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Is trust the foundation for value-based pricing?


Ibbaka recently did a large project with a non-profit that wanted to understand how pricing and value perception were shaping the decisions of their target audience (or rather of the three groups that constitute their audience). This organization’s mandate it to ensure safety and although it needs to self fund it is primarily concerned with shaping behaviours to ensure safety. Working with this group reinforced the importance of trust in pricing. If you have not earned trust, it is very difficult to execute on value-based pricing.

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Why is this? Value-based pricing relies on two things, a deep understanding of the customer’s business and how it is changed by your offer and the ability to connect price and value. At the end of the day, both of these depend on trust. If your customer does not trust you, they will not share the data you need to go deep into value with them and they will not believe your value-messages.

Trust also impacts the beliefs and actions of your sales team. They also need to believe in the value analysis and value messages that have been provided. The best sales compensation plan for a company taking a value-based pricing approach is one based on gross margin (see inset below). This will only work if the sales people trust the information about gross margin provided by management and if management trusts the sales team with this information. In too many organizations this basic trust between sales and management is missing. If people inside the company won’t trust each other then it is hard to ask their customers to believe the value claims and to get them to share critical information.

Creating a sales incentive to drive profit

Recommendation from The Strategy and Tactics of Pricing Sixth Edition

See page 278-279

When sales is compensated on top-line revenue, this is what they will focus on. In many cases, the easiest way to do this is to offer discounts rather than by doing the hard work of communicating value. Sales people tend to do what they are paid to do. They are coin operated as one of our favourite sales advisors Reg Nordman says. Tom Nagle suggests the following compensation model for sales.

Sales Credit = [Target Price - k [Target Price - Actual Price] x Units Sold

k is the profitability factor, or ‘kicker.’ It gives a way to incentivize sales based on the contribution margin. The higher the contribution margin the higher k should be to align the sales person’s interests with the company’s.

Monetizing Data Liozu and Ulaga

Trust is becoming even more important as we move into a world where most products generate and share data, and some of the best business opportunities are based on data monetization. In their recent book on this theme, Monetizing Data: A Practical Roadmap for Framing, Pricing & Selling Your B2B Digital Offers by Stephan Liozu and Wolfgang Ulaga, they devote a whole chapter to the theme of trust. This may be a first for a pricing book. In Chapter 8, “Build Confidence and Trust in the Data and Its Value” they argue that in order to effectively monetize data one has to build customer trust around data quality, data rights, confidentiality, capabilities and relationships. In fact, this extends beyond data-centric offers. All companies that want to execute on value-based pricing need to invest on building trust.

Our research has found that trust is based on three things: fairness, transparency and consistency. Let’s look at each of these.


Is the price fair? This is as emotional question, a price is only fair if both sides perceive it to be so, but there is an economic underpinning. Buyers want to believe that they are getting fair value for their investment. They do not want to overpay, and smart buyers, who trust their vendors and want a long-term relationship will not want to underpay either. This of the standard Economic Value Estimation model developed by Tom Nagle. If the vendor tries to claim too much of the differentiation value the buyer will not regard this as fair. On the other hand, if the buyer refuses to pay any premium for the differentiation value then either they do not believe the value story or they are not willing to play fair themselves. If a buyer is not willing to pay a fair price walk away.

Differentiation Value and Pricing Fairness


Transparency is as important as fairness. Without transparency, there can be no assurance of fairness. For value-based pricing, we are not talking about cost transparency. Costs are only relevant if you are basing your price on costs. What matters is how you came up with your estimate of value. There are three keys here:

  1. Have you really chosen the next best competitive alternative for the buyer or have you set up a straw man?

  2. Have you recognized your negative value drivers (your shortcomings relative to the next best competitive alternatives and your unique costs). We often see EVE models with no negative value drivers. In reality, this is seldom the case. You can win trust by acknowledging your shortcomings and having a way to address them.

  3. Do your value driver equations demonstrate an understanding of your customer’s business (do you have the structure right) and are the placeholders for the variables believable? If you get the structure right and use believable estimates, your customer is often willing to share their own numbers with you as you have demonstrated that you care enough about their industry to understand it and that you are not trying to trick them.

Another aspect of pricing transparency is how you set the price. This has to be clear and easy to understand. You don’t need to disclose this on your website (whether or not to publish pricing is a subject for another day) but you should be willing and able to disclose this in the sales process.


Pricing needs to be consistent. Buyers want to believe they are paying roughly the same amount as others who are similar to themselves. They need to believe that companies have a good reason when they change prices. People in procurement do not want to hear that a competitor has negotiated a better deal on a key input or piece of equipment, and in serious cases, they can lose their job for this.

This will be a challenge for dynamic pricing and load management systems. We can already see this with the airlines, where adoption of revenue management software has contributed to commoditization. If the hotel industry is not careful, it will follow the airlines down this hole.

The use of artificial intelligence (AI) to set prices is going to make it more difficult to develop trust. Companies that use AIs to set prices (which is going to be almost everyone) are going to need to develop policies to ensure that their customers continue to trust them (and to counter the AIs that procurement will be deploying in price negotiations). Be prepared to answer the following questions:

  • What data is used to set prices?

  • What is the machine learning being trained to do?

  • How does the pricing algorithm work? (This will be impossible to answer if your pricing was developed by a deep learning system but that will not stop people from asking it.)

  • What does your AI do to help your customer get more value from your solutions?

Trust is going to become more important, not less, in a world filled with bots and AIs, a world where data is critical to almost all products and services. Programs and policies to promote trust are going to be a central part of any value-based pricing or data monetization strategy.

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