The Ultimate Guide to Dynamic Pricing

The Ultimate Guide to Dynamic Pricing

Dorota Owczarek - February 22, 2023

Dynamic pricing has the potential to revolutionize the way businesses approach pricing, but it’s not as simple as just flipping a switch. This sophisticated pricing strategy adjusts the price of a product or service based on real-time market demand and supply, offering companies the flexibility and agility they need to stay ahead in today’s fast-paced and competitive market. But with so many moving parts and factors to consider, successfully implementing dynamic pricing can be a daunting task. That’s why we’re here to help, with a comprehensive guide to dynamic pricing that will demystify the process and give you the tools you need to succeed.

In this article, we will dive into the world of dynamic pricing, exploring:

  • how it works
  • the factors that influence dynamic pricing rules
  • the key types of dynamic pricing models with industry examples
  • steps involved in implementing a dynamic pricing strategy
  • the importance of measuring the effectiveness of a dynamic pricing model
  • the challenges and limitations of dynamic pricing strategies
  • our top tips on how to overcome them

Whether you’re a seasoned business professional or just starting out, this article will provide you with a comprehensive guide to dynamic pricing and all that it entails. So, let’s get started!

Understanding Dynamic Pricing

In a nutshell, it sounds simple - instead of maintaining fixed prices, you adapt them to the current conditions in order to maximize profit. But when you dive deeper, it turns out that there are various strategies to adapt and different variables to choose from, depending on the specific case of your business. There is no universal dynamic pricing model that works for everyone.

Those systems which establish prices automatically on big platforms inevitably ignore the specifics of the company’s target group, even if they are optimized in terms of the industry. That may affect the effectiveness of the price calculations. For your dynamic pricing to boost sales and fortify your company’s finances in the long term, it is worth customizing your model. However, in order to do that, you should first delve into the basics of dynamic pricing. Let’s jump into that together!

How Dynamic Pricing Works?

Dynamic pricing strategies replace fixed prices with fluctuating prices, calculated and updated in an automated way based on a bunch of variables. The main goal of dynamic pricing is to maximize revenue and profit by adjusting prices according to real-time market demand and supply. By doing so, businesses can adapt to changes in the market and stay competitive.

Static pricing (with single price point) vs. dynamic pricing (with multiple price points)

Static pricing (with single price point) vs. dynamic pricing (with multiple price points)

The environment can have a significant impact on dynamic pricing models. Dynamic pricing algorithms rely on various external data sources, including sales history, competitor pricing, market trends, and consumer behavior, to determine the optimal price point for a product or service at a given moment. The algorithm then adjusts the price up or down with multiple price points in real-time based on this information.

Static pricing (with single price point) vs. dynamic pricing (with multiple price points)

Static pricing (with single price point) vs. dynamic pricing (with multiple price points)

Factors That Influence Dynamic Pricing

Any dynamic pricing strategy implies constantly recalculating prices based on changing conditions. The frequency of these calculations depends, above all, on how often the relevant conditions change.

An example: in the case of e-commerce companies, the most effective approach is a customer-focused one. That means the price will adapt to every customer anytime they look up a particular product, based on their behavioral patterns and general factors like current demand. Meanwhile, in the case of a company offering B2B logistics services, the changes will probably not be that frequent or radical because:

  1. the purchases take place less often
  2. companies have their budget and expect at least some level of predictability
  3. the main variables here are the external factors - demand, fuel, costs, etc., not the customer behaviors.

This is only an example that illustrates how different the approach to dynamic pricing may be. There are various paths to take, and each model may integrate a unique combination of factors into its calculations. These factors include:

  • value
  • demand for the product or service
  • availability of the product or service
  • customer-related factors (the customer’s relationship with your brand, their shopping habits, for instance, whether they are impulsive buyers or wait for the right timing)
  • environmental factors (or, in other words, external - like fuel costs, material costs, market trends, competition performance, and economic factors, like inflation and general market sentiment)

How are the prices calculated, though? With the dynamic pricing examples collected below, it will be easier to understand the mechanisms behind it.

Key Types of Dynamic Pricing

Cost-Plus Pricing

In the case of cost-plus pricing, the final price is a sum of the direct costs of the product or service plus a fixed percentage of that value. How does it work in practice?

