Trends in pricing: how to stay competitive? Author: PriceCop Tuesday March 11th, 2025 • Category: Blog • Updated: Friday April 4th, 2025 «In the conditions of the digital economy, a pricing strategy is not just a sales mechanism but a key tool for managing competitiveness.» — Philip Kotler, marketing expert Pricing plays a key role in a company’s business strategy. In a dynamic market, where consumer behavior is changing and competition is intensifying, approaches to price formation must evolve. Big Data, automation, and personalized pricing strategies are becoming critical success factors. Which trends are shaping the market today, and how can businesses use them to increase competitiveness? Content list Dynamic Pricing: Flexibility and Adaptation Big Data and AI in Pricing Personalized Prices: An Individual Approach Fighting Dumping and Tracking MSRP Pricing Automation 1. Dynamic Pricing: Flexibility and Adaptation In a highly competitive environment, traditional pricing methods become outdated. If a price remains static, a business loses money: during periods of high demand, it could earn more, and when demand falls, it could attract customers by lowering the price. That is why dynamic pricing is becoming critically important for online stores and suppliers. The problem is that competitors are already using this approach. If a competitor adjusts its price in real time and your business remains tied to a fixed cost, it inevitably loses. The price is too high — the customer goes to a competitor. The price is too low — the margin rapidly diminishes. How Does Dynamic Pricing Work? It allows you to set an optimal price by taking into account: Changes in demand — if a product is in high demand, its price goes up; if demand falls, the price goes down to stimulate sales. Competitors’ prices — the system automatically adjusts the cost to remain competitive. Seasonality and trends — factors such as holidays, weather conditions, or marketing campaigns are taken into account. According to McKinsey, companies that have implemented dynamic pricing record a 5–10% increase in profit by finding the optimal balance between demand and price (Source: McKinsey, “Pricing in Digital Commerce”). Example: Marketplaces like Amazon analyze both customer and competitor behavior, adjusting prices for millions of products every hour. This not only helps retain customers but also avoids price wars, as prices are adapted to real conditions rather than set “at random.” What Should Businesses Do? Switch from fixed prices to automated price management. It’s impossible to manually adjust prices for hundreds of products — automation is necessary. Use competitor price monitoring. Analyze market dynamics and adjust prices to stay on top. Set up flexible pricing strategies. For instance, lower prices for new customers, raise them during periods of high demand, or segment the audience. Dynamic pricing is not just a trend but a necessity for a business that wants to remain competitive. Without a flexible pricing approach, it’s impossible to compete with companies that operate in real-time mode. Today’s consumer expects fair prices that respond to changes in demand, seasonality, and competitor activity. 2. Big Data and AI in Pricing In the modern world of data, it’s not enough to set prices at random or focus solely on a competitor’s strategy. Big Data and artificial intelligence (AI) turn pricing into a precise tool for profit management, enabling companies not only to react to the market but also to predict its behavior. Companies that do not use data operate blindly. They either lose profit by overpricing and scaring away customers, or they underprice and lose margin. Analyzing large data sets allows for forecasting an optimal price based on real market factors rather than intuition. How Does Big Data Change the Approach to Pricing? Demand forecasting. AI analyzes trends, seasonality, and customer behavior to determine the optimal price for maximum profit. Competitor analysis. The system monitors competitor price changes in real time, allowing instantaneous response to their strategy. Offer personalization. AI can take into account customer preferences, offer individual discounts, and increase the likelihood of a purchase. According to the Boston Consulting Group, companies that use Big Data in pricing increase profitability by an average of 6–8% compared to traditional methods (Source: BCG, “Smart Pricing: Using Big Data to Make Better Pricing Decisions”). Example: Supermarket chains use machine learning to adjust prices depending on weather conditions, time of day, and historical sales data. For instance, if rain is forecast, prices for umbrellas and raincoats may be raised, while prices for cold beverages could be lowered. What Should Businesses Do? Implement analytics and pricing forecasting systems. This helps predict which products will be in demand and set prices in advance. Use automated competitor monitoring. This allows prices to be instantly adjusted to maintain a favorable position. Adapt pricing to consumers. Analyzing customer behavior enables the creation of personalized offers that boost conversion. Big Data and AI make pricing predictable, automated, and efficient. Companies that apply these technologies are not just competing in the market — they are setting its rules. The collected data about purchasing behavior, customer preferences, and competitor activity allows for informed pricing decisions. Using artificial intelligence and machine learning enables the analysis of large volumes of information and the prediction of the most profitable pricing strategies. 3. Personalized Prices: An Individual Approach In the era of digital retail, customers are accustomed to personalized experiences — unique offers, individual discounts, personal recommendations. However, in many companies, pricing is still static: all customers see the same prices, regardless of their purchase history and preferences. As a result, businesses lose potential profits by not offering personalized discounts where they could work or by not increasing the margin for customers who are willing to pay more. Why the Classic Pricing Model No Longer Works Identical prices for all = lost profit. Customers with different purchasing power get the same offer, though some might pay more. No segmentation = reduced conversion. Without personalization, the customer sees no value in the offer and goes to a competitor. “Blind” discounts = money loss. Many companies hand out discounts to everyone, even those who would have purchased without one. How Do Personalized Prices Work? Personalized pricing uses data about the customer’s behavior, past purchases, site activity, and competition to offer the optimal price. Key methods