What with long-term personal relationships, individual negotiations and a deliberate lack of transparency, B2B pricing has traditionally been a highly complex business. In dynamic pricing, or automatic price adjustment by means of algorithms, many observers now see a tool that might change time-honored pricing processes. But is dynamic price management really a model that can be used successfully in B2B business?

Dynamic pricing has long been standard practice in B2C business. Stationary traders such as filling stations have for years adjusted their prices automatically, and they are by no means the only ones to do so. In online trading too, competitors have developed sophisticated algorithms so as always to be able to offer their customers individual, customized prices. As in so many areas, Amazon is considered to have pioneered this trend. Amazon is well known to adjust its prices several times a day on occasion. According to a report in “etailment” magazine, products can in this way change their prices up to 70 times a week in peak periods.[1] And Amazon is not alone in pursuing this strategy. As the Brandenburg consumer advice center recently discovered in a random sample, dynamic pricing is already a reality in 15 out of 16 large B2C online shops.[2]

In view of this option it is no wonder that B2B traders are increasingly analyzing whether and how they can integrate dynamic pricing into their business model. It does, after all, offer considerable advantages. B2B business also frequently faces volatile framework conditions such as a fluctuating purchase price. By means of automatic price adjustments fluctuations of this kind can be passed on efficiently to the customer—or that, at least, is the idea. In addition, dynamic pricing might help to ease the burden on sales and distribution or even, in the long term, replace them entirely.

B2B Pricing is Subject to Numerous Influencing Factors

To date, however, the B2B sector has found it hard to introduce automatic price adjustment. This is due especially to the traditional pricing models that B2B traders have used in an attempt to come as close as they can to the best possible combination of achievable margins and high order volumes. B2B business today is subject to countless influencing factors that make pricing an extremely complex affair and make automatic price adjustment by means of algorithms more difficult. To give an idea of this complexity I will here merely list a few examples of criteria that can influence pricing in B2B business.

  • Purchase price development: The development of purchase prices differs very widely from product to product. While some products are characterized by long-term price stability, prices in other product groups such as commodities or fresh foodstuffs are highly volatile.
  • Individual contracts and agreements: The B2B sector has traditionally been very dependent on sales representatives. Business relationships have frequently existed for years. Buyers and sellers often know each other personally. This tradition has led to a culture of individual pricing based on the negotiating skills of the business partners. Automatic price adjustments are only possible to a limited extent in this mostly contractually fixed framework.
  • Strategic considerations: A B2B trader’s strategic considerations are naturally reflected in his prices. For a large customer with the prospect of significant sales a trader will, for example, be more inclined to offer low prices than in negotiations with what look like being small fry customers. But from what level of sales is a customer a large customer? As a rule, definitions of this kind are not standardized in B2B trading organizations; they are subject to the individual sales representative’s scope for setting prices. That makes drawing up universal rules for an algorithm something of a challenge.
  • Competitors’ prices: The B2B market is characterized by a serious lack of transparency. Due to this lack of transparency in contrast to the transparency of the B2C market it is not easily possible to determine the competitors’ price models in detail. Automatic price crawling in online shops is certainly more or less impossible because “genuine” competitive prices are not generally disclosed openly, or only to individual customers once they log in.
  • Regional price differences: Prices can differ widely by region in the foodstuffs sector, for example. Sea fish, for instance, can be offered for sale at significantly lower prices on the coast than in Bavaria. A B2B trader can take this into account in his pricing, but he must not necessarily do so, of course.

The soft skills of a human sales representative cannot be mapped—or at least not in the foreseeable future—by a standardized algorithm.

This list could be extended without difficulty to include many other criteria. With all of these influencing factors and, above all, their combinations and interdependencies, fully automatic dynamic price adjustment is virtually impossible. Dynamic pricing is also made more difficult by the countless soft skills that the price representative brings to bear on pricing with his knowledge of the customer and the market. Is, for example, the customer’s buyer an old hand who knows inside out how market prices have developed over the past 15 years, or is he a greenhorn who has yet to gain this experience? Does the buyer know the company next door’s buyer personally and does he discuss with him the prices that are on offer? And what prices does the most important competitor offer the buyer in question? All of these questions, to which a good sales representative will as a rule know the answers, are of decisive importance for individual pricing. Furthermore, a human sales representative is able to find creative solutions to challenges that arise and at times to depart from the usual pricing paths for the company’s benefit by, for instance, offering a disgruntled large customer a special goodie to make him happy once more. These soft skills cannot be mapped—or at least not in the foreseeable future—by a standardized algorithm.

