The eCommerce industry has demonstrated unprecedented growth over the past decade. With increasing accessibility and convenience, it’s no surprise that around 2.64 billion people are shopping online in 2023. Naturally, there is a lot of optimization going on in the background to make eCommerce platforms work seamlessly.
Apart from optimized websites, fast loading times, and a friendly user interface, you also need dynamic pricing strategies to be a successful eCommerce business. While the concept of dynamic pricing has been around for centuries, the eCommerce industry has given it a new angle. Brands can now leverage AI-driven dynamic pricing strategies to target a wider range of customers and increase their profits.
This blog covers everything you need to know about dynamic pricing strategies in eCommerce and how you can implement them in your business.
The Future of Dynamic Pricing
The combination of AI and dynamic pricing is clearly the definitive solution for the eCommerce businesses of tomorrow. In the future, AI-based pricing software and big data will help increase profit margins by automatically processing data points to come up with dynamic pricing recommendations.
AI-based dynamic pricing strategies will help businesses develop a better understanding of their customers and what they will be willing to pay for each product or service. These solutions provide the best ways to optimize prices and meet revenue targets. According to a survey of 1,000 companies in 2022, 97.2% of the companies were willing to invest in AI and big data. In essence, getting accurate predictions about your business metrics will significantly increase your sales and revenue.
The Importance of Pricing in E-commerce Businesses
According to statistics, 81% of customers do their research before purchasing from eCommerce platforms. As this research is mainly focused on product prices and additional costs, brands need to have advanced pricing strategies to attract customers. This is where dynamic pricing comes into play.
By implementing dynamic pricing, your eCommerce business is able to:
- Offer competitive pricing and have better chances of pulling customers from your competitors
- Increase your sales and revenue
- Extract maximum business value with accurate SKU-level pricing
- Understand customers’ price perception and unlock long-term profitability
- Gain control over your business with better insights into pricing
- Benefit from customers’ growing interest as they monitor dynamic price changes over a period of time.
When you implement dynamic pricing in e-commerce, it means your business is now adapting to market changes, customer behavior, demand, and other competitive factors. As your customers have a lot of brands to choose from, it is essential to price your products in a justified manner. With dynamic pricing, you are able to target the right customers at the right time.
The Evolution of E-commerce Pricing Strategies
Setting prices in eCommerce is a tricky game altogether. If you set the price too high, you get a high number of abandoned carts. But if your products are too cheap, customers might assume that the quality isn’t that great.
Today’s eCommerce platforms and online marketplaces allow retailers to adopt a pricing strategy of their liking in order to maximize their sales. Traditionally, eCommerce businesses have implemented a static, or fixed pricing strategy. This method involves retailers manually setting a fixed price for each product that does not change. Although static prices can be changed manually, they do not necessarily reflect market changes, competitive pricing, or demand-based pricing. E-commerce businesses use static pricing as a way to have more control over their pricing. However, there are many drawbacks of static pricing:
- Pricing does not change automatically with respect to market fluctuation, fulfillment costs, or changes in demand
- Retailers need to place buffers to compensate for fluctuations and shipping costs
- Loss of potential sales due to the wrong fixed price of the product when competitors change their price
- Lower market visibility
- No competitive advantage
When it comes to eCommerce, you simply cannot take so many risks at once. For this reason, dynamic pricing is a solution that factors in market dynamics and changes in customer behavior.
What is Dynamic Pricing?
Dynamic pricing in eCommerce is the practice of pricing products based on multiple data-driven factors. Using both real-time business data and algorithms, retailers can monitor the demands and preferences of customers, the inventory levels of the product in question, and competitor pricing strategies.
Today, numerous brands and eCommerce platforms implement dynamic pricing without us even noticing it. A common example of dynamic pricing can be seen in aviation, as airlines change their ticket prices almost every day of the week. Considering the seasonality, time, and location, eCommerce brands adjust their prices to extract maximum benefits.
