Optimal pricing – The best methods for the pricing process
One of the most important value-added processes of companies is finding the optimal pricing in the course of the pricing process. It encompasses various phases, the details of which vary depending on the industry.
Pricing must incorporate seven essential pieces of information (“7C” of the pricing process), which are described in our blog post “Price optimization – The role of modern methods for market success“.
After the general description in the article “Digital Pricing: The role of price management in the digital transformation” and the presentation of price optimization with the 7Cs of pricing, this article discusses some of the different methods for determining the optimal price. The methods highlighted here result from different types of “observations”. Another area is the methods based on “surveys”, some of which are described in the article “Price determination – methods for optimal pricing decisions”.
There are various approaches to the methods of observation, including
- Price experiments
- Econometric analysis of market data (including online auctions)
- Social Listening (Voice of consumer analytics)
Optimal pricing, which is based on survey methods, is discussed in more detail in this article. These methods include:
- Direct surveys (including Price Sensitivity Measurement)
- Conjoint Measurement
- Focus groups
- Expert assessment
Price experiments for optimal pricing
This method for pricing and optimization is gaining in importance in the course of digitalization. Today, the Internet offers a wide range of possibilities for researching consumer behaviour. Alternative prices can be tested on online portals in different dimensions (customer, time, region, product etc.) with regard to their acceptance. The effect on sales and market shares is recorded on the basis of the behaviour of the buyers. Price experiments should not only be used to test willingness to pay and price levels. Different price-offer structures (versioning; menu pricing) and price models (e.g. subscription models) can also be efficiently tested for their effect on the market.
A/B testing is a very efficient method to assess the customer acceptance of different variants or formats. Systematic version testing is particularly important in online industries and in the content business (e.g. software and web design). The technological potential for measuring customer behavior is constantly improving in the course of digitization.
An example from the retail trade: In stationary shops, so-called beacons are used to locate customers and record their behaviour. These Bluetooth transmitters, invisible to the customer, are integrated into electronic price tags, among other things. The usage behaviour of customers can thus be measured in real time. Consideration processes (length, results, etc.) as well as the customer’s routes and procurement networks are analysed in detail.
Using artificial intelligence, it is possible to interpret the mouse movements of customers in online retailing. For example, it can be analyzed whether a customer – despite having already completed the compilation of a shopping cart – threatens to abandon the purchase at short notice. Measures are automatically derived from historical patterns of behaviour and the course of current ordering processes. The customer’s behaviour control is clearly professionalised by these technical possibilities.
Case study offer configurator in eCommerce
In many sectors, customers can compose digitally supported service packages. As part of the individual selection of services, willingness-to-pay can also be recorded online. One case in point is the online jeweller 123gold, a company that has been taking advantage of the opportunities offered by digitalisation since 2002. The jeweler created a significant competitive advantage with a digital offer configurator. Instead of choosing from a few available models, the customer can design the wedding rings online – the parameters depend on the customer’s upper price limit and thus correspond to the customer’s exact requirements profile. The system recognizes preference patterns from the customer’s selection behavior across the different variants. The possibility of optimizing an individualized product in terms of price-performance ratio is an individual value proposition for the user. A core principle of professional price management is automatically stored with such offer configurators: It is all about trade-offs! Higher services require higher prices. For the user, it is rarely only about the price – what counts in the end is the individually optimal price-performance ratio. The example shows: This is where digitization must start – with the optimal satisfaction of customer needs!
Econometric analysis of market data
In many markets, standardized information can be used for pricing. Price elasticity can be derived from historical data on sales volumes and prices of all competitors. These data are transformed into price sales functions using econometric regression methods. Online commerce provides an excellent information base that allows conclusions to be drawn about price effects.
Online auctions represent a special form of market data collection. Online portals use auctions to systematically survey the willingness of potential customers to pay.in the course of digitalization, the conditions for measuring price effects on sales, turnover and profit have improved significantly, even for classic products (e.g. petrol). Here it must be taken into account that various disturbance variables (seasonal effects, competitive actions, etc.) can influence the measurement of price elasticity. The recording of causal relationships is a matter of causality. Cause-effect relations must be clearly separated from correlations.
“Social listening” for optimal pricing decisions
Social media monitoring will become increasingly important in the future for price-related market research. Statements on the relative price-performance ratio are made very clearly by numerous users in social media. Coupled with this, there are always wishes and suggestions for improvement from customers, which can be used for the further development of the offers and price management. The term “social listening” illustrates what will be much more important in the future than it has been in the past: All qualitative and quantitative information on customer perception must be used in a targeted manner. They are often the best early indicator of the actual impact on the market. Software from companies such as SAP (Qualtrics) is available for the use of innovative methods of price optimization (“Voice of Customer” Analytics).
About Frank Frohmann:
Frank Frohmann has already been engaged with questions of digitalization in projects for B2C and B2B companies at the end of the 90s. His comprehensive wealth of experience with digitization strategies and price optimization is based on three main fields of activity: External management consulting (Simon-Kucher & Partners; since 1996), operational price management (Lufthansa; cargo and passenger) and in-house consulting (Bosch and Evonik, among others). His book “Digitales Pricing” (only available in German) was published by Springer Verlag in September 2018.
Frohmann has been working as Business Development Manager Pricing at Vistex GmbH since September 2019.
Vistex Inc. was founded in 1999 and has its headquarters in Hoffman Estates, USA. As a Global Solution Extensions Partner of SAP SE, the company offers SAP-based IT solutions with specialization for the automotive, chemical, consumer goods, food, high-tech, manufacturing and pharmaceutical industries, as well as retail and wholesale, especially in the go-to-market sector.
Whitepaper “Digital Transformation and Pricing” by Frank Frohmann
When Frank Frohmann’s book “Digital Pricing” was published by Springer Gabler in September 2018, it generated great interest, not only in the German-speaking market. Before an extended English edition is published, the gap will be closed with this white paper, which describes essential aspects of digital price management.
Digital Transformation and Pricing