Latest Pricing Insights from PriceBeam

Guest author: Univ.-Prof. Dr. Oliver Koll, Professor of Marketing and Partner at IMARK Strategy Consulting

What is a Price Premium?

There are a number of different metrics one can use to evaluate brand strength. Brand recognition, likeability, willingness to recommend, readiness to purchase are some of the most popular ones. A number of studies have shown, that these cognitive and affective factors are also linked with the consumers’ willingness to pay for a brand’s products. The more appealing a brand, the more the consumer is typically willing to pay for its products. Therefore, a comparison of the willingness to pay for a brand with relevant references products or “NoName” competitors provides insights into a company’s brand strength.

That value-based pricing offers a great avenue to strong prices and significant profits is probably clear in many pricing practitioners' minds. But what is also important to remember is that a value-based pricing strategy should be data-driven: data about customers' willingness-to-pay. Data about value drivers. Data about customer segments. And not just a single global set of data, but for each market where the product or service is sold.

Launching new products or services can be a daunting task. With everything from product development, marketing, sales training, customer communication, as well setting the price. Price research can help in various ways with these challenges.

OK, so of course your product or service has a price. A price that reflects what you think is a fair price for the value you deliver to the customers(?). But do the customers see it the same way? And do you charge appropriate prices for what the customers value, or is it disjointed?

When pursuing a value-based pricing strategy, the core focus is on Willingness-to-Pay. What are customers willing to pay for given product or service. This can of course be on the overall level but for proper value-based pricing, it should also be on the feature level. How much value do customers put on individual features or combinations of features. This is where Conjoint Analysis comes in handy.