The Benefits of Dynamic Pricing in eCommerce
Dynamic pricing allows retailers to offer flexible pricing for products and services, which is why it is now being adopted in the hospitality and entertainment sectors as well. It helps fulfill business goals and stay profitable while providing customers with the confidence to purchase the right products.
There are different types of dynamic pricing, some of which we will discuss later in this blog. Online retailers often need to lower their prices for new customers and also need to raise them in case of products that are high in demand. To address such challenges and make life easier for eCommerce businesses, dynamic pricing can take the form of surge pricing, segmented pricing, time-based pricing, and personalized pricing.
How is Dynamic Pricing Different from Traditional Fixed Pricing
But what really makes dynamic pricing great is that you do not have to manually calculate and set prices every now and then. The hands-off approach to eCommerce pricing is referred to as intelligent pricing, as it is backed by AI and machine learning algorithms.
Unlike traditional fixed pricing, retailers who adopt dynamic pricing can set predefined rules to change their product prices based on market conditions and customer expectations. They can also set margins and pricing caps to make the price changes as seamless as possible. While traditional pricing involves manually setting prices, dynamic pricing automatically updates the listing prices without the need for any manual input.
Factors Influencing Dynamic Pricing
When there is a decrease in demand, retailers often reduce prices to try and get more sales. In case you do not know what is currently happening in the market, you should not price your products based on guesswork. Dynamic pricing is based on data-driven decisions that factor in market conditions and set the best price range for the given product.
Setting a lower price just to attract more customers does not always work in eCommerce, especially if you do not know what your competitors are doing. As customers can compare prices within seconds, you need to be sure that your pricing strategy is based on real market data. Dynamic pricing helps you bypass this challenge with valuable insights ranging from competitors’ pricing to customers’ shopping habits.
The customer segment your eCommerce business targets matters a lot when it comes to product pricing. Customers from different regions and age groups demonstrate different buying decisions, which makes it harder for businesses that set prices manually. Thankfully, dynamic pricing solutions are based on AI algorithms that process demographic data to make the right pricing decisions.
How AI Powers Dynamic Pricing in E-commerce
The use of artificial intelligence in dynamic pricing means that there is a lot of data analysis going on behind the scenes. The pricing decisions are dependent on real data from different crucial aspects of eCommerce. AI algorithms make adjustments in real-time based on market demand and inventory levels. This not only speeds up your decision-making process but also makes it more accurate.
How AI algorithms analyze large sets of data in real-time
Using a combination of data-driven insights and predictive analytics, AI processes large chunks of eCommerce data to produce the best dynamic pricing strategy. AI is also capable of accurately tracking competitors’ pricing changes to keep your eCommerce at par with the competition.
The role of machine learning in understanding patterns and predicting market changes
Machine learning models such as deep learning and reinforcement learning are used for more accurate prediction of the right price point at a given time for a given product. Machine learning is a subfield of AI with a major focus on training algorithms to spot patterns and anomalies in datasets. These algorithms utilize computational methods to pull out the required information from market data and run predefined models to generate the most reasonable results.
Types of Dynamic Pricing Strategies
There are always those cases in eCommerce where the price of a product increases or decreases for a particular time period. In such cases, dynamic pricing takes the form of time-based pricing. This method of dynamic pricing is based on the time period for which the product or service is used by a customer. For instance, eCommerce brands often increase their prices for products with the option of same-day delivery. Similarly, ride-hailing services raise their prices during rush hours due to increased demand.
As discussed previously, customer segmentation makes a lot of difference in eCommerce. With segmented pricing, you are able to offer different prices to different types of customers. This allows brands and service providers to generate more revenue by selling a single product or service at different prices. For example, McDonald's and Starbucks offer discounts for loyal customers and cinema tickets are more expensive for those who want better seats.
This is where brands change the price of a product or service based on increasing or decreasing customer demand. This type of dynamic pricing helps retailers optimize their sales revenues by capitalizing on customers’ needs. Airline tickets are a perfect example of demand-based pricing, as customers have no choice but to buy tickets no matter how high the price surges.