include: Customer segmentation. Dividing the audience into groups: loyal customers, new users, those who haven’t purchased for a long time. Dynamic price changes. For example, lowering the price if the customer added an item to the cart but did not complete the order. Flexible discounts. AI determines which customers truly need a discount and which would buy without one. Example: One major marketplace introduced AI algorithms for personalized pricing. As a result, conversion increased by 20%, and the average order value went up by 15%, because the system offered personalized discounts instead of mass sales. What Should Businesses Do? Analyze customer data. Track purchases, on-site behavior, and order frequency. Use dynamic pricing. Set up automatic price changes based on user activity. Apply personalized discounts. Offer discounts not to everyone but only to those who really anticipate them. Personalized prices are not just a trend; they are a way to increase the average order value, boost loyalty, and optimize profits. In a highly competitive environment, companies need to offer customers prices that truly meet their needs, rather than a single price for everyone. One of the key trends is customer profile–based pricing. Personalized prices are built on analyzing purchase frequency, order totals, preferences, and on-site consumer behavior. Example: Airlines and booking services offer different prices to users based on their search history and geolocation. 4. Fighting Dumping and Tracking MSRP In a highly competitive environment, dumping becomes a serious problem for both suppliers and online stores. When product prices are reduced uncontrollably, businesses face several painful consequences: Profit erosion. If competitors reduce the price below the manufacturer’s suggested retail price (MSRP), the other market participants are forced either to operate at a loss or lose customers. Brand devaluation. Constant discounts dilute the perceived value of a product in the eyes of the consumer. If a smartphone costs $500 today and $350 tomorrow, consumers begin to doubt its real worth. Conflicts between partners. Manufacturers and distributors lose control over the market price, leading to conflicts with dishonest sellers and reduced brand trust. According to a Boston Consulting Group study, 42% of suppliers say that uncontrolled dumping among partners leads to a loss of dealer loyalty and reduced margins (Source: BCG, “The Price War Paradox”). How to Protect Against Dumping Modern technologies allow businesses to automate the process of price monitoring and detect MSRP discrepancies in a timely manner. Main methods include: Automated price monitoring. Using specialized services to track competitor prices in real time and detect MSRP violations. Fines and restrictions system. Introducing sanctions for partners who regularly undercut prices helps maintain stable margins. Minimum price on marketplaces. Implementing algorithms that automatically compare prices and limit the minimum cost for dealers. 📌 You can read more about how automated screenshots help detect dumping in this article . What Should Businesses Do? Set up continuous price monitoring. Automated tools allow you to track competitor prices and respond to violations promptly. Develop a clear policy for working with partners. Clearly written agreements and control mechanisms help prevent chaos in pricing. Use dynamic price protection. Enable algorithms that automatically adjust prices in response to competitor dumping. Without effective price control, suppliers and online stores risk losing not only their margins but also long-term partnerships. Modern technologies allow for real-time detection of MSRP violations, preventing price wars and preserving business stability. 5. Pricing Automation In modern e-commerce and retail, managing prices manually is becoming impractical and unprofitable. If competitors use automatic systems to adjust prices while a business continues with an old model, it will inevitably lose. What Problems Does Pricing Automation Solve? Slow reaction to market changes. Competitor prices can change daily, and in some niches — hourly. If price monitoring is done manually, the company risks either selling too cheaply, losing profit, or setting prices too high and losing customers. Human factor and errors. Managers cannot effectively analyze hundreds or thousands of items daily. Pricing mistakes can lead to losses. Suboptimal pricing strategies. Without analytics, it’s difficult to determine which products can be sold at a higher price and which need to be lowered to increase demand. Why Automation Is a Necessity Rather Than Just Convenience According to a McKinsey study, companies using algorithmic pricing increase their margins by an average of 5–15% (Source: McKinsey, “The Future of Pricing”). This is because algorithms instantly analyze large volumes of data and find optimal price points. Example of implementing automatic price updates for stores on the Horoshop platform: Connecting to the Horoshop API — the system receives up-to-date data on products, their availability, and prices. Integration with price monitoring — the monitoring service analyzes competitors’ prices and calculates each product’s cost according to a specified algorithm. Automatic price updates — based on the dynamic pricing algorithm, store prices are updated via the API without manual intervention. Flexibility settings — you can set minimum and maximum price thresholds to maintain profitability and avoid dumping. What Should Businesses Do? Implement automatic competitor monitoring. This allows for an immediate response to market changes. Use algorithmic pricing. AI-based dynamic prices help you find a balance between demand, competition, and profitability. Set up personalized discounts. Automated systems can offer individual prices to different customer categories. Without automated solutions, managing prices becomes chaotic and unprofitable. Companies that introduce algorithms for analyzing and adjusting prices not only save time and resources but also gain a competitive advantage thanks to more precise management of margins and demand. Are you a representative of an online store? Find out now at what prices your competitors are selling in Ukraine 🇺🇦 Pricing is becoming increasingly technological. Using Big Data, dynamic pricing, personalized pricing, price monitoring, and automation enables companies not only to adapt to market changes but also to maintain a competitive edge. In a highly competitive environment, a business’s ability to respond quickly to price changes is a critical success factor. 📢 Want to track market prices in real time? Try PriceCop for free and see how pricing automation helps businesses grow!