Dynamic Pricing: A Complete Guide with Tips and Examples

You have a hot product ready to launch. Everyone wants to get their hands on it, so you know you can charge a premium right now.

But how do you set your prices for the long term? You need to charge what the market will bear, and that’s an ever-changing target. This is where dynamic pricing comes into play.

If you’re unsure how to set prices for your business, you’re in the right place to learn. Let’s discuss the fundamentals of dynamic pricing, the most common types, and tips for getting started.

What is dynamic pricing?

Dynamic pricing, also called surge pricing or demand pricing, involves adjusting prices in real time based on factors like market demand, supply levels, competitor actions, and customer buying behaviors. Rather than setting fixed prices, dynamic pricing enables sales teams to proactively maximize revenue opportunities as demand fluctuates or market conditions change.

By closely tracking market conditions and adjusting prices strategically, businesses can capture the highest possible revenue during peak periods, minimize losses in slower periods, and respond effectively to competitors’ pricing. This flexibility can be a competitive advantage, but frequent or unpredictable price changes may confuse or alienate customers.

How does dynamic pricing work?

Dynamic pricing works by analyzing real-time market data like demand, inventory, competitor pricing, customer behaviors, and seasonal trends, and adjusting prices accordingly. The process generally involves three key steps:

1. Data collection

Businesses start by gathering real-time market and customer data. This includes sales trends, customer purchase histories from CRM systems, website browsing behaviors, inventory levels, competitor prices, and broader economic indicators. Effective dynamic pricing depends heavily on comprehensive, accurate, and timely data. For example, an ecommerce retailer might monitor customer page views, abandoned carts, previous purchases, and competitor pricing changes, combining this information to understand real-time buying intent and market competitiveness.

2. Price analysis and decisioning

Next, this collected data feeds into pricing software. These tools analyze the information to identify pricing opportunities or threats like excess inventory or competitive price drops that could lead to lost revenue. For example, when demand peaks, the system may suggest raising prices to maximize revenue; when inventory is high or demand dips, pricing software might recommend price cuts to stimulate sales.

3. Automated price adjustment

Once the pricing strategy is set based on real-time data, automation tools update product prices instantly across sales channels, such as ecommerce websites, booking engines, or in-store digital displays. For example, airlines often dynamically price tickets based on how far in advance travelers book, competitor fare adjustments, and current seat availability. As flight dates approach or demand surges, ticket prices automatically increase; on the other hand, tickets may drop closer to departure if seats remain unsold. This allows the airline to balance supply and demand, maximizing revenue on each flight.

Pros and cons of dynamic pricing

When I helped an online retailer of power tools roll out their first dynamic pricing strategy, we focused on strategically using data to move inventory at exactly the right time. We quickly saw how adjusting prices based on real-time inventory levels, competitor pricing, and seasonal demand increased quarterly revenue — a 9% jump after using dynamic pricing. However, I’ve also seen businesses rush into dynamic pricing without proper data strategies, resulting in customer confusion and lost loyalty.

Dynamic pricing offers big advantages — but also some real risks. Let’s break down both sides:

Pros of dynamic pricing

• Increased revenue and profitability: Dynamic pricing helps businesses maximize revenue by adjusting prices in response to real-time market conditions. For example, if demand surges, prices go up to secure higher margins.
• Better inventory management: One of the clearest benefits I’ve seen in practice is inventory optimization. For the power tool retailer I mentioned earlier, we used dynamic pricing to drop prices on out-of-season products and increase them for high-demand items — keeping inventory moving while improving margins.
• Improved competitiveness: Regularly adjusting prices according to competitor actions keeps companies appealing to price-sensitive customers.
• Adaptability to market trends: Businesses can quickly adjust pricing in response to market shifts or consumer trends, ensuring agility and responsiveness to real-time events.

Cons of dynamic pricing

• Customer confusion and dissatisfaction: Changing prices too often can frustrate customers, which can impact their loyalty. Guardrails, such as price-match guarantees, can help mitigate this.
• Complex implementation: Effective dynamic pricing depends on thorough data analysis, reliable software tools, and accurate execution. Companies that overlook these essentials risk mispricing products and losing revenue.
• Risk of price wars: Competitive pricing strategies can accidentally trigger price wars, leading competitors to undercut prices, resulting in reduced profitability for everyone involved.

Ethical and transparency issues: Customers or regulatory bodies may perceive certain dynamic pricing methods, particularly those involving personalized or location-based pricing, as unfair or discriminatory. This can cause trust issues and regulatory scrutiny.