While the actual price of a product is determined by the cost of production, most eCommerce businesses leverage competitive pricing to take advantage of their market. This kind of pricing strategy is especially useful in competitive e-commerce situations where numerous businesses are offering similar products.
Benefits of AI-based Dynamic Pricing in E-commerce
Increased revenue and profit margins
AI-based dynamic pricing automatically lowers product prices when you need to get rid of some leftover inventory and when the demand is low. This means you can increase sales for slow-selling products. As a result, your eCommerce business generates higher revenue with improved conversion rates. According to Forrester, companies can boost their profits by as much as 25% by using dynamic pricing.
Improved competitiveness and market positioning
Capitalizing on the natural ups and downs of the e-commerce market, dynamic pricing strategies enable businesses to maintain stable margins. The AI behind dynamic pricing constantly analyzes market trends to adjust product pricing and keep your business ahead of the competition. It also allows you to capitalize on special seasonal trends with the help of promotions and discounts.
Enhanced customer satisfaction through optimized pricing
Every product has a given price range that customers are more likely ‘willing to pay’. By pricing your products according to customer demands, you can attract a larger number of customers from different segments. When a customer finds a product with reasonable and competitive prices, there are higher chances that they will be satisfied with their shopping.
Challenges of Dynamic Pricing in E-commerce
While there are various plus points of dynamic pricing, it also brings a few challenges for retailers. These challenges are mainly related to the complexity of pricing criteria, transparency, and ethics on the part of those who deal with the numbers.
- To deal with the complexity, you need to have the right machine learning and AI algorithms in place
- To keep the pricing transparent, you need to be able to justify how and why product prices have changed
- All pricing policies must be communicated honestly within the business and with the customers
- To avoid discrimination and exploitation of customers, you need to factor in the impact of pricing changes on customers, business personnel, suppliers, and competitors. You also need to stay compliant with all the relevant laws and regulations
Examples of Dynamic Pricing Success Stories
While dynamic pricing is particularly popular among retail platforms, the strategy is adopted by a wide range of industries such as hospitality, ride-hailing, airlines, and car rentals. Here are some examples of dynamic pricing:
Amazon is popular for its wide variety of products and services across the globe. It is one of the oldest adopters of the dynamic pricing strategy in the eCommerce industry. The prices of millions of Amazon products are constantly updated to balance supply and demand, address customer behavior, and stay ahead of the competition.
Amazon’s sophisticated AI and machine learning algorithms process large datasets to implement dynamic price updates every 10 minutes. The AI retrieves customer data and calculates the ideal price point to maximize profit margins for each product.
Another example of dynamic pricing can be seen in the ride-hailing sector. Uber is the most notable ride-hailing service provider with over 93,000,000 active users throughout the world. Uber’s dynamic pricing algorithm adjusts trip costs based on demand, location, time, and rush hours.
The AI algorithms calculate the distance to the destination, the time it will take to reach there, the expected traffic and peak hours, and the current rider-to-driver demand ratio. As a result, every ride costs slightly different, even for similar routes.
Implementing AI-based Dynamic Pricing
Data Collection and Analysis
The most basic step in implementing AI-based dynamic pricing in your eCommerce business is to gather market data. Here’s the data you need to collect:
- Competitors’ pricing strategies
- Customer demand in terms of online searches
- Customer reviews of similar products
- Buying behaviors during different time periods
All this data is then analyzed and processed by AI to provide the most accurate pricing for each product.
Choosing the Right AI Solution
In order to choose the right AI-based dynamic pricing solution, you need to look for various factors. These include customizability in pricing criteria, control and limit-setting features for controlling and setting limits, and A/B testing capabilities. You also need to look for a solution that provides visualization of pricing and revenue metrics and helps you understand which prices are the most optimal. Choosing the right AI solution allows you to unlock the maximum potential of dynamic pricing and generate higher revenue.
For businesses operating in volatile markets such as eCommerce, dynamic pricing strategies are a viable solution. Regardless of the changes in market conditions and customer demands, dynamic pricing strategies always take your business further in terms of revenue, inventory optimization, and staying competitive.