Let’s say you have a catering business and are about to prepare a quote for a birthday 3-course meal delivered at the client’s address. If you pick cost-plus pricing, you should first sum up the costs of ingredients, resources (electricity, water), labor, equipment rental, fuel, etc. If you decided your cost-plus will be 15 %, then your final price will be 115% of the previously calculated value.

As you can see, this strategy is quite simple, but it falls under the dynamic pricing category because it takes the changing prices into account, finding the profitable price points for you based on the current condition.

Value-Based Pricing

The example of an e-commerce website and its strategy described above illustrates what value-based pricing looks like in practice. This type of dynamic pricing aims to identify the value the product or service brings to a particular customer and adjust the price on that basis.

For example, a parent of a newborn that leads a very active urban life will be more likely to buy your ergonomic baby carrier than the stay-at-home parent living in the suburbs. Or: the music passionate with extensive audio-related knowledge will be ready to invest in your good sound system more than a regular customer. Sometimes, on the other hand, value-based pricing is all about availability. Remember the pandemic times and the fortunes spent on masks and sanitizers?

For such a strategy to be successful, you need extensive access to customer data and an effective system to process it so that the model can adjust the price to data insights in real time. A significant part of successful value-based pricing is good segmentation and good targeting. That’s because the value may lie in various aspects, and sometimes it’s all about the brand itself. If you sell luxury goods, you will not even try to sell your product to those who don’t recognize your brand. Instead, you will price your product accordingly for those who understand where it comes from and are ready to pay the high price.

Competitor-Based Pricing

Here, the case is simple – you adjust your prices based on the decisions of your competitors. It may take different turns depending on your niche and the competitiveness of your market. You can either try to stand out among your competitors with your price or, analogically, try to find the middle ground. In this case, you pick the competing firms you identify with the most and establish similar prices to theirs.

Both pricing methods may increase the likelihood of purchase. The first one is mainly used in niches where the variety of companies offering the same offer or product is very high, and so is the demand - like FMCG. Since their offers are very similar, they lower the price to attract customers. Companies that target wealthy customers searching for prestige may pick it too, but in an opposite way - by putting it higher than the others.

Bundle Pricing

Price bundling is a strategy as old as time - you sell a few products in a package for a lower price than they would cost individually. Companies, particularly standard retailers, use it often to boost their sales. They can employ dynamic pricing to find the optimal price points that will allow them to maximize the margin in such a practice while enhancing the likelihood of purchase.

Time-Based Dynamic Pricing

This strategy popularized dynamic pricing, making the customers more accustomed to price fluctuations. In its case, the algorithm uses the time-based opportunity, finding the most optimal price point at the very moment for the specific customer. The best example is ride-sharing apps, like Uber or Bolt, which constantly re-estimate the price for the same route based on the current availability of the drivers in the area and the demand. Time-based dynamic pricing is also commonly used in e-commerce, combining customer-related data with time-related variables.

Inventory-Based Dynamic Pricing

In an inventory-based strategy, as the name suggests, the crucial variable is the stock levels. In a nutshell, the algorithm adjusts the prices based on the amount of a particular product stored, dynamizing sales of the products that don’t vend off that well and squeezing the most value out of those that sell fast.

How to Implement Dynamic Pricing?

Just like in the case of any innovation, the successful implementation of dynamic pricing takes some research and preparation. Here are the steps you should take into account.

Setting up the Infrastructure for Dynamic Pricing

In order to calculate the optimal price points, your model needs a constant flow of data. Which data exactly? That depends on the strategy you pick. But even in the most basic one, like cost-plus pricing, you will need to feed your model with the sources of the cost-related information. If you focus on customer habits to optimize your estimations, you should collect customer data across channels. That all calls for solutions that facilitate smooth data processing and storing large datasets. Cloud-based infrastructure is a standard in dynamic pricing, particularly if you don’t only use the model for analytical purposes but also for automated price updates.

Determining the Right Pricing Strategy and Choosing a Dynamic Pricing Model

Whether it is a small company or a big organization, the dynamic pricing strategy implementation should always be preceded by an in-depth analysis.

First, you should audit the suitability of dynamic pricing for your niche and target groups. Even though it always aims at maximizing your margins, this strategy does not have to be doomed to success. Some audiences still approach dynamic pricing with a dose of skepticism. In their case, it may be worth doing A/B tests with your strategies and, above all, taking it slowly instead of going all in.

