AI-driven price optimisation gains ground in B2B markets

Dynamic pricing was long considered the domain of airlines and hotel chains. In B2B markets, where prices are traditionally fixed in contracts and catalogues, that picture is changing. Software companies are bringing AI-driven pricing models to retailers, wholesalers and manufacturers that want to respond to market movements without manually updating price lists every time.

The promise is tangible. Research into AI price optimisation in B2B contexts points to average margin improvements of 11 percent with no measurable loss in conversion, and sales growth of around five percent within nine months of implementation. Where pricing analyses used to take weeks, comparable diagnostics can now be completed in hours. That speed makes it easier for sales teams to act on recommendations rather than running all the calculations themselves.

What AI price optimisation does in practice

An AI pricing model continuously processes multiple data sources simultaneously: historical transactions, competitor prices, inventory movements, seasonal patterns and customer behaviour. Based on this, the system proposes a recommended selling price, or adjusts it automatically within margins set by the user.

For B2B, this is more complex than for consumer markets. Customers negotiate discounts, hold framework contracts or purchase through multiple channels at once. A pricing algorithm must account for customer segments, order size and relationship length, not just the current market price. Companies that configure this well can differentiate between a long-standing customer buying in large volumes and a new buyer placing a one-off order, without sales staff having to manually approve every exception.

The technology itself is not new. What has changed is that specialised software companies now offer it as a service, enabling mid-sized companies to use it without an in-house data team.

Dutch players in this segment

Several startups are active in the Netherlands that apply AI to pricing-related challenges in B2B and retail environments.

SYMSON, founded in 2011 and based in Rotterdam, focuses specifically on AI-driven pricing software for improved margins and dynamic pricing strategies. The company raised a Series B round of €59.8 million in January 2022, indicating that substantial capital is available for further product development and market expansion.

Visualfabriq, based in Maarssen and founded in 2013, focuses on revenue forecasting and promotion management for consumer goods companies. Pricing decisions and promotion planning are closely intertwined in this work. The company received private equity funding of €1.8 million in 2021.

Dashmote, based in Amsterdam and active since 2014, delivers market intelligence for food and beverage brands through AI, and closed a Series A round of €4.2 million in 2023. Its focus is on translating market data into actionable signals for brand and pricing strategy.

Wonderflow, also Amsterdam-based and founded in 2014, converts customer feedback from thousands of sources into insights that can inform product development and positioning. In 2024, the company raised a Series B of €18.3 million. Although the focus is on customer feedback, it directly touches on price perception and the question of which product features customers are willing to pay for.

How companies convince customers of the added value

A recurring challenge for pricing software vendors is building trust with the buyer. Pricing decisions directly affect margins, customer relationships and sometimes contractual obligations. Many commercial directors are reluctant to hand control to an algorithm over something they have managed themselves for years.

Vendors typically address this by starting with a transparent advisory model: the system makes a recommendation, a person makes the decision. Only once the recommendations prove reliable does responsibility gradually shift to the system. Data availability is also a practical obstacle. A model is only as good as the data it is trained on, and many B2B companies have their historical sales data scattered across multiple systems or insufficiently structured.

Adoption is fastest among companies with large numbers of SKUs, tight margins and high order volumes, such as wholesalers and distributors. These are the businesses where manually maintaining prices is most burdensome, and where the potential gain from automated optimisation is greatest.

Position in the Dutch and European ecosystem

The rise of AI price optimisation in B2B fits into a broader movement in which Dutch software companies are building vertical AI applications for traditional sectors such as wholesale, retail and food. The funding rounds of SYMSON and Wonderflow show that international investors are taking this segment seriously.

For founders elsewhere in the ecosystem, the lesson is that domain expertise and data access carry more weight than generic AI capabilities. Companies that understand how pricing decisions are made in a specific sector build models that better match the reality of their customers. For investors and policymakers, the picture confirms that the value of AI in many cases lies in sector-specific applications, not in horizontal platforms alone.