the AI retail market, its perspectives, and peculiarities.

It’s no secret that 2020 was a crisis and even catastrophic year for many industries, including retail. In this domain, the AI niche fell by 30% compared to 2019.

Artificial intelligence in retail: number of deals globally

Since harsh times require an innovative vision, retailers have started investing in artificial intelligence again. According to CB Insights, the niche has already hit a new record in 2021: 1.998 billion USD this year compared to 1.711 billion USD in 2019 (a pre-crisis period).

The thing is, the pandemic highlighted the importance of online presence for the retail industry. Those businesses that aim at the online environment are also seeking their advantages over the competition.

Artificial intelligence allows for quicker decision making, providing profound and detailed insights when retailers need them the most. To add, machine learning (as one of the AI applications) helps to identify the customers’ typical shopping patterns to make personalized offerings.

As stated by Mordor Intelligence, North America has the dominating AI for retail market share mostly because it includes the US and Canada’s strong economies.

At the same time, the territories of India, Australia, and Asia-Pacific countries are demonstrating the most rapid market growth.

Another reason why the North American market is considered strong is that it hosts lots of world-known AI providers: SAP SE, IBM Corporation, Microsoft, Google LLC, Salesforce, and many others.

Why Does Your Retail Business Need AI Optimization?

The numbers look impressive, but how about details on the real business benefits of artificial intelligence in retail? We’re not going to make you believe in miracles – only in powerful AI algorithms.

First, let’s take a look at how retail businesses are using AI worldwide:

Retailers using AI Statista

Source

Let’s go into detail now.

1. Routine operations become more effective

Routine tasks go first because any retailer faces them daily:

  • A supply chain is something many retailers have tried to optimize looking for the optimal route plans. AI algorithms make their suggestions on the best plan to use, eliminating the human factor.
  • Picking and packing are now supplied by robotic power. Moreover, robots can collaborate and pack bigger orders together.
  • The number of product returns can be reduced due to the early analysis of future purchase trends. Algorithms analyze previous transactions, searches, and even weather conditions.

2. The loyal audience is growing

Nowadays, AI can help retail provide smooth customer support in different scenarios: starting from automated checkouts and up to customer mood tracking. With technologies, you’ll be sure that every visitor has got enough attention and consultancy to make the final decision. It will eventually lead to higher customer satisfaction.

3. Personalized approach reaches the next level

Artificial intelligence allows transmitting online shopping to the offline environment. If a retailer has a website (which is most common now), AI algorithms will gather important customer statistics using email marketing and personal accounts. This information may then be used to predict customer behavior and make personalized offers to visitors through their loyalty cards.

4. The in-store space is used in an optimal way

Space and inventory optimization is an easy task for retailers using AI. Algorithms consider existing consumer preferences, product location, season and weather conditions, expiring dates, etc. to place shelves and products where visitors expect to find them intuitively. As a result, every store corner is well-thought-out, and sales are going up.

5. Data security efforts become more accurate

AI technology is the earliest to identify atypical data movements in the system, and no human administrator can do it faster. For this reason, lots of retailers use AI powers to provide solid data security. This measure is crucial as companies store a lot of information about their customers and buying trends.

Technologies Used for AI in the Retail Industry

In 2021, AI for retail has a variety of applications. Below we are giving an overview of the specific technologies used by online and offline stores.

1. Automated checkouts

These devices were created to enhance the customer experience by removing regular limitations of the traditional checkout systems.

The core of this innovation is computer vision built in the store’s cameras and set up in several spots around the space. The system recognizes the items picked up by the visitor as it’s connected with the stock database. When exiting the store, a customer can use an app’s account or a payment card to pay for the chosen groceries with a smartphone.

2. Robotics

Robots are a popular application of artificial intelligence in the retail industry. Their most interesting use case is as shop assistants.

Read also:How to Create an AI Application: CHI Software Guide

Just like virtual assistants at your house or in your smartphone, in-store robots use the ASR (Automatic Speech Recognition) technology that helps to identify human speech and turn it into text. Robots can answer after processing the customer’s inquiry using predefined algorithms.

3. Personalized recommendations online

AI in online retail is more common than ever before. Have you ever thought about the power of YouTube or Netflix recommendations? These platforms have gained and retained their success mostly because of artificial intelligence.

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It’s pretty much the same in retail. This is what it may look like:

  • Recommending items related to the one reviewed by the user;
  • Giving hints at what other shoppers with similar preferences bought on the website;
  • Offering products based on the customer’s previous purchases;
  • Recommending the latest version of the viewed item.

Before implementing something similar on your website, you should verify all of the gathered information. The product catalog should be complete, while each listing should contain quality descriptions.

