At the heart of any pricing system is the price logic – that is, the way we want the price to be determined for each combination:
customer x product x purchase context
Price logic is a derivative of two issues:
– the already existing historical relationships that can be obtained from numerical analysis (while in the “price cloud”, by definition, they are visible in a blurred and delicate way, but even such delicately outlined patterns can be sanctioned in the price logic and thus they can have a better effect in the future)
– on the other hand, our business decision as to how these prices should be shaped. The logic depends on the management of the company, and whether this decision is well prepared will depend on how successful the implementation of such logic will be.
Primarily, the price logic is the very algorithm of price allocation, but the key to it is to understand the two variables of this price formula: customer segmentation and product classification.
Customer segmentation is a process in which we divide customers into homogeneous groups in terms of key characteristics. Some of these characteristics can be obtained from data analysis, i.e.:
– average order quantity,
– order product structure,
– the width of the assortment purchased
Other qualitative characteristics can be partially got from the CRM system or directly developed / arranged with the sales force. This is mainly about such elements as development potential, special price sensitivity, other special features of the customer influencing our relations.
That is why it is important to go through with the sales force at least once a year in a structured way, through the customer list and consider what value the customer represents for us (nowadays and in the future), how sensitive he or she is and what we should offer him or her in each category of products or services they purchase from us. Numerical algorithms can, of course, help us a lot in this exercise.
Product classification in terms of price flexibility
The second important dimension includes products. We primarily care about the classification of products in terms of price flexibility, which, as a result, allows us to determine the appropriate margin range for a given product, from which, after imposing customer characteristics, we will receive the recommended final price. We often see that in enterprise systems a certain characteristic margin (margin is a more universal measure than the price, which obviously depends on the cost of acquisition) is assigned to product groups. However, we should remember that even within one product group, we have a lot of differentiation in terms of price flexibility. The best-selling products with the highest turnover tend to be more price-sensitive (price flexibility).
However, it is not only the product category, turnover or frequency that influences price flexibility – it is the brand (A-brand products are less sensitive than the ones of popular brands), the number of substitutes (which determines the strength of competition), the price (we usually pay more attention to the price of cost products – however, in B2B this is not the rule as our customers rather pay attention to turnover), product uniqueness or novelty item status.
The price logic algorithm is based on customer segmentation and product classification when determining the optimal price (margin / mark-up) for a given customer x product combination.
It would be easy if everything could be contained in algorithms. In real life, especially in the B2B segment, we cannot count on it. The price logic will certainly better adapt the price to the product and the customer, reducing the number of interventions and negotiations (which is one of the important advantages of introducing price logic), but there will always be customers and purchasing situations when it is necessary to create special conditions.
Sometimes, in case of particularly large transactions, there can be a multi-level approval of a price change. However, by increasing the degree of control, we have to take into account the fact that the process will involve more employees and managers and the process will take longer. And what is the most important – the more decisions have to be made individually, the decisions are more automatic, clichéd, and simply worse. It is therefore necessary to calibrate the parameters of the process in such a way as to maximise the number of prices resulting directly from price logic and, in the case of necessary deviations, to establish the conditions for acceptance so as to capture all material transactions, on the one hand, and, on the other, not to accuse decision-makers of making too many individual decisions that they would have to make.