Dynamic pricing is a particular strategy that allows adapting a company’s needs to market conditions, which are continuously evolving.
If you also believe you have this need, you need to know precisely what we’re talking about, so as to exploit all its advantages and reduce its potential risks. In this guide you’ll find the definition of dynamic pricing and the detailed explanation of its functioning, with all the pros and cons. Not only that: you’ll have the opportunity to learn about some practical application examples and the best strategies to implement between present and future. Buckle up: let’s go!
Dynamic pricing what it is: definition and meaning
The meaning of dynamic pricing, also known as flexible pricing, refers to a flexible price determination strategy through which companies continuously modify the prices of their products or services based on changes that occur within the market.
Difference between dynamic price and traditional pricing
The main difference between dynamic price and traditional pricing consists in the frequency with which the selling price of products or services is modified: while the traditional strategy provides for rare and periodic changes, the dynamic price technique presupposes continuous changes in almost real time. This, obviously, has a natural consequence: dynamic price, unlike traditional pricing, has a high reactivity to market changes and, in particular, to competitors’ prices.
A further difference is related to the way to calculate the selling price and, specifically, to the fact that price changes, in dynamic pricing, occur automatically thanks to data analysis and advanced algorithms, while in the traditional strategy revisions are manual and based mostly on market research and sales history.
Dynamic pricing model: how it works
We just mentioned algorithms and Big Data, fundamental tools for the functioning of the business model based on dynamic price. We’ll talk about them again in a few lines but, first, it’s necessary to focus attention on the variables that influence dynamic pricing.
The variables that influence dynamic price
One of the main variables that algorithms take into consideration to establish the price in dynamic mode is market demand (current and expected): fundamental, in this sense, are sales trends, seasonality, and future events that can modify demand.
Another variable is supply, which can vary based on stock availability and supply capacity.
Especially in sectors characterized by high competition, a variable to keep in great consideration concerns the prices and marketing strategies implemented by competitors.
Other variables capable of modifying a dynamic pricing strategy are consumer behaviors (which can be investigated through the analysis of historical sales data but also through website actions) and their reviews (or feedback in general).
Last variable to consider, but certainly not least in importance, is the cost of production, storage, and distribution of the product. Don’t forget that the goal remains to ensure an adequate profit margin.
Algorithms, Artificial Intelligence, and Big Data
As we’ve already had the opportunity to mention repeatedly, dynamic pricing models adopt innovative technologies, such as, for example (but not only), algorithms, Artificial Intelligence, and Big Data.
The analysis of the latter, for example, allows access to enormous quantities of information from different sources and to be able to identify patterns and trends capable of suggesting changes to be made to the selling price of products or services.
Those who adopt dynamic pricing resort to AI to develop advanced predictive models based on multiple variables and to automate the pricing process, eliminating human intervention.
Algorithms based on Machine Learning manage to predict future trends related to demand and allow making changes to the selling price more quickly.
Internet of Things also contributes to the correct functioning of dynamic pricing processes, providing real-time valuable information on stock availability or goods transportation conditions, but also on customer behavior in store.
Similarly, modern inventory management systems allow optimizing prices and warehouse flows based on stock availability and demand forecasts.
There’s another aspect to consider regarding the correct functioning of dynamic pricing models: it’s transaction security. In this regard, important assistance is offered by modern blockchain technology.
Advantages and disadvantages of dynamic pricing
Knowing the advantages and disadvantages related to the adoption of a particular strategy is fundamental. In the next lines you’ll discover benefits and risks of dynamic pricing.
Benefits for companies: margins and competitiveness
The main advantages for companies that decide to calculate the selling price of their products or services in dynamic mode are the possibility to maximize revenues in every period, capitalizing on sales opportunities based on demand peaks, and to always remain competitive in the market.
Another important benefit concerns, as already highlighted, better inventory management.
Risks for consumers and perception of fairness
The main risk related to the adoption of a dynamic pricing model refers to consumers and, specifically, to their possible confusion and, in the worst case, dissatisfaction that can derive from frequent price changes. The challenge to win, in this sense, is to be able to explain your decisions correctly and timely.
Practical applications of dynamic pricing and success examples
Dynamic pricing is applied in different contexts, even very different from each other. Let’s discover them together.
ECommerce and SaaS: dynamic price software
If you’re thinking about designing an eCommercev you should know that many companies in this field effectively adopt dynamic pricing. Among these, Amazon stands out, which is used to frequently updating the prices of its products based on various variables, from demand to stocks passing through consumer preferences.
Among SaaS companies, dynamic price is adopted especially in some specific sectors: among these it’s possible to mention hospitality, ticketing, online marketplaces, and platforms that offer online content.
Transportation and travel: from car sharing to airlines
Various companies that offer ride-sharing services, such as for example Uber and Lyft, adopt dynamic pricing models to manage demand during peak periods, increasing prices at times when demand is higher than the supply of available vehicles.
As for travel, you’ll probably not be surprised to know that airline ticket prices can vary even considerably based on the booking date and the departure date. This is a direct consequence of the adoption of a dynamic pricing strategy.
Physical stores
In recent times even physical stores have started to adopt dynamic prices thanks to particular tools, such as electronic labels, and real-time data monitoring technologies that allow this type of business as well to adapt prices based on stock availability and demand.
Strategies to implement dynamic price
Having reached this point, it’s fundamental that you know that dynamic pricing is based on various economic theories and price models.
How to choose the right dynamic pricing model
Among the economic theories that guide the implementation of dynamic pricing strategies, it’s possible to cite the theory of demand elasticity (which measures the reactivity of the requested quantity of a product or service in relation to price variations) and game theory (useful for predicting reactions of competing companies to price variations).
Among the models, instead, stand out the one based on reservation price (the maximum amount a consumer is willing to pay for a good or service), the one centered on equilibrium price (the exact meeting point between demand and supply), and the one that considers price in relation to the value of the product or service perceived by the consumer.
In this last regard, it’s proper to remember the words of Warren Buffett:
“Price is what you pay, value is what you get.”
Monitoring and continuous adjustments
Beyond theories and models to adopt, there’s a fundamental principle you must keep well in mind if you want to successfully implement your dynamic pricing strategy: for it to prove effective, you must carefully monitor the consequences of every price change (even minimal) so as to be able to continuously adjust your aim in response to every scenario change, whether it’s related to consumer demand or competitor behavior.
Future trends
Before writing the final word on this guide dedicated to dynamic pricing, it’s appropriate to look to the future.
AI and price automation
Artificial Intelligence already plays a decisive role in dynamic pricing models but future trends show that AI will become even more central in relation to the automation of price variation processes for products or services.
Toward greater personalization
The other trend that can be identified in the future of dynamic pricing is personalization, made possible by increasingly sophisticated machine learning algorithms capable of analyzing consumers’ individual habits, their willingness to pay, and their historical preferences.
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