4. Virtual dressing rooms

Standing in a line to a dressing room, then trying every clothing piece on – not everyone likes this part of the shopping experience. In the pandemic reality, the issue is standing out even more sharply.

With virtual fitting rooms, people don’t have to leave their homes to find a perfect item or outfit. The AI technology places the item on the customer’s image to get a better understanding of the size, style, and color.

5. Mood tracking

Cameras placed all over your store may benefit you by another important feature – mood tracking. Store workers can’t keep an eye on every visitor, but AI algorithms can. Your employees get a notification about an annoyed customer and can approach them immediately. This innovation boosts buyer satisfaction and expands your loyal audience faster than traditional methods do.

6. Visual search

Visual search allows people to upload images of the item they are interested in and get products of similar colors and shapes. This is a great feature for big retailers with a wide range of items on offer. This way, you meet the expectations of buyers who know exactly what they are looking for. Visual search is the shortest way from a request to a closed deal.

These technologies are only a few examples of existing AI solutions for retailers. The market is changing rapidly, responding to global trends and emerging customer needs.

7 Use Сases of Artificial Intelligence in Retail

Let’s face it: retailers using artificial intelligence have an advantage on the competitive market. These companies have already started the big change, and you might be the next to join.

1. Lowe’s: a helping robot

Lowe’s introduced its LoweBot back in 2016. This is a customer assistant that “speaks” several languages and knows the product location better than anyone else. It can provide maps and directions to visitors, while employees provide customers with more in-depth knowledge of the product.

At the same time, LoweBot monitors the store’s inventory in real time and signals if products should be restocked.

2. Sephora: Shade Finder

Finding a perfect tone shade is a quest for many customers, especially online. Sephora makes it simpler with Shade Finder. It’s an instrument available on the company’s website, where a user should provide several parameters and then pick a tone from the list of suggestions.

The parameters include the brand currently in use, formula, and shade. If users find picking  a formula confusing, they can take a quiz to find out the characteristics of their perfect foundation.

3. Macy’s: AI-based customer assistance

The retailer collaborated with Microsoft to make customer service smarter. The AI-driven virtual agent is available for desktop and mobile shoppers to make their experience very similar to the in-store one.

This AI-driven solution can answer text questions and solve multiple customer issues because it has access to the information on orders and inventory. For example, if a customer asks where their order is, the virtual agent can provide this information with a unique order number.

4. Walmart: The future of AI retailing

Walmart went far on the AI subject and created the Intelligent Retail Lab (IRL) to experiment with technology for the sake of a superb shopping experience.

The company created a tech incubator that looks exactly like a usual store but with a huge twist –it’s stuffed with all kinds of innovative technologies.

“We’ve got 50,000 square feet of real retail space. The scope of what we can do operationally is so exciting. Technology enables us to understand so much more – in real time – about our business. When you combine all the information we’re gathering in IRL with Walmart’s 50-plus years of expertise in running stores, you can create really powerful experiences that improve the lives of both our customers and associates”. – Mike Hanrahan, CEO of IRL

The IRL has hundreds of sensors and cameras to collect information about what’s happening inside. For example, cameras paired with real-time analytics allow identifying out-of-stock products and notify store managers immediately via an internal app.

Read also: AI Decision-Making: How to Make It Work for Your Advantage

The latest Walmart AI innovation (June 2021) offers online shoppers the best substitute for the out-of-stock product. To make it possible, the solution gathers information on dozens of parameters: the product’s type, size, price, brand, the customer’s individual preferences, etc. After the deployment stage, the substitute acceptance by the customers reached 95%.

5. Amazon: A true grab-and-go experience

Amazon created the Just Walk Out Technology that eliminates the need to have cashiers (and annoying lines) in the store. To experience this kind of shopping, customers only need the Amazon app and account.

The flow looks like this:

  1. When shoppers turn up in a store, they need to scan the “In-Store Code” with the Amazon app.
  2. Shoppers then pick products from their list just like in any other store.
  3. At this moment, sensors enhanced by computer vision technology identify products taken from the shelf and track them in the cart.
  4. When shopping is finished, customers are free to go out with no additional actions – they get charged later through their Amazon account.

6. eBay: AI experience every step of the way

This e-commerce platform has been actively cultivating AI practices for more than 10 years. During this period, the company has implemented smart search, enhanced a recommendation system, and helped sellers to set the best price for their products.

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Another innovation was announced at the end of 2019 –it’s a visual search. This is how it works: users go to the eBay app and take a photo of an item they are looking for.

Within a second or so, the app’s algorithm checks around 1.5 billion listings to provide a user with the list of similar products in stock. This insane speed is possible thanks to Krylov, eBay’s AI platform developed specifically to accelerate the company’s market growth.