Reinforcement learning model for dynamic pricing algorithms

Reinforcement learning model for dynamic pricing algorithms

When you are sure to what extent you want to engage in dynamic pricing, it’s time to pick the right strategy and model. There are various strategies to choose from - some of which we described above. The key to finding the right one for you is understanding your industry, target group, and the factors that drive and limit your profit. That’s where the dynamic pricing consultant’s support may be incredibly helpful. They will also help you pick the model that relies on the relevant variables in the appropriate order.

Discrete price-demand model based on Thompson sampling for dynamic pricing implementation

Discrete price-demand model based on Thompson sampling for dynamic pricing implementation

Integrating Dynamic Pricing Model With Other Systems

That part may be very different depending on whether you want to deploy the dynamic pricing model for the purpose of your own website or integrate it with an external system like a booking portal or a marketplace. Usually, the dynamic pricing development company takes care of API integrations so that you can seamlessly update calculated estimations automatically in the external systems. That’s essential if you pick a customer-oriented or time-based strategy that requires constant updates and smooth data processing. You will also need integrations to feed the model with the customer data from the systems in order to find the optimal price points.

Best Practices for Implementing Dynamic Pricing

You can contribute to the success of your dynamic pricing strategy by observing its impact on sales and implementing changes on that basis. Adaptation is essential - the market changes and, with it, the tendencies among your customers and their expectations. The strategy you established one year may stop being relevant a year after. Stay flexible, don’t get attached to one pricing method, and you’ll be fine! Remember that:

  1. Testing is your best friend! Before you stick with one strategy, try a few different on various customer groups. Try to segment them in various ways to observe the impact.
  2. Without measuring, it’s just guesswork. Keep an eye on results to implement changes on time if needed.

Key Metrics for Measuring Dynamic Pricing Success

When measuring the effectiveness of dynamic pricing, you should not stick to one variable. It is a combination of various factors that we refer to below. All these metrics are relatively easy to track and, combined, give you a good idea of whether your dynamic pricing strategy is working as it should.

Are your customers buying more or less when the prices fluctuate? How does the frequency of these fluctuations influence their purchases? What are their patterns - do they mainly wait for the price to drop or buy right away? Are there some current market trends - for example, inflation-induced consumption reduction - that may impact their decisions in the nearest future? It is worth constantly verifying these aspects to check whether your dynamic pricing strategy is effective and adapts to these insights.

Evaluating the Impact on Revenue and Profit Margins

The main goal of dynamic pricing is to maximize revenue and profit margins. If they are not rising, you definitely should rethink your pricing strategy. However, give yourself (and your clients) some time.

Profit will not start rising from day one - your customers need to get accustomed to this change, especially if you are a pioneer in your industry. For a few first months, the margins may even stay lower than before, but it should eventually change, multiplying your profit in the future.

That, of course, is not the case with the marketplaces, the customers of which are used to dynamic pricing by default. However, in such cases, you may be forced to play their game - if you adopt your distinct pricing strategy, they may reject it.

Inventory Management or Resources Utilization

Dynamic pricing can also positively impact inventory management, so monitoring changes in inventory levels and turnover rates can be important for evaluating success. The same goes for services - do you utilize your resources in the most intensive way possible (e.g., minimizing trucks driving empty)? You can set multiple metrics that will track this aspect and impact the model.

Continuous Improvement of Dynamic Pricing Strategy

With time, your artificial intelligence model should get better and better at predicting the impact a particular change will have on customer decisions. If the efficiency is not growing exponentially, you may want to take a closer look at it again to check whether it needs some structural changes and price adjustments.

Benefits of Applying Dynamic Pricing Strategy

Companies across sectors are starting to notice that dynamic pricing is the future. As a much more flexible strategy than fixed pricing, it fits perfectly the unstable times in which prices fluctuate much more intensely than in the past. It is also harder to stay afloat in an increasingly competitive market, and dynamic pricing creates new opportunities for companies to sell. In a perfect scenario, it:

  • maximizes profit
  • boosts sales, especially in the low-demand period
  • reduces the surplus of stock
  • reduces waste and empty miles
  • strengthens the financial stability of the companies
  • strengthens bonds of the customers with the brand (they treat price fluctuations as an opportunity to “hunt” their optimal price range)

Challenges and Limitations of Dynamic Pricing Methods

It’s an impressive list of benefits, but let’s not look at the dynamic pricing through rose-colored glasses. It takes some effort to create a successful strategy, and there are some obstacles you should be aware of.