Dynamic pricing vs. elastic pricing

Elastic pricing differs from dynamic pricing in that it sets prices based on the elasticity of demand for a product or service. Elastic demand refers to the effect demand has on certain variables such as the availability of similar products and customer income. It also measures how sensitive customers are to price changes. Dynamic pricing can incorporate elastic pricing principles, but elastic pricing is a broader concept that focuses on price sensitivity and revenue optimization based on elastic demand. Here are some examples:

Elastic demand

If a customer is willing to buy off-brand potato chips because they’re on sale or chooses not to buy chips at all because the price has gone up, demand is elastic. Another example is gasoline. When the price of gas rises, consumers tend to reduce their consumption because they can find alternatives or potentially adjust their behavior to use less fuel. On the other hand, when the price of gasoline falls, consumers may increase their consumption because it becomes more affordable.

Dynamic pricing

A major airline sells tickets online. They use dynamic pricing software that adjusts ticket prices based on various factors — demand, time until departure, competitor pricing, and even the customer’s browsing history. During peak travel seasons or when there’s high demand for specific routes, ticket prices increase. But, during off-peak times or when there are unsold seats close to the departure date, prices decrease to stimulate sales. This dynamic price adjustment lets the retailer maximize revenue by capturing the highest possible price customers are willing to pay at any given moment.

When to use dynamic pricing

Dynamic pricing isn’t a one-size-fits-all solution. Its effectiveness depends on your product, market, and how prepared you are to respond to real-time data. That’s why I always suggest starting small — by choosing a single product category or sales channel, testing your strategy, and then building from there.

Here are four scenarios where dynamic pricing tends to work best:

Responding to changes in customer demand

When interest or demand spikes, raising prices can help capture higher margins. In slower seasons, lowering prices can boost sales and help clear excess inventory. For example, snow shovels tend to command higher prices in winter, but lawnmowers may need lower prices to move in colder months. 

Handling changes in supply

When supply levels change, pricing should follow. For example, if your inventory of a trending item is running low, raising the price can extend availability and preserve margins. On the other hand, excess stock of a slow-moving product might require markdowns to spark interest.

Competing in a crowded market

Markets move fast — and so do your competitors. Dynamic pricing lets you adapt to competitors’ price changes, helping you stay visible and competitive. I’ve seen brands automate these adjustments daily, sometimes hourly, to keep pace with market conditions.

Adapting to customer behavior

Customer preferences shift quickly, especially online. Dynamic pricing lets you respond based on actual behavior, such as purchase history, product views, or responses to past promotions. Understanding price sensitivity across different segments is crucial here; for example, a returning customer may receive a different price offer than a first-time visitor, depending on their likelihood of conversion.

5 most common types of dynamic pricing

Dynamic pricing varies based on your strategy, data, and business goals. Here are the five most common types and how each one functions:

1. Demand-based pricing

This strategy adjusts prices in direct response to customer demand. When demand surges — due to seasonality, trends, or unexpected spikes — prices are raised to capture higher margins. When demand decreases, prices are lowered to encourage sales and prevent excess inventory.

Behind the scenes, demand-based pricing typically relies on historical sales trends, behavioral signals such as site traffic or cart activity, and predictive models that forecast future purchasing trends. It’s commonly employed in industries with fluctuating interest rates or inventory pressure, and it works best when powered by real-time data and pricing automation.

2. Time-based pricing

This model adjusts prices depending on the time of day, week, year, or season. Businesses use it to manage predictable shifts in customer behavior — such as increased demand during lunch hours, holidays, or weekends — and to balance supply and demand across peak and off-peak periods.

It’s commonly seen in industries like transportation, hospitality, and entertainment, where value fluctuates over time. Successful implementation of time-based pricing requires consistent data and automation to adjust prices quickly and accurately. When done well, it can improve margins during peak periods while maintaining stable volume during slower periods.

3. Segmented pricing

Also known as price differentiation, segmented pricing tailors prices for different customer groups based on specific attributes like purchase history, demographics, location, or loyalty status. The goal is to align pricing with each segment’s willingness to pay, maximizing revenue without sacrificing volume.

This approach relies heavily on first-party data to identify meaningful customer segments and set appropriate price points for each. It’s commonly used in industries like travel, retail, and digital services, where the same product or service can have different perceived values depending on the buyer.

4. Location-based pricing

With location-based pricing, businesses adjust prices based on geographic factors, like regional demand, local market conditions, tax rates, or even the cost of living. This helps companies compete in each market while optimizing profit margins across different regions.

It’s commonly used by global retailers, travel providers, and service-based platforms where the same product may have a different value or cost depending on where it’s sold. The key to doing this effectively is accurate geolocation data and clear pricing logic to ensure transparency and fairness.

