Examples of pricing scenarios to optimize your strategy
Companies generally struggle to apply fair pricing for the products and/or services they offer because developing an effective pricing strategy requires brands to conduct market research upfront. This often involves enlisting the help of a specialized structure or relying on an automated computer program capable of developing an evolving pricing model taking into account several factors (demand, season, region, etc.). For companies, the use of artificial intelligence (AI) for price optimization and the development of a pricing scenario adapted to their business objectives is increasingly common.
Which pricing strategy to adopt?
In order for a company to optimize its sales, its pricing must be acceptable to the majority of consumers. Prices that are too low will significantly reduce margins, while an increase in product costs will automatically result in lower sales. Finding the right price will not only allow him to keep a comfortable margin, but also to increase his turnover.
However, it is not always easy in a constantly changing environment, where needs are not fixed, to propose fixed prices. The solution is to vary prices more or less frequently depending on demand. This is known as "dynamic pricing" as opposed to strategies that recommend setting prices according to cost (cost-based pricing) and perceived value (value-based pricing).
The principle of dynamic pricing is to understand demand in order to adjust the price. Thus, it is not uncommon to observe, during a year, price fluctuations for the same product. Many e-commerce sites use this technique to set their prices. But how to estimate the needs in question to adapt its prices? Companies most often use Excel-based software or predictive models using AI to cross-reference information from internal and external sources to produce statistics that provide insight into consumer buying behavior.
Thus, for a pricing strategy to be successful, a company must have reliable data on the customer base and the market to be conquered. With machine learning technology, it can easily identify the optimal price for each product in an assortment assigned to a given store.
Machine learning for dynamic pricing
The concept of dynamic pricing
The challenge for a company specialized in retail or evolving in the mass distribution is to adopt a pricing strategy to maximize its sales, satisfy its customers and protect its brand image. Thanks to the machine learning algorithm, there is a way to achieve all these objectives. Indeed, machine learning will use Big Data for its learning; this ensures that the company will have in its possession reliable data to make accurate predictions that will allow it to keep stocks moving and to stay in line with sales.
For example, dynamic pricing involves setting prices based on the market and demand. High demand would automatically lead to higher prices, while low demand would mean lower prices.
How does machine learning affect product pricing?
The machine will extract patterns from contextual and historical data (location of sales outlets, assortment, inventory status, customer remuneration levels, overall market trends, customer opinions on a product, etc.) and other information (prices charged by competitors and sales seasonality), that will allow the company to evaluate the propensity of customers to pay a certain price for a product. It will also be able to predict their reaction to different pricing strategies and test several scenarios to finally adopt the solution that will allow it to increase its profits and remain competitive.
Let's analyze this practical case: with the data provided by the machine, a pricing strategy based on dynamic pricing will lead, for example, an Internet access provider to propose a price during the week that will not be the same as the one charged on the weekend for the same formula. With such a strategy, the provider in question can be assured of maintaining its margin without sacrificing its revenue, which would probably not be the case if it had opted for a fixed price based on cost-based pricing.
Tailored prices thanks to machine learning
With the help of machine learning and its self-learning algorithm, a company can adopt personalized pricing. In this case, prices will be adjusted according to the needs of each customer and his buying behaviors, thanks to a data partitioning (data clustering) performed within the target customer base. As a result, the company's price offer will be completely tailored, which usually results in an improved customer experience.
Improving the customer experience is not the only benefit that comes from customized pricing. Indeed, such a pricing strategy allows each outlet to maintain a micro-market that could generate additional profits.
In addition to cost-based pricing, value-based pricing, dynamic pricing and personalized pricing, there are other pricing scenarios to boost a company's business strategy.
Take inspiration from the rates charged by the competition to gain in competitiveness
There's nothing wrong with not knowing where to start when it comes to implementing a pricing strategy. Before developing their own pricing model, major brands have tested several models over the years. For example, most of them started their businesses by looking at their competitors' pricing policies for each product category.
This is an attractive option for start-ups that can not only keep an eye on the competition, but also avoid being priced out of the market (offering below average costs).
A company that decides to adopt this pricing strategy is not necessarily looking to optimize its margin, but to gain competitiveness. This sometimes implies offering relatively low prices. In this case, the company can maintain its margin by obtaining its products at a decent cost from a supplier. Its prices can increase if the supply does not fully cover the demand.
Setting prices according to available inventory: the yield management technique
The concept of yield management is simple: act on the price to modulate demand. This pricing strategy consists of increasing prices when the stock of products is exhausted in order to reduce demand and vice versa. If the demand corresponds exactly to the available stock, losses are minimized, and the company is assured of maximizing its revenue.
However, yield management, also known as "revenue management" or "differential pricing", only applies if the company has one or all of the following criteria
- an inability to stock (an unsold product is lost) ;
- a fixed offer (inability to act on the available stock);
- an ability to forecast its activity (implementation of a reservation system or possession of statistics on past sales).
Applying the principle of yield management to the field of sales and marketing would mean, for example, that a company would lower its prices (sales) to generate demand for a stock of summer clothes. Without this pricing strategy, the company would lose a lot of money on this sale.
Lowering prices to increase market share
Increasing revenue is not always the goal when companies decide to develop a pricing strategy. Sometimes, a company may seek to increase its market share in order to be able to operate on a larger scale and improve profitability. Thus, increasing market share is simply a matter of ensuring that you have a better sales ratio than your direct competitors.
Many processes such as innovation, selection of high potential products and/or services, expansion of the product range, etc. can help a company to substantially increase its market share. But it is also possible to act on prices to gain market share. In the framework of a pricing strategy, this translates into a strategic price reduction on product categories with a strong potential to increase market share.
A company that chooses this pricing strategy has two options:
- set its prices at the lower end of its comfortable price range;
- position itself at a slightly lower price range than the lowest competitor in the same product category.
In conclusion, there are many pricing strategies to optimize sales. A company should choose the one that is most in line with its business objectives and that specifically addresses its target customers.