Dynamic Pricing in Ecommerce: How It Works

Dynamic pricing is a technological and strategic response to the never-ending process of optimization in business, a helping hand for those searching for new ways to increase profit and leverage the dynamic changes in the market.

There are many discussions online about what dynamic ecommerce pricing is all about. Let’s explore and see how this phenomenon can help your business grow.

The Essence of Dynamic Pricing

Dynamic pricing in ecommerce is a method of price optimization where prices for products or services are adjusted in real time based on a variety of factors. Imagine a virtual marketplace where prices seem to live their own life, fluctuating in response to demand, competition, and other market dynamics. Exactly this dynamic approach allows online retailers to fine-tune their pricing strategy to maximize profits and stay competitive. 

Businesses get to strategically adjust their prices to outmaneuver their competitors and capture the customers’ attention. Behind the scenes are sophisticated algorithms that shift numbers and analyze data, making sure that every price change is a calculated move aimed at attracting customers and optimizing revenue. 

It is safe to say that dynamic pricing keeps the ecommerce industry dynamic and competitive.

Marketers differentiate four types of dynamic pricing: 

• Surge pricing. When prices go up for a specific period of high demand. 
• Personalized pricing. The pricing changes depending on the buyer profile and their preferences, purchase history, loyalty level, place in a sales funnel, purchasing power, etc.
• Segment-based pricing. The pricing differs in connection with various segments of the target audience. Customers are usually segmented based on gender, age, geography, and behavior patterns.
• Time-based pricing. Prices change depending on different times of day, week, month, or during different seasons, which in turn correlates with demand fluctuations.

The technology that enabled dynamic pricing appeared in the 1980s. Although the tech behind dynamic pricing in ecommerce is definitely not a new trend, it is still quite an uncommon pricing method since only one in five US and European companies use it. 

Today, businesses must focus on the following aspects to consider using dynamic pricing.

• Demand. A business needs to gather and analyze data to understand exactly when, why, and how much demand for their products changes. That will help you notice the patterns and predict changes to your advantage.
• Supply. Businesses must focus on supply to be certain they can meet fluctuating demand. For example, a popular electronics retailer might raise prices slightly when their stock is running low to capitalize on scarcity, then lower them again once supply is replenished to stimulate demand. This dynamic approach to pricing based on supply levels helps businesses stay competitive and responsive to market conditions.
• Competition. By monitoring rivals’ prices and adjusting their own dynamically, businesses can attract customers without sacrificing profits. For instance, a travel website might lower its hotel prices in a city where a competitor has recently dropped rates to be sure it remains competitive. This dynamic approach to pricing is based on competition, helping businesses maintain their edge and quickly adapt to changing market conditions.
• Customer behavior. One may notice patterns when analyzing consumer behavior in their online shop. For example, people from New York may buy airline tickets to Florida more often during winter. With this insight, businesses sell their products in larger volumes and successfully upsell items.
• Customer expectations. During popular holidays, like Christmas, New Year, Black Friday, Labor Day, Mother’s Day, etc., customers expect prices on certain products to drop. In some niches, like airplane travel or music concerts, people expect ticket prices to be lower long before the actual date.

This info should give you a good heads-up on the topic, but let’s take a look at how providers implement dynamic pricing in real-world cases.

How Companies Set Their Dynamic Pricing

Here are three good examples of companies that successfully use dynamic pricing. 

• Uber. This transportation service leverages everyday changes in demand. During rush hours and late night when public transport doesn’t operate, people still need a ride — and the demand skyrockets. The price reactively goes up. Private transportation services are a niche where dynamic pricing became an international industry standard.
• Amazon. They masterfully use seasonal changes, personalization, segmentation, and fluctuating prices depending on the time of the day, supply and demand for specific products, and prices among their competitors. Amazon changes prices every 10 minutes and around 2.5 million times a day.
• Airbnb. This hospitality service switches prices at night, during special events, and during seasonal shifts. They also call it ‘smart pricing.’ An Airbnb host sets the lowest and the highest price limits while the service automatically adjusts prices.

Dynamic pricing is popular in tourism, retail and ecommerce, digital advertising, entertainment, and public utilities. But let’s try to figure out exactly how dynamic pricing works.

Ecommerce and Dynamic Pricing: How Does It Work?

Businesses use a combination of technology and analysis behind dynamic pricing according to their needs and abilities.

• Machine learning. Machine learning employs algorithms and statistical models to analyze large amounts of data. These algorithms learn from historical pricing data, customer behavior, competitor pricing, and other factors to predict future demand and set optimal prices in real time. The Expectation Maximization (EM) process is widely used to implement ML-powered dynamic pricing. It consists of 6 steps: tracking sales performance, monitoring the market, predefining price factors, analyzing business strategy and pricing policy, and applying data learned.
• Price management automation. Specialized tools or algorithms help businesses manage dynamic pricing autonomously by collecting and analyzing data from various sources and then applying predefined rules and algorithms to set and adjust prices.

Price management automation usually comes with two different approaches — “a glass box” and “a black box.” 