5. Competition-based pricing

This strategy sets prices in response to competitor pricing to attract customers in crowded or price-sensitive markets. Businesses monitor competitor actions and adjust their own pricing to match, beat, or position strategically in relation to alternatives.

It’s especially useful for commoditized products or highly competitive industries like retail and consumer electronics. While it can help maintain market share, it requires constant monitoring and smart automation — otherwise, businesses risk triggering unsustainable price wars or undercutting their margins.

Examples of dynamic pricing in action

Dynamic pricing strategies take many forms, depending on the product, market, and business objective. Learning from successful pricing strategy examples can help businesses apply the right approaches to meet demand, stay competitive, and drive revenue.

Energy industry 

One global solar and renewable-energy firm used Salesforce software with CPQ and dynamic pricing rules to automate discounts, approvals, and maintain pricing consistency. After launch, they saw a 20% rise in sales productivity, quotes generated 30% faster, and revenue growth of 20%, all while preserving pricing accuracy.

Utilities industry

Utility companies take a different approach. Many use dynamic usage-based pricing to manage power grid load and reduce strain during peak times. Electricity rates often rise during periods of high demand, such as on hot afternoons when air-conditioning is in use, and drop at night or during off-peak times. The goal is to encourage consumers to shift their usage and prevent system overloads while maintaining efficiency and a cost balance.

Retail industry 

In retail, companies often combine dynamic pricing with automated outreach. A customer who has viewed a product multiple times might receive a personalized app notification or email when that item’s price drops. Travel is another industry that heavily relies on dynamic pricing. Airlines use real-time signals, such as seat availability, booking patterns, and user behavior, to adjust fares constantly. If a traveler stays on a page without booking, the price may nudge upward. If seats remain unfilled closer to departure, prices may fall to boost conversion. It’s a delicate balance of urgency, value, and timing.

For businesses concerned about alienating customers with frequent price changes, strategies like price-match guarantees or transparent discount timelines can help preserve trust.

Best practices for implementing a dynamic pricing strategy

Dynamic pricing can deliver measurable results, but only when it has a solid foundation of strategy, clean data, and the right tools. Here are five best practices to help guide your implementation:

Define your goals

Having clear objectives is crucial so you can develop strategies to meet them through dynamic pricing. Before adjusting any prices, define what success looks like. Are you aiming to increase revenue? Clear out your inventory? Enter a new market? Your goals will shape your pricing logic, the metrics you track, and how you balance short-term wins with long-term brand equity.

Choose the right pricing strategy

Not all pricing strategies are created equal. Choose a model that suits your product type, sales motion, and customer expectations. A commodity product might benefit from competition-based pricing, while a seasonal item may respond better to demand-based logic. Ensure your pricing approach aligns with your revenue targets and customer experience goals. You also need to choose whether you’ll use a rule-based or AI-powered approach to set price points.

Collect your data and set up your tools

Clean, connected data is essential. Implementing a dynamic pricing model only works if it relies on high-quality data. To measure success, spot trends, and stay competitive, you must ensure your data is recent, accurate, complete, and error-free. Integrating data and AI tools into your CRM can help you establish a single source of truth. AI can also automate key processes, reducing manual price adjustments that can lead to human errors and consume more time.

Automate your processes

Manual price changes are slow, error-prone, and hard to scale. Tools like Revenue Cloud use AI-powered automation tools to evaluate real-time data and update prices instantly across channels. With built-in guardrails like minimum and maximum price thresholds while maintaining price flexibility. Be sure to test your logic before going live so everything runs smoothly.

Test and learn

No pricing strategy is set-it-and-forget-it. Use A/B tests and sales analysis to evaluate the impact over time. This helps you determine whether customers respond to the changes and if revenue improves without losing trust. By constantly monitoring and tracking key metrics such as sales volume, conversion rates, average order value, and customer satisfaction scores, you can better identify which adjustments lead to better results. Dynamic pricing works best when it’s regularly refined based on results.

Dynamic pricing can give you a competitive edge

When executed with intention and the right tools, dynamic pricing can be a powerful differentiator. It helps businesses move quickly, stay competitive, and turn market volatility into opportunity. However, it’s not just about adjusting prices — it’s about developing a pricing strategy that’s responsive, data-driven, and aligned with your broader goals.That means weighing the benefits — greater revenue, smarter inventory turnover, tighter alignment with demand — against the risks. Poorly managed dynamic pricing can confuse customers, trigger price wars, or hurt brand trust. That’s why testing, automation, and clearly defined pricing logic are essential.

AI-powered tools like Revenue Cloud can help unify pricing, sales, and finance workflows, connecting the dots between what’s happening in the market and what gets quoted to the customer. With integrated data, automation, and guardrails, you can implement a pricing strategy that’s not only dynamic but also sustainable.