Effective pricing methods that maximise profit

Artificial intelligence is not just changing how people shop. It is changing the rules under which brands compete.

As AI tools make price comparison and feature benchmarking effortless, competitive landscapes become structurally more transparent. Specifications are extracted, ranked and displayed in seconds. Prices are surfaced without friction, increasing price awareness among consumers.

This is not a technological evolution. It is a strategic shift. If your offer can be reduced to structured, measurable attributes, it will be. And when measurable attributes dominate the comparison, price quickly becomes the most visible point of differentiation. In this environment, brands will need to prove more than ever that they are worth their price tag.

The feature trap: when functional dominates, price follows

AI systems are designed to structure information. They parse product pages, extract specifications and rank comparable attributes. In doing so, they privilege what can be measured: performance scores, technical features, material composition, size, speed, capacity.

When products or services are reduced to structured specifications, the purchase decision risks collapsing into a trade-off between measurable features and price. The richer layers of brand meaning become less visible in the comparison interface.

This is what we call the feature trap: when the architecture of comparison makes price the most salient lever.

Brand equity as a strategic shield

Strong brands show that pricing power does not stem from functionality alone. Customers routinely choose more expensive options despite credible and cheaper alternatives. Not because they failed to compare, but because they value more than the spec sheet reveals.

Patagonia is a clear example. In a category where many brands offer technically comparable outdoor apparel, customers willingly pay a premium. The differentiation does not live solely in fabric weight or water resistance. It lives in purpose, identity, credibility and the total experience of engaging with the brand.

The same dynamic can be seen in brands such as Ben & Jerry’s, Apple, Starbucks and Rituals. Their products can easily be compared on functional attributes, yet customers are willing to pay more because the value extends beyond the product itself.

Besides functionality, there are three other dimensions that determine value:

• Emotional: the feelings, identity and meaning a brand evokes‍
• Trust: the credibility and reliability consumers associate with a brand‍
• Experience: the total customer journey before, during and after purchase

AI comparison tools heavily favour the functional dimension. They are far less capable of capturing emotional resonance, accumulated trust or the lived experience of being a customer.

For brands with shallow equity, this asymmetry is dangerous. Their competitive advantage resides mainly in functional claims, which are easy to benchmark and easy to imitate.

For brands with deep equity, AI becomes less of a threat. Their value proposition extends beyond what can be neatly organised into comparable data points. Customers’ willingness to pay is anchored in something broader than specifications.

Pricing power is about willingness to pay

Pricing power emerges when customers perceive sufficient value to accept a higher price and remain relatively insensitive to changes within a certain range. Strong value perception raises the ceiling of willingness to pay and reduces price resistance. It also creates differentiation across segments: some customers are willing to pay significantly more because they value specific dimensions more strongly.

To avoid competing purely on price, brands must understand which elements of value truly drive willingness to pay, and how these differ across customer segments.

Customer insight as the engine of pricing power

To gain these insights and rebuild pricing power, you need to listen to your customers. Understanding the role of functional, emotional, trust and experience value starts with measuring how important each of these dimensions is for your brand.

The next step is to identify the drivers behind each dimension: which specific elements shape functional value, build trust, create emotional connection or strengthen the customer experience. These drivers may differ across customer segments, as different groups of customers value different aspects of an offer and are willing to pay different prices for them.

A combination of qualitative and quantitative research, complemented by market data and web scraping, helps build a clear understanding of what value means for your brand. Next you can quantify how that value translates into pricing power by measuring willingness to pay and price elasticity.

There are different approaches to measuring this, ranging from simple survey-based methods to more advanced techniques such as conjoint analysis, historical sales analysis or price experiments. Each method comes with its own trade-off between complexity and accuracy.

Competing on value in an AI-driven market

AI will continue to increase transparency. It will continue to make feature comparison faster and price differences more visible. That trajectory is unlikely to reverse.

The strategic response is not to resist transparency. It is to ensure that what becomes transparent includes more than just specifications.

