Optimize your prices with a dynamic pricing strategy
The market is constantly evolving, whether in terms of the practices implemented by professionals, new consumer habits or the increase in supply.
Today, traditional sales methods, which are based more on relationships, are no longer adapted to the realities of the market. With the development of online sales and the improved accessibility of information by consumers, customers are better informed and no longer hesitate to buy from different companies if they can get better prices.
This is why optimizing sales prices according to the market has become a strategic issue and a competitive advantage that is essential to their survival. To constantly adapt their prices and offer the right price to their customers, many companies are developing a dynamic pricing strategy.
Would you like to know more about this topic? You are at the right place, because we propose you to discover all the subtleties of the dynamic pricing strategy.
How dynamic pricing works
Dynamic pricing is nothing more than a price optimization technique (margin, sales, turnover, promotions, etc.) used today in almost all areas of business. The objective is to improve profitability and to increase performance in order to be more competitive with the competition.
Moreover, dynamic pricing is not a new policy. Some sectors such as passenger transport and tourism have been applying it for many years.
Examples of dynamic pricing applications
What better example to explain our statements than the price difference between high and low season? Indeed, it is not uncommon to see prices rise depending on the period of affluence (winter for ski resorts, summer for tourist and seaside resorts).
Moreover, this seasonality also applies to the sale of products in the trade. For example, it is better to wait until winter to buy garden furniture in order to take advantage of more interesting prices than those charged in summer. Well, in theory, because in reality, this is not always the case. While it is easy to believe that prices are always higher when demand is high, some companies prefer to lower the selling price of their products. This is what dynamic pricing is all about: finding the best strategy to increase sales.
Thanks to the implementation of a variable and flexible pricing policy, companies can adjust the price of their products and services to the market situation (the game of supply and demand, but also in relation to the competition), to the strategic factors specific to each sector of activity (weather, season, current events, etc.) or to the profiles and consumption habits of customers.
The development of marketplaces and price comparison sites has strongly contributed to the rise of dynamic pricing, on the one hand because companies have easier access to their competitors' information, but also because direct competition leads to a price war.
The limits of dynamic pricing
Examples of dynamic pricing are numerous in everyday life (variable fuel prices or train and plane tickets, discounts on products at the end of their shelf life, etc.). And even more incredible is the fact that even mass distribution and retail food stores are now practicing daily price optimization. In addition to the usual promotional sales periods, more and more retailers are now equipping themselves with RFID (digital display) labels, thus replacing the traditional paper price labels.
We are still far from the wonders of dynamic pricing as it is practiced in online sales (we will come back to this in what follows), but already supermarkets are adjusting their prices in an automated way.
What about price transparency and unfair competition?
To avoid abuses, French law regulates the freedom of prices and imposes limits. To this end, the law regulates the prices of certain sectors, in which the increase is limited, either to guarantee competition or to avoid a surge in prices (the energy sector for example or health).
In addition, price freedom must respect the rules of healthy competition. Accordingly, certain practices are prohibited, such as dumping (resale at a loss), resale at a fixed price (the supplier imposes the selling price on the reseller), deceptive practices (such as a discount on a previously inflated price) or price gouging (selling price that is insufficient in relation to production costs). On the other hand, selling at very high prices is not prohibited.
The dynamic pricing strategy to boost revenue
Dynamic pricing is a technique that aims to adjust sales prices according to the market, the context and the customers. But this technique alone is not enough, it must be consistent and regular, because the reputation of the company depends on it. This is why dynamic pricing is part of a more global approach, a strategy in its own right aimed at achieving very precise and clearly defined objectives.
The challenges of the dynamic pricing strategy
The implementation of a scalable pricing strategy is therefore part of a global approach, as it represents much more than just an increase in revenue for companies. Based on sales forecasts, a pricing strategy contributes to
better inventory management (reduce stock-outs or surplus) ;
control of various logistics costs (transport, storage, handling, delivery, etc.);
- a better knowledge of market trends (essential for business development and innovation);
- a better understanding of customer reactions and behavior (loyalty, customer relations, adapted communication, etc.);
etc.
The first challenge of a dynamic pricing strategy is to anticipate market changes in order to be proactive and not reactive (to suffer and adapt to changes). This is why a company's pricing policy is based on sales forecasts.
Thanks to predictive marketing models, companies can determine the major market trends (past, current, future), such as the best-selling products. From this data, they make their strategic choices (or bets). As we explained earlier with the example of garden furniture, one company may decide to raise its prices when a product is in high demand, while another may opt for the opposite strategy.
Several strategies can be implemented:
- lowering the price of the product in relation to the competition while increasing the price of accessories sold separately, which allows the customer to be captured with the product and to initiate the process of buying accessories;
- pricing based on stock, called yield management, the lower the stock, the higher the selling price;
- the surge pricing strategy, which consists of increasing prices when demand increases while supply is insufficient;
- pricing by segmenting customers into several groups according to their profile.
Finally, it is now more common to implement a customized dynamic pricing strategy for each customer. Of course, this is only possible in the context of online sales. But how? Thanks to artificial intelligence which allows to combine millions of pieces of information.
Machine learning and big data at the heart of dynamic pricing strategy
Thanks to the union of big data and machine learning, predictive models allow the analysis of customer data, such as their average shopping cart, the history of cart abandonment, the maximum price of products consulted, etc.
Thus, for the same product, consulted at the same time by two customers, the price can be adapted to each profile and therefore different. The criteria that can be taken into account in personalized pricing are various. For example, it could be the value of the phone used to consult the e-commerce: an iPhone user could then be offered a higher price than a user of an entry-level smartphone.
The arrival of machine learning (the training of algorithms by learning as they are calculated) in the business world allows companies to make faster and better documented strategic decisions, reducing the risk of errors. To do this, sales forecasting software allows companies to cross-reference numerous data and analyze certain variables, such as the marketing strategy that resulted in the highest margin, the most purchased product during the last promotional sales, the most effective sales channel, etc.
But because progress is unstoppable, predictive tools reduce the risk even more since they can simulate the effects of a marketing action or a pricing policy on customers. In addition, they allow to answer one of the major questions when implementing a dynamic pricing policy: what is the price that customers can accept? In other words, what is the minimum and maximum price they are willing to pay for a given product?
The dynamic pricing strategy is therefore an essential process for the performance and profitability of a company, allowing it to optimize prices according to the market while adjusting the "product" portfolio (and therefore inventory management) to demand in order to offer the right product, at the right time and at the best price.