The key to retail success is carefully orchestrating pricing, promotions, product assortment, and inventory availability. It’s no exaggeration to say that price optimization is a merchant’s top priority. Pricing is perhaps the biggest factor that can quickly affect sales and profits. According to Harvard Business Review, the beauty of focusing on pricing is that it pays off immediately. The price can be changed on Sunday night and sales and profits will start to accrue on Monday morning.
Today, retail companies use AI-based solutions to enhance customer experience and increase sales. When prices change by the second, it becomes impossible to track the movements manually and update your prices accordingly. Retailers can, however, use neural network models to adjust prices automatically, based on multiple factors, even on a per-customer basis; thanks to AI. The market for artificial intelligence-based retail solutions is expected to reach $24.1 billion, by 2028.
AI & Pricing
Brands cannot keep up with rapidly changing trends in the market and conduct surveys regularly to find opportunities. Providing customers with a regular rotation of discounts is harder than it sounds. That’s why merchants use the power of artificial intelligence and machine learning to implement offers, promotions, and discounts. Artificial intelligence is very effective in determining optimal prices through analysis of both competitive and historical data, customer behaviors, and seasonal trends.
Dynamic pricing can be achieved by retailers using intelligent AI based on customer engagement reports. A manager who must set the best prices for thousands of products a week must have superhuman abilities. Here’s where AI comes into play. AI-powered pricing systems increase your profitability, by enabling quick and intelligent pricing decisions based on several factors such as stock availability, competitor analysis, point of sale, product portfolio, and customer sentiment.
Benefits Of Price Optimization In Retail
According to PwC, price is the most important reason to buy something for 60% of consumers. This kind of power must be addressed, and a retail price optimization plan can make or break your success. In the early stages of a new and improved price optimization strategy, retailers should focus on a few key pricing factors that can have an immediate impact, which is:
- Current price point
- Margin of sales
- Competitor pricing
- Promotions & Discounts
These factors can be changed and updated in real-time so that retailers can see the impact and adapt to their goals. Retailers who set their price targets based on historical data and analytics will see the most immediate impact on their bottom line.
2. Forecasting Customer Behavior
Imagine having a crystal ball that allows one to see the exact price point that will maximize our profits and keep customers happy. Retail price optimization tools can get us to get closer to this ideal world. Predictive pricing, a feature of many retail price analytics platforms, allows us to automatically monitor market prices, adjust prices, and make pricing decisions based on customer data. With advanced marketing algorithms and existing data, we can predict the impact of specific price changes and price points on sales.
3. Automation of Operations
Automation is taking over every industry, so there’s no reason why it can’t be part of your retail price optimization strategy. Manually tracking, forecasting, and adjusting prices is simply too time-consuming and expensive because we lose out to competitors who update regularly to maximize profit margins. Automating the pricing strategy helps to:
- Avoid common man-made errors that impact sales/revenue
- React in real-time to market trends, maximizing profits and sales
Not just pricing, AI Can Improve Retail in general, How?
AI is revolutionizing retail. To stay ahead of the competition, retailers are increasingly relying on artificial intelligence. AI-first retailers are using machine learning and computer vision to improve customer experience, increase profitability, and stay competitive. Retailers are increasingly investing in AI, with global spending expected to reach 7.3 billion by 2022. Meanwhile, 325,000 retailers are expected to use machine learning by 2023. AI can be used in retail in a variety of ways. Let’s examine a few of them.
1. Improve customer experience
Innovative shopping applications offer retailers significant opportunities to improve their customer experience. Shoppers can benefit from more targeted advertisements tailored to their preferences online. In addition, geo-targeting can be used to share real-time recommendations based on a shopper’s location.
2. Enable visual search
Customers often conduct visual searches before purchasing products online. Image-based search tools use smartphone cameras to help retailers make better recommendations to customers by showing similar or related items. Augmented reality is used to enhance the reality of what customers see in front of them so they may better grasp how the product will be used in their daily life. For instance, the software will display exactly how the consumer would perceive an outfit or how the sofa would appear from various perspectives in their living room. This is a one-of-a-kind, cutting-edge shopping experience that can’t be compared to anything else and is swiftly being embraced by many retailers
3. Provide chatbot-based assistance
Shoppers expect help, whether online or in-store. The chatbot offers 2/7 support and can not only answer questions, but also recommend products based on the shopper’s browsing history, recent purchases, and personal preferences. And if a request becomes too complicated, an AI-based bot can hand over the interaction to a human operator.
[Read: The value of good intent detection]
4. Personalized product recommendations
70% of consumers are more inclined to purchase a product when it is personally recommended to them. AI is the master of personalization because of its capacity to evaluate vast amounts of data, and machine learning algorithms are excellent at proposing goods that customers are likely to purchase.
5. Enhanced in-store security
Machine learning is already widely used by businesses to identify payment fraud, stopping millions of false transactions daily. Companies can also use AI-based video monitoring in their stores to spot suspicious activity and prevent crimes like theft from occurring.
Future Of AI In Retail
Throughout 2020, retailers turned to AI-driven technology to streamline operations and better understand their customers. By 2021, retailers started using data collected over the past year to focus on retaining customers and driving brand loyalty. By 2023, 83% of businesses are expected to use AI, and businesses that do not, risk irrevocably losing market share to competitors that are using AI. According to McKinsey, being able to anticipate customer needs and predict customer behavior will enable retailers to increasingly personalize the in-store shopping experience, increasing in-store sales by 20% to 30%. Additionally, implementing AI will improve the store’s ability to make smarter decisions, increase sales, and ultimately improve customer retention. With the right AI tools in place, retailers are best positioned to drive customer engagement and brand loyalty in the future.
Edited By: Naga Vydyanathan