If you want to increase prices and ask yourself how high a price increase can be without losing customers, or which feature you could perhaps do without for cost reasons in order to keep prices stable, you will soon realize that this is an extremely risky bet without empirical data. In the following, we present a tool that predicts the behaviour of your customers when prices change or when the offer changes. Along the way, you’ll also get information about your brand value.

Price is the most important profit factor for a company. If it is possible to increase prices by a few percent without losing sales, many companies can double their profits. However, this is only possible if the killer application is known, i.e. those product features for which the customer is willing to pay more money. More and more often, these killer applications are not in a technical achievement, but in a special feature of the service (fast delivery, warranty periods) or in an emphasis of an existing feature: Although all windows are “custom-made”, this feature is not communicated by the window industry. However, customers are willing to pay more for custom-made windows. The situation is similar when safety, convenience or sustainability are highlighted, provided of course that this corresponds to the facts

A market simulation also clearly shows whether there are price thresholds, i.e. a price which, if exceeded, leads to a massive drop in sales. However, price increases up to just below the price threshold cost almost no sales. If you know the price thresholds, you can either increase prices without losing sales (a previously wasted profit) or you know the maximum price for a large target group.

In addition to price and product features, the brand plays a central role in the purchase decision. In this context, the market simulation answers a whole series of central questions on the topic of brand: First, it can be determined what share of the overall decision the brand plays at all. There are markets where 60 – 70% of the decision is based on the brand (and thus not on price or product features) and there are markets where brands play virtually no role. Much more important, however, is the question of what value one’s own brand has in comparison to the competition. The market simulation can express in Euros per product whether there is a positive, neutral or even negative brand value. In our experience, there are often astonishing surprises in this area in particular.

The basis of the market simulation is in no case a questioning of consumers about their wishes à la: “What is the maximum you would pay for this brand? This would only result in meaningless wishful answers. Valid market simulations are based on a realistic simulation of purchase decisions by means of a software-based Choice-Based-Conjoint-Analysis, which simulates consumer decisions and very realistically simulates the change of decisions and brand shares. For more details, please refer to “The road to market simulation”

The road to market simulation

The CBC (Choice-Based-Conjoint) in practise

What actually happens if you increase prices by 5%? And what would be the effect of shortening the delivery time to 7 days or extending the warranty to 2 years? What would have been unanswerable years ago can now be done at the push of a button. The market simulation not only shows how market shares are reshaped by price or product changes, it even shows which competitors you lose and from whom you gain market shares. We will show you how this works here:

When customers (whether B2B or B2C) make a purchase decision, this is co-determined by a bundle of characteristics: If you’re an Apple fan, you’ll buy this brand and see if the price still fits into your budget. Someone who is not interested in brands will, for example, look at the price of a computer monitor in relation to the most important product features.

In each case, a choice is usually made from different offers or a purchase is not made. This is exactly what market simulation models based on choice-based conjoint are based on.

In a first step, those features must be defined with the client who significantly influences a purchase decision. Of these, price and brand are almost always predefined. Since a maximum of 6 – 8 features must be queried, it can make sense, especially with technical products, to have a focus group beforehand so that one does not forget an essential purchase criterion, which is often not technical at all, such as “fast delivery” or “user-defined colour”.

Once the decisive product features and their various characteristics (e.g., screen diagonal) have been defined, the field phase can begin: Product feature – screen diagonal; characteristics: 42 inches, 49, inches, 55 inches, etc. the competitors to be included in the analysis defined, the field phase can begin. Using an online survey, the purchase decision process is recreated as realistically as possible by requiring respondents to make several product comparisons. In practice, several different product bundles are suggested to the respondents, which differ from each other in terms of brand, price, and other defined product features. The respondent thus has to weigh the different product features relative to each other and ultimately decide which option to select.

If all the product comparisons have been carried out successfully, it is then possible to calculate how important the brand, the price and all the other product features taken into account are for the purchase decision process.  The software behind the survey enables the statistical calculation of so-called part worth values for the individual product features. In this way, it can ultimately be validly determined which features are particularly important for the product evaluation or decision, as well as the degree to which each feature is preferred from the customer’s point of view.

However, this superior methodology not only makes it possible to analyse the relevance of individual product features in the decision-making process, but also to simulate the impact of product and price variations on the achievable market share. Based on the part worth values determined, the “share of choice” in the sample can be calculated – in other words, what percentage of respondents would opt for a particular product-price variation. All the results of the CBC analysis can thus be combined in a simulation tool that shows, on the one hand, which market conditions – in terms of the “Share of Choice” – prevail in the market for certain offers and, on the other hand, how these market conditions change with price or product variations. In other words, the software allows you to simulate the extent to which you can increase your market share by lowering your prices or improving your product, and from which of your competitors you steal market share in the process.

If you have further interest in a CBC, please feel free to contact us here

22/09/2022

Copyright: Interconnection, Publication free of charge for coverage regarding the study and InterConnection Consulting.