It’s safe to assume that AI is the next technological leap as important as the invention of the internet, electricity, and steam engines of the past. We are witnessing a breakthrough in digital transformation today, but it is not yet possible to predict how it will evolve in the months and years to come. However, it’s worth bearing in mind that for AI, these are distant dates and could be the same as talking about some of the revolutions that could happen in the coming weeks.
AI is powering many jobs, from marketing to retail to business intelligence and analytics. Automating many repetitive tasks can save a lot of time, allowing specialists to focus on what really matters, like solving problems and building a more customer-centric approach.
How AI will change retail
As noted by the SPD Group, the prevalence of AI in the retail industry has increased significantly over the last few years. More than a quarter (28%) of retailers are now using AI in some aspect, compared to just 4% in 2016.
These developments pose unique challenges. In the future, access to better AI tools may become commonplace, leveling the playing field. This means that the competitive starting point will change, and the ability to adapt AI to enterprise needs will be critical.
Professional expertise continues to be essential. They will either test how AI works or use it to automate tasks. Additionally, new professions will emerge that combine AI with traditional roles, such as AI Prompt Engineer, who communicates with AI for optimal results. The result is increased competition and new ways to reach customers.
However, some elements remain unchanged. The number of customers will remain constant and the purchasing power of customers will not increase significantly. As a result, companies are competing fiercely for the same customers in more sophisticated ways.
8 Benefits of AI in Retail
Here are some ways AI can be leveraged in retail.
1. Process automation
Artificial intelligence in the retail industry can help automate many of the tasks that were previously done manually by professionals, resulting in less time for employees to spend on repetitive and time-consuming tasks. As a result, you can focus on more customer-focused operations. AI-assisted work is also more reliable as it eliminates the risk of human error during tasks such as invoice processing.
2. Customer service – from automated support to cashierless stores
Various levels of AI are taking over customer service in brick-and-mortar stores and online shopping sites. You can monitor customer behavior and measure customer satisfaction (using facial recognition). This helps identify situations in which customers may need assistance and allows staff to respond more quickly.
In many stores, customers no longer check the products themselves. AI does it while the customer chooses the products they want and puts them in the shopping cart. A common payment solution often used by autonomous retailers is to charge the customer from a linked payment card as they leave the store.
3. Prevention of loss or theft
Automatic charging of certain products reduces the risk of loss. In such a retail model, customers can enter fully automated self-service stores only if they have been pre-authenticated. In this way, payments for recalled products will always be charged from that account.
For brick-and-mortar stores that offer traditional services, AI can be used to detect suspicious activity and theft. Loss prevention can also be based on detecting products that should sell out quickly (due to expiration date or end of season).
4. Customer behavior analysis
AI can also help analyze past customer behavior patterns to create better guidelines for future customer experiences. This allows for better product recommendations and a more optimized purchasing process.
This use of AI has nothing to do with detecting what products customers will like in the future. Instead, its task is to determine in what model the user would like to purchase and use the product or service.
AI can also analyze customer behavior to detect what conditions in the store are causing a sudden drop in sales or hampering the buying process. Customer behavior analysis can also be applied to the e-commerce space, where AI detects areas of poor optimization, such as UI and UX elements that are not intuitively designed.
5. Provide a unique customer experience
It is based on providing customers with personalized messages and communications, and using customer insights to deliver personalized offers. This makes customers feel important and valuable, leading to increased customer loyalty.
A personalized message means that the brand itself is no longer recognized as a vendor and the relationship becomes much friendlier. Customers are more likely to forgive the company more easily and return to using the service when something goes wrong (such as an error in the service process).
6. Interactive chat
Leverage AI and deploy chatbots to help your customers get real-time support in the best possible way. Chatbots can answer the most common questions about products and services, but the data collected about customer preferences, behaviors, and concerns can help detect a wide range of customer pain points.
Such data helps us make better decisions about how to optimize the customer experience, from product placement in stores to the structure of our apps and websites.
7. Logistics – supply chain optimization
Artificial intelligence can analyze where and which products sell the fastest – where they are most needed. Deep learning and its assistance can optimize supply chains to get consumers in specific locations with the products they need most. Algorithms also help find optimal and cost-effective delivery routes.
8. Scheduling Employee Working Hours and Locations
Based on the analysis of various factors such as the presence of customers in the store, it is possible to identify moments of increased demand for employees in a particular location, and to better adjust employee placement based on this.
This will help avoid employee overload and will have a positive effect on employee health in the long run.
What are some examples of the use of AI in the retail industry?
AI is already having a major impact on various retail industries such as fashion, food, pharmacy and convenience stores. Its applications drive improved financial performance, retail operations and customer experience. Let’s take a look at a practical example of AI utilization in retail.
Fashion Industry: Virtual Fitting Room
AI technology is revolutionizing the fashion industry by helping customers make purchasing decisions. One such application is Nike Fit, an augmented reality feature available in the Nike App. Accurately measure a customer’s foot size and compare it with data collected from other users to recommend the best shoe size or suggest size variations.
Another example is The North Face, which uses AI to match models of the ideal court based on a customer’s specific needs. The user answers questions about the conditions of their intended use, and algorithms identify the best option.
Beauty industry: perfect shade matching
Personalized customer service and expert advice are essential in the beauty industry. For example, Sephora has developed an app that scans customers’ faces and provides customized recommendations for shades, lipsticks, and other beauty products based on the data collected.
Food industry: fast and convenient ordering
Speed and convenience are key in the food industry. Integrating AI into the ordering process through mobile apps improves the customer experience. Voice assistants have been deployed by companies such as Starbucks and Taco Bell to allow customers to place voice orders on the go and pick them up at restaurants.
Pharmacy: accurate diagnosis and recommendations
AI can improve pharmacy service processes by processing patient information, associating it with specific diseases, and suggesting relevant questions to improve diagnostic accuracy. Additionally, AI can recommend more effective treatments based on a patient’s experience and lifestyle.
In summary, what are the best uses for AI in retail?
The best use of artificial intelligence in retail is based on a holistic approach that introduces AI into processes within the enterprise, from raw data to analytics to customer service. To exploit its potential more effectively, it should be implemented like this.
The Future of Artificial Intelligence in Retail
The future faces AI. The AI market value in the global retail industry in 2021 was $4.84 billion. Spending on AI development for retail continues to grow and is estimated to reach $52.94 billion by 2029.
What will the future of AI look like in retail and marketing?
AI in the retail industry can help further optimize processes and monitor efficiency.
AI in marketing helps create more customized messages that build better relationships with customers
How Comarch can help
The retail industry is evolving rapidly, with manufacturers introducing new technologies, machine learning, and AI-based solutions every year. To keep up with the competition, retail solutions must be constantly developed. Comarch helps launch AI-powered retail loyalty programs with a range of tools and features to take your business to the next level. These include:
- Personalized marketing service by AI/ML – To create personalized offers and promotions for our customers
- Chatbot powered by AI/ML – Automate customer interactions and provide a personalized and seamless shopping experience while providing quick and convenient resolution to customer issues.
It’s also worth mentioning that using AI comes with many risks. These are primarily related to the fact that AI processes and generates a lot of information that can be attacked. To prevent this, it is important to always follow the latest cybersecurity recommendations and only use trusted IT service providers.
If you want to use AI to build better relationships with your customers, check out the Comarch Loyalty Marketing Platform. Contact us to find out how we can help your business grow.
