Price optimization combines all procedures for pricing and price setting. Its purpose is to implement the pricing policy in such a way as to achieve its objectives as well as possible. The types and methods are presented here.
Types of price optimization
The possibilities to optimize prices can be classified in different ways. This helps to keep the overview and to get to know important parameters.
Dynamic – Static
Prices can be set at the beginning of the product launch or during the product life cycle. If the price or the sequence of prices is optimized at the beginning, this is called static price optimization. However, if the adjustment takes place during the market phase, this is referred to as dynamic price optimization.
Static price optimization does not react to deviations of the condition from the assumptions. This makes the procedure vulnerable to wrong decisions. However, planning is simpler and less effort is required for information gathering.
The dynamic variant, on the other hand, incorporates current information into the price decision. However, the amount of information collected is higher and the procedure is therefore more time-consuming.
Mixed forms are also conceivable and are used. This could take the form of opting for a price sequence strategy at the beginning, e.g. penetration strategy or skimming, and defining a corridor for the price trend. However, the exact amount of the adjustment and the time period are then determined at unspecified points in time.
Number and frequency of optimizations
When and how often a price is adjusted is also a distinguishing feature of different types of optimization. The range extends from once to an indefinite number, always when it “appears” necessary. How the new prices are then determined falls into the category “dynamic or static”.
Price optimization always follows a purpose. However, this purpose can be different, which is why the prices actually charged differ. Often, profit and contribution margin are considered the target figures. These should be as large as possible. But there are also other goals that a company can pursue. Basically, these must contribute to the achievement of the overall objective of the company (for example, survival). It is therefore possible that the pricing targets may change over time.
Maximize sales quantity (as long as the price is greater than the variable unit costs).
The period under consideration plays a major role here.
In the penetration price strategy, profit is initially foregone in favor of a high market share. The high market share should later be expressed in high profits and the price should increase.
Manual – Automatic
The prices can be calculated by humans “by hand” or automatically by computer. In a fully automated system, the algorithm would search for all the necessary data itself to calculate the optimal price and feed it into the merchandise management system. The fully automated procedure is necessary if prices are to be adjusted dynamically and a large assortment is available.
More common, however, are interim solutions that allow for employee intervention.
Global – individual
In addition to the question of how high the price should be, there is also the question of which customers or customer groups the price should apply to. In the ideal case, it is possible to determine the willingness to pay of each individual customer and set the price exactly so that this will be skimmed off. In e-commerce, it is possible to segment customers based on various characteristics (operating system, purchase history after login, click behavior, etc.) and thus adjust the price group by group.
If, however, the optimum is formed over all customers, one speaks of global price optimization. The finer the segmentation of customers, the more one speaks of individual optimization.
The figure provides an overview of the types of price optimization available.
Methods of price optimization
The aim is to find and demand the optimal price. Various methods are available for this purpose. Which method is used for price optimization and makes sense depends on the objectives and the type.
Nowadays, price optimization is done by software and an automatic evaluation of competitors (see automatic competitive analysis). This is particularly common in online trading, as data is available in real time, can be evaluated and prices can be adapted to the new situation. For this purpose, algorithms are used that take various parameters into account. Such parameters can be:
Purchase click rate (in online trade)
Predetermined upper and lower price limits
Prices of other, similar products
Information on broken prices
Some of the algorithms used “learn” independently which price brings good results under which conditions and then adjust them automatically.
There are providers who have specialized in certain shops or shop systems (Amazon, Ebay etc.). There you can read out competitor information and adjust your own prices according to the guidelines and rules you have given.
Time series analysis, competitor analyses and specifications from the price strategy are available for manual price optimization.
With the help of A/B tests you can check which prices generate which sales.
They are more suitable for manual, one-time or periodic adjustments. However, a permanent A/B test is also conceivable, but more complex. The problem here, however, is that over a long period of time you have to assign customers securely to the individual groups and require a large number of sales until the results are meaningful and reliable.
One problem is that the considered time horizon for the optimization is chosen correctly. A short-term optimization can turn out to be wrong or not optimal in the long run.
A company manufactures products of low quality and thus actually follows a low-price strategy. However, it can be seen that the price can be set higher and thus a higher profit can be achieved in the short term. However, it is only after the purchase that customers notice that the quality does not meet the expectations that one had due to the higher price. Therefore the brand gets the image “expensive and bad quality”. Word gets around, so that later customers do not even consider this brand or product in their purchase decision, even if the price has dropped to a level appropriate for the quality.
Price optimization can therefore be in contradiction to the pursued price policy. Especially in the case of automatic price optimization, the algorithm must be given exactly which strategy is being pursued.
Isolated consideration not optimal
The price optimization for a product does not only have an isolated effect on the sold quantity of a product but also on other similar products or the whole shop. It must be taken into account that the perception of the price by the customers often takes place in comparison to other products. A price reduction therefore makes other similar products or expensive appear, whereas a price increase makes other products appear cheaper. The sale of different products can thus be controlled in a targeted manner.