Brands that invest in building and measuring multidimensional value can withstand comparability because their differentiation lives beyond the spreadsheet. Their pricing power is anchored in perception, trust and experience, not just in technical performance.

The real question is: is your brand equity strong enough to ensure that, even in a perfectly comparable environment, customers will still choose you? In other words: are you worth your price tag?

Need help mapping the drivers of your value and identifying how you can increase willingness to pay? Let’s talk.

Rising material and labour costs, decreasing purchasing power, a competitive market and high promotional pressure: no wonder many companies struggle with price setting in today's economy. There is unfortunately no ready-made formula to follow. Understanding your brand, product, market and customers is essential to get your pricing right. Building a pricing strategy without these insights is like building a house on quicksand. An insight-driven method such as value-based pricing is not the easiest to implement, but it is rewarding in the long run. It allows you to maximise your price potential, especially if combined with increased brand equity as this will result in lower price elasticity.

The importance of a strategic approach

How loyal are your customers? Do you understand how competitors set their prices? What is the price elasticity of your brand compared to competitors? How resistant are they to inflation? Do you know what your customers value the most: your brand, product quality or package design? 

If you rely solely on gut feelings to answer these questions your current pricing strategy might be suboptimal. Whether you choose cost-plus, competitive-based or value-based pricing, you always need a certain amount of data and insights to set the right price. Unlike the other methods, value-based pricing requires a deep understanding of your customers and consumers in general, viewing price as an expression of the value you offer. It is the only approach that allows you to maximise your price potential while building brand equity, because once you know what consumers and customers value and what drives their choice, you can deliver an offer tailored to their needs. This often results in a higher willingness to pay.

5 steps to value-based-pricing

Working with our clients, we have seen time and time again that there are five important steps to implement this approach successfully. The overall company strategy should always be your starting point (1), ensure the price is in line with the brand, product and consumer (2), listen closely to consumers and customers (3), create a win-win for all channel partners (4) and analyse whether your market research data is in line with pre-existing knowledge (5).

1. Start from the overall company goal

Although it might seem obvious, it is not always clear why a company wants to adjust their prices. Do you want to focus on volume, revenue, profit or even increasing customer satisfaction? If your goal is increasing volume, you will probably lower your prices, whereas optimising profit might mean higher prices. The KPI you decide to focus on determines your optimal price, as optimising all is rarely possible.

2. Look beyond price and business KPIs

Regardless of the KPI you prioritise, price isn’t a standalone feature. It should always be aligned with your brand, product or service and target consumer or customer. 

• Whether consumers think of your brand as trusted, premium or trendy will impact the price they are willing to pay. 
• Do you understand why people choose your product? Is it the brand or packaging design? The colour or product quality? This influences the price you can ask.
• And what about your consumers and customers? How price sensitive are they, and are they all equally sensitive or are some segments willing to pay more because they truly love your products or brands?

3. Listen to the customer

You will need data to identify the customers’ willingness to pay and your brand’s price elasticity. It will also allow you to understand how customers value your products. A combination of methods will help you achieve this. Transactional data capturing customers’ past behaviour enables you to predict the impact of past price changes on sales. Qualitative research gives more insights into the value drivers and willingness to pay, especially for customers who are hard to reach. Various quantitative methods (such as Van Westendorp, Gabor Granger or conjoint analysis) will help you predict future behaviour for pricing scenarios that have not yet been seen in the market.

4. Create a win-win for all channel partners

No matter how solid your price strategy is, it will fail if you don’t get your partners to agree and adapt their prices accordingly. Share your knowledge with them, educate them on consumer insights and possibly split some gains to get them on board and build long-term relationships.

5. Build your final price setting on four inputs

Lastly, avoid solely relying on market research for your new pricing strategy. Make sure it is aligned with the company strategy and take internal knowledge, expertise and existing data into the equation. Talk to as many stakeholders as possible and capture their insights, especially if your business has been around for quite some time and already navigated many challenges. Build on the experience you already have.  

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Keen to know more about value-based pricing and how to optimise your price potential? Get in touch!