Digital Tools Should Support the Sales Representative, not Replace Him

So individual, local pricing by a competent field sales force will continue to be the rule in the B2B business in the foreseeable future, especially as this form of pricing is part of the business model of many B2B traders and via cross-subsidization and mixed costing often makes an essential contribution to these companies’ viability. This does not mean, however, that pricing must continue totally unchanged. Instead, this process can and should be supported systemically. The primary objective of B2B business should not be to attempt to replace its field sales force by technical innovations but to place tools and data at its disposal that enable it to concentrate even more on its core tasks of maintaining close customer contacts, boosting sales and improving the company’s commercial key performance figures.

Digital tools can make the sales representative’s work perceptibly easier.

The daily work of the field sales force offers several opportunities for digital support. A major challenge for the sales representative is, for example, to have all the factors that influence his work in his head and to take them sufficiently into account in price negotiations. He must, for instance, keep track of the current prices of countless articles, different price change intervals, different contacts and people involved, the price strategies of the competition and the company’s own business development and incorporate them in his work. There is also potential for optimization of preparation and follow-up of sales negotiations. In the run-up to negotiations key figures must often be researched, products pre-selected and possible price ranges defined. In the follow-up the results of the negotiations (new prices, contractual terms, etc.) must be recorded, validated and transferred to the trader’s systems. At present all these tasks are performed to a large extent manually and take up a great deal of the sales representative’s time.

Digital tools can make these processes significantly more efficient and the sales representative’s work perceptibly easier. Tools of this kind are, for example, able to preselect automatically products the price of which must be renegotiated so that the sales representative does not have to do this research himself. In addition, key figures for all of the relevant influencing factors can be provided in order to assist the sales representative in discussing pricing with customers. Based on the datasets the applications can also automatically suggest prices that the sales representative can use or not as he sees fit in view of his personal assessment of the situation and his knowledge of the customer.

The aim of digital tools of this kind is thus not to price products automatically by means of an algorithm but to assist the human sales representative in specific negotiations with the customer. In this way the sales representative’s special know-how not only continues to influence pricing; he also retains the final power of decision on the price. At the same he is effectively supported in his daily work and relieved of the burden of many time-consuming ancillary tasks. That is why the usability of applications is of decisive importance. Only when they are as intuitive as possible and easy to use will they really make the sales representative’s work perceptibly easier.

Does Dynamic Pricing Have a Future in B2B?

Even if digital tools change B2B sales in the future, B2B will continue to be a predominantly people business. In view of the significantly higher order volumes when compared with B2C business pricing decisions should continue to be reviewed and made by people. Nevertheless, meaningful application scenarios for dynamic pricing exist in B2B, albeit not in business-critical areas. B2B traders do, for example, have a long tail and various niche product ranges that are of limited interest for their clients. Pricing them individually and manually would bind many resources that might more sensibly be deployed elsewhere. It might also make strategic sense to adjust prices automatically more for smaller customers in order to have more capacity available for individual care of large customers.

What can be said for sure is that it makes sense to combine in B2B business the possibilities of dynamic and manual pricing. Personal customer care and individual price negotiation will, however, continue for the foreseeable future to play a significantly greater role than in B2C business. But there are no generally valid blueprints for deciding how to combine dynamic and manual pricing. Companies must draw up an individual solution that is suitable for their organization, their industry and their competitive situation.

[1] https://etailment.de/news/stories/Dynamic-Pricing–Wunderwaffe-risiko-4220

[2] https://www.verbraucherzentrale-brandenburg.de/pressemeldungen/presse-bb/onlinehandel-das-spiel-mit-dem-dynamischen-preis-28651

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