1. In a black box pricing model, the algorithms and decision-making processes are not transparent to a user. This means that a user does not have an insight into how the system arrives at its pricing decisions. While black box models are effective at making complex decisions, they can be challenging to understand or audit, leading to concerns about fairness and accountability.
2. In contrast, a glass box pricing model is transparent, giving users visibility into the pricing algorithms and decision-making processes. Users can see how the system analyzes data and arrives at pricing decisions. This transparency leads to greater trust in the pricing system. However, glass box models may be less effective for highly complex decision-making processes where simplicity and interpretability are sacrificed for transparency.

Choosing between a black box and a glass box approach depends on various factors, such as the complexity of the pricing decisions, the need for transparency and explainability, and the level of trust required in the pricing system. These two access levels are needed to provide different layers of control and oversight in managing pricing strategies within a company.

• Profitability analysis. Profitability analysis assesses how pricing decisions affect a business’s profits. It considers costs, demand, competition, and market conditions to model different pricing scenarios. In practice, let’s say an ecommerce company uses profitability analysis to adjust prices for their popular product. During high-demand periods like holidays, they raise prices to maximize profits. During slower times, they lower prices to boost sales.
• Price/trend forecasting. With proper technology, you can predict future price trends for products or services based on historical data, market trends, and other relevant factors. For instance, an online retail company forecasts demand for winter clothing based on historical sales and market trends. If the forecast predicts higher demand due to a colder winter, the company might raise prices slightly to maximize profits. On the contrary, if the forecast indicates lower demand, they might lower prices to stimulate sales. 
• Price competition marketing analysis. This method is aimed at gaining insights into how competitors are pricing similar products or services, using this information to develop effective pricing strategies. Suppose an ecommerce company analyzes competitors’ prices for smartphones. If they find their prices are higher, they might adjust them to match or undercut competitors. They then monitor competitors’ pricing to stay competitive, attract customers, and maximize profits. 
• Customer analysis for personalized pricing. Customer analysis for personalized pricing uses customer data to tailor pricing strategies to customer segments or individuals Its purpose is to understand customer behavior, preferences, and purchasing patterns for maximum personalization. For example, a store may offer loyalty discounts for frequent buyers while highlighting discounted items for price-sensitive shoppers. Big spenders get premium offers, and so on. 

Now, let’s learn what it takes to implement this pricing method in your business.

How to Implement Dynamic Pricing 

Dynamic pricing for ecommerce is not a one-size-fits-all solution, so it requires careful planning, data analysis, and time for implementation. It takes five steps to implement a dynamic pricing system in your project. Here they are: 

1. Gather information. Start by collecting relevant data such as sales history, customer behavior, competitor pricing, and market trends. This information will make the foundation for your dynamic pricing strategy. You may want to use analytics tools to analyze the data collected and gain insights into customer preferences, demand patterns, and competitor strategies. This analysis will help you understand the market dynamics and identify opportunities for dynamic pricing.
2. Develop a pricing strategy. Based on the insights gained during data analysis, develop a dynamic pricing strategy that powers your business goals. Consider factors like price elasticity, seasonality, and customer segmentation to alter your pricing strategy to different market segments.
3. Choose the right tools. Your dynamic pricing tech stack may include various tools for dynamic pricing based on machine learning, AI, and algorithms (Acctivate, Competera, and Otamiser are among the best complex platforms for dynamic pricing management).
4. Test and optimize your strategy. Before fully implementing your dynamic pricing strategy, conduct thorough testing to ensure its future effectiveness. Use A/B testing or pilot programs to compare different pricing strategies and identify the most successful approach. Optimize your pricing strategy continuously based on the results of these tests.
5. Implement, monitor, and adjust your strategy. Once your dynamic pricing strategy is live, watch its performance closely. Keep an eye on all incoming data, including market changes, customer behavior and feedback, as well as competitor actions to make timely adjustments to your pricing strategy. Remember that the market constantly changes, so you want to stay flexible with your methods and approaches.

 Advantages and Drawbacks of Dynamic Pricing

The advantages of dynamic pricing in ecommerce include the following: 

• higher revenue in the long run;
• larger wages for hired workers;
• higher sales during periods of low demand;
• a broader audience is pleased;
• customer loyalty and retention rate boost due to more personalized offers;
• efficient adjustment to market trends and competitors.

On the flip side, some of the drawbacks of this method include: 

• possible discontent from certain customers;
• increase in overhead costs and operational complexity;
• risk of harming your brand’s value if implemented poorly.

While there’s a certain risk of some customer discontent and added complexity, the potential for higher profits and better customer loyalty make dynamic pricing a smart practice for many businesses. Just remember to implement and manage it carefully to avoid any negative effects on your brand and customer satisfaction. A well-thought-out dynamic pricing approach is a game-changer for boosting sales and keeping customers returning for more. 

Bottom Line 

It’s time to stand out, not just fit in. Going for dynamic pricing implementations, keep in mind that it’s the quality of expertise you put into it that guarantees truly successful results. Let Elogic’s experts craft a tailored ecommerce strategy to set your business apart from the fierce competition. Book a free consultation, and let’s write your success story together.