For 20 years, e-tailers have had an advantage of business over their brick-and-mortar competitors thanks to the data they have on their customers and their ability to interpret it.
Most traditional retailers have opened their e-commerce stores to regain this market share. They are building their customer databases and using emerging artificial intelligence technologies to be more efficient and improve their revenue.
In this article, we explore what AI is. We then share 18 examples of how AI is helping retailers reduce costs, keep customers happy, and compete with online competitors.
Automation and artificial intelligence explained.
Retail is complicated. The stakes are so high that retailers need automation and artificial intelligence to compete. It is now too risky to rely solely on human decision-making on many issues.
With AI’s ability to analyze data and solve problems, you can answer the following questions faster, more cost-effectively, and over time with greater accuracy:
- What will customers want to buy in the fourth quarter, and what volume?
- How many items should we keep in stock in individual stores and for online clientele?
- If a customer needs to buy X, what else would interest him?
- Who will likely spend the most money on products in the subsequent three months?
- Who is most likely to upgrade to the best product?
- Which group of customers will respond best to a new promotion?
How AI-powered predictions are changing retail
AI improves the in-store and online knowledge for customers and staff Business. Its forecasting also helps retailers purchase the right quantities of inventory and raw materials, reducing costs and waste for their supply chain partners.
Below are some ways retailers can harness the predictive control of artificial intelligence and machine learning.
Improve the in-store experience.
Retailers are creating better in-store experiences for shoppers through the following adaptations:
Adaptable displays in store. These displays show shoppers separate offers on wall-mounted LED screens as they gait through the store, activated by their phones with Near Field Communication (NFC) and Bluetooth technology.
Locally adapted display cases. Make the most of Business window displays by only displaying items that AI applications predict local customers will likely want all year.
They personalized customer experiences. Invite shoppers to take their own 60-minute guided store tours. Ensure the items you’ll need according to the AI are stored and ready before they arrive. The more personalized the customer service, the better your chances of maximizing sales.
They have automated personalized experiences. Business Equip your locker room mirrors with sensors. If a person’s facial features suggest they are unhappy with the garment being tried on, immediately ask the AI to suggest alternatives on an adjacent screen. Customers can press a button if they see something they want, and an employee can deliver the desired items directly to their checkout.
Tablets in store. Invite a customer to use a tablet in the store if what they want is not available there. If they find something they want in their entire inventory, they can place the order there and then arrange delivery to their home or nearest store.
Store design. Changing the layout of a store is expensive and disruptive. Have an AI model of how people would move around the store based on different layouts and how that affects spending before committing to a new design.
Know which products are current to customers online Business .
AI can also boost online sales with the following features:
Custom home pages. Use your home page to show customers the products they will most likely want based on their browsing behavior and previous purchases at similar times in previous years.
Suggestion tools. Place images and “more like this” buttons on each product page to show them something complementary based on their preferences and what other customers have purchased. For example, a client might see a pair of stylish shoes that complement the jacket she is looking at.
Personalized marketing. AI can create email and text marketing campaigns with individual messages for each customer. The content is based on your responses to previous campaigns and your browsing/purchase past, which can increase conversion rates.
AI chatbots. Businesses can offer in-store knowledge, but online. Imagine going to your preferred store and having a two-way conversation with a chatbot to help you identify what you want based on your responses and the AI’s knowledge of what you have already purchased or requested.
Become a better retail employer Business .
Here’s how employees can benefit from introducing AI company-wide:
Store staff can increase sales. Sellers can increase sales by showing customers what other people who purchased a product also purchased at the point of sale. AI could also suggest other products based on a customer’s past purchases.
Web designers have better track records. AI lets web designers and developers know where the sales process breaks down. They can create optimal, personalized, and sole online customer experiences based on interaction and engagement data.
Labor meets demand. Provide customers with the high level of service they deserve by ensuring enough staff to serve them. AI can help businesses predict the staffing needed in-store, in customer service, and their D2C distribution warehouse.
Run a tighter, more efficient retail operation.
AI benefits the entire enterprise, including procurement and leadership teams, through the following advancements:
Spot trends. By analyzing blog and social media content, fashion retailers now use AI predictions to decide styles, patterns, colors, and fabrics for their collections. All retailers can also use broader economic data to predict promising products and those on the verge of extinction.
Sentiment analysis. Find out what consumers think of your brand and products by analyzing real-time mentions on social media and discussion forums. Understand user problems to guide product development.
Stricter supply chain management. Knowing what customers want and don’t want means procurement teams and creation buyers can better specify the products they want from suppliers.
Better inventory management. Shoppers can also predict how much of each item they need and when they need it. Therefore, there is less chance of stock out, which means higher revenue, higher profits, and happier customers.
Responsive pricing. Dynamically change your in-store and online prices to match or beat your competitors’ prices, the season (e.g., higher prices for DIY products in spring), and the weather (e.g., run a daily sale if you expect it to rain ). Increase the influx of the public). ).
Welcome to the new retail paradigm Business
Older forecasting methods were time-consuming and prohibitively expensive. Data scientists had to create a new data model for each prediction they were asked to make, and each prediction required a two-month lead time.
On the other hand, AI-based predictions are affordable and can give you responses from an app within a day. Better yet, many apps can check their results to find ways to make better predictions for the future.
AI allows you to improve appointments, introduce deep customer personalization into your in-store and online marketing, increase sales, and build customer loyalty – meaning you can be proactive rather than reacting to a crisis.
Machine learning and AI prediction technology represent the future face of modern business. If you want to get ahead, you’ll need to get there before your client realizes where you’re going.