Technical Challenges of Implementing Dynamic Pricing Software

Dynamic pricing naturally requires more effort and logistics than fixed pricing. Companies should keep in mind that they should have data resources and a flexible system architecture that facilitates integrations to implement a successful dynamic pricing model. Read more about the pros and cons of dynamic pricing in our article.

In order to implement your custom model, you will likely need to hire a specialized team of data scientists that will design the model to solve your specific problem and AI engineers who will deploy it and integrate it with the systems. Specific IT skills and expertise are essential here, and so is solid cloud infrastructure. Also, if your business model relies on external marketplaces, you should make sure that you can customize your dynamic pricing strategy.

The ethics of dynamic pricing is still sometimes considered controversial. Customers sometimes express a feeling of being tricked and manipulated. However, if the company clearly lays out the foundations of its strategy, these claims are unjustified. In the end, such a model can reduce price discrimination by making the products or services more accessible to various target groups. It is not difficult to crack the mechanisms behind it, and once they do, they can take advantage of great bargains.

Another controversial aspect is data collection. The customer-focused strategies need extensive data to understand the behavioral patterns of your target group. However, some customers do not want their data to be processed and pay extra attention to that. You should thus prioritize verifying the legal compliance of your data collection process.

Customer Perception and Acceptance

In the current economic landscape, dynamic pricing is shifting from an option to a necessity. Once accustomed to it and having experienced the benefits it brings, clients rarely want to go back to fixed prices, even though they were skeptical at the beginning. However, it is not guaranteed they will react enthusiastically to this change.

In industries like eCommerce, travel, transport, or logistics, dynamic pricing has already become a standard, so there is nothing to worry about. But if your competitors don’t use this strategy yet, make sure to carry out extensive research.

6 Tips For Companies That Want to Implement Custom Dynamic Pricing Engines

Implementing custom dynamic pricing tools can be a complex process, but here are some tips that companies can follow to help ensure success:

  1. Define your pricing objectives: Before implementing a dynamic pricing engine, it’s important to define your pricing objectives clearly. This includes understanding your target market, identifying key competitors, and determining your desired profit margins.
  2. Collect data and apply exploratory data analysis (EDA): To create an effective dynamic pricing engine, you’ll need to collect data from a variety of sources and analyze it with the help of experienced data scientists. By collecting this data and applying manual exploratory data analysis techniques, such as data visualization and statistical analysis, you can gain insights into your business and your data and develop pricing rules and algorithms that reflect your unique needs and goals.
  3. Develop customized pricing rules: A one-size-fits-all approach to dynamic pricing is unlikely to be effective. To create a custom dynamic pricing engine that works for your business, you’ll need to develop customized pricing rules based on your specific objectives and target market.
  4. Invest in the right technology: Implementing a dynamic pricing engine requires access to advanced technology, including machine learning algorithms and real-time data processing infrastructure. You will need a modern infrastructure that can process massive amounts of data with low latency for the machine learning model to be effective.
  5. Test and refine your pricing engine: After implementing your pricing engine, it’s important to continuously test and refine your pricing rules to ensure that they are effective in achieving your pricing objectives.
  6. Monitor your competitors: Keep an eye on your competitors’ pricing strategies and adjust your own pricing engine as needed to stay competitive.

Kickstart a Successful Dynamic Pricing Strategy

This guide is just a beginning - depending on your specific case, there are various other aspects to remember about. That’s why having the guidance of an experienced, dynamic pricing company is a must. We can lead you through that process, from strategy definition to model deployment and maintenance. If you could use such support, let us know - we will be happy to take this challenge and implement dynamic pricing within your company!

About the author

Dorota Owczarek

Dorota Owczarek

AI Product Lead & Design Thinking Facilitator

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With over ten years of professional experience in designing and developing software, Dorota is quick to recognize the best ways to serve users and stakeholders by shaping strategies and ensuring their execution by working closely with engineering and design teams.
She acts as a Product Leader, covering the ongoing AI agile development processes and operationalizing AI throughout the business.

Would you like to discuss AI opportunities in your business?

Let us know and Dorota will arrange a call with our experts.

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Dorota Owczarek
AI Product Lead

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