7. Morrisons: Demand predictions

In 2018, the UK’s retailer Morrisonscollaborated with Blue Yonder to improve demand predictions. Knowing what people will buy beforehand allows the retailer to make more accurate stock orders and, therefore, reduce product waste.

This innovation eliminated inefficient manual product ordering, while the number of available products on shelves increased by 30%. Meanwhile, store personnel can focus on customers and provide quality human-to-human interaction.

What Is the CHI Software Advice on the Role of AI in the Retail Industry?

Artificial intelligence can help retail in many ways, but which way is yours? Before you move any further, we recommend considering several things based on our development experience.

What should you consider before starting AI implementation?

There are no two identical retailers on the market, so every decision on changes and innovations should be carefully calibrated. Keep an eye on competitors but always put your business and its specifics first.

  1. Know why you’re doing it. First, you should decide which part of your business requires AI innovations. Clarify it for the vendor at the beginning of your conversation. Try to provide a full picture –it will help a tech team to offer you the best solution.
  2. Consider IT infrastructure updates. Forget about traditional software if you plan AI implementation. Depending on your goals, you’ll need to invest in certain parts of your IT infrastructure suitable for AI techniques. If you are already using corporate apps and are familiar with big data and cloud solutions, your AI adaptation will go more smoothly.
  3. Collect necessary data. To solve a particular issue, developers need a certain type of information. Only after figuring out the challenge and the amount of available data, can the decision on the AI algorithm be made. The AI solution evolves in-synch with the growing amount of data, so you should never stop your AI advancement.

Read also:How to manage unstructured data

  1. Define metrics to estimate project success. The combination of artificial intelligence and retail can bring fruitful results, but you will never know for sure without a system of data-driven metrics. Examples include conversion rates, waste reduction, or a percentage of customer issues solved –it all depends on your primary goals.

What questions should you ask an AI vendor?

Choosing an AI development center is definitely not what you do every day. How can you make sure of the right choice?

Read also: A Complete Guide on How to Develop an AI Software

Next, you can proceed with the following questions:

  • What do you mean by artificial intelligence? Why do you think it’s important?
  • How exactly is this AI solution better than our traditional method?
  • Which and how much internal information will be needed to implement this AI solution?
  • How will this data be processed?
  • What’s your experience in solving a similar issue?

Artificial Intelligence for Retail: CHI Software Use Cases

What we love the most about artificial intelligence is its adaptability. There is hardly a limit to solutions you can develop based on the retailer’s niche, customer demands, and existing infrastructure. These are a few examples from our unique experience.

Computer vision solution for a cosmetic retailer

Our client is a Singapore retailer with a wide variety of beauty products in stock. Customers appearing in the store were getting lost in this variety of options, and it was challenging to provide an individual approach to each visitor.

The CHI Software team created a mobile app with computer vision and face recognition capabilities. The app can analyze a person’s facial features and recommend the most appropriate products.

Ultimately, customers can easily navigate in the product range and take just minutes to pick one product, which increases the store’s sales and customer loyalty.

Price tag tracker

Our client is an international retail corporation with hundreds of stores across Europe. Each store contains around 5000 items, so monitoring and manual price tags updating are everyday challenges for the retailer’s employees. Plus, a delay in changing a price tag causes revenue losses.

CHI Software was a part of the team that developed a complex solution for this retailer. The key features include collecting price tag images (the computer vision part), processing data and comparing tags with a database (the NLP part), defining what tags to change in real time with the CCTV module, and sending notifications to the store’s employees.

The solution allowed removing the need to keep checking price tags all the time. Now employees can focus strictly on changing tags after receiving a notification. It reduces time and money losses for the company.

Face analysis

The solution was created at the CHI Software initiative to provide our clients with advanced technologies improving security and customer relations.

At the heart of this solution lies the face recognition technique. Video cameras located throughout a store send videos to the system and analyze the visitors’ faces. As a result, the retailer gets buyer personas’ characteristics, information about customers with suspicious behavior, and predictions when the store will be most crowded.

Conclusion

When it comes to artificial intelligence, retail is one of the industries that makes the most out of this technology. That’s what you now know for sure:

  • In 2021, the AI retail niche is going to reach and exceed its pre-crisis volume by almost 300 million USD;
  • The top three global AI use cases for retail include customer care, quality control, and inventory management;
  • AI solutions can now cope with routine customer care operations, while store employees can focus more on complex tasks. This is a winning combination to enlarge the loyal audience;
  • Such world-renowned retailers as eBay, Sephora, Macy’s, Amazon, and others have been benefiting from AI advancements;
  • Artificial intelligence and retailing together can drastically change traditional shopping experience that existed for decades;
  • No matter what others say, you should always keep your business reality in mind and implement AI algorithms according to your current needs and strategies.
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