Zilliant and the price that got away

The Danish automotive supplier FTZ had a practical question. Could a pricing system keep up with its webshop? With more than 300,000 stock-keeping units and over DKK 2 billion in digital sales, a slow answer would be a commercial problem, however elegant the mathematics behind it.

So FTZ ran a test: 1,000 randomized pricing requests, sent through the same customer-side client under comparable conditions. Zilliant’s September 2026 announcement reports roughly three times faster sequential responses and about 70 times higher output at maximum throughput. The rival platform was unnamed. These are results from one selection exercise, not a universal speed ranking. But the question itself is instructive: how long does the whole answer take to arrive?

A price needs somewhere to go

In ordinary conversation, a price sounds like a number. In a distribution business, it is often a relationship: between a product and its cost, a customer and an agreement, a region and a sales policy. The same part may have different legitimate prices for different buyers. A spreadsheet can hold those numbers. Keeping their relationships intact is the harder assignment.

Zilliant sells cloud software for that assignment. Its focus is B2B pricing, particularly in manufacturing and distribution, where large catalogs meet negotiated terms and shifting costs. Public customer references include Ben E. Keith, NIBE, Infineum and JTEKT. The company’s expertise is concentrated in the unglamorous details of commercial life: price segmentation, scenario modeling, cost changes and the distance between an approved price and a completed sale.

Ten million small acts of discretion

One electrical products distributor in Zilliant’s case library served more than 20,000 customers. More than 70 percent of its revenue came through its webshop. Its pricing operation also contained ten million discounts entered manually. That is a remarkable amount of discretion to entrust to repetitive typing.

The published account describes spreadsheet- and ERP-dependent processes that had become difficult to control. Teams could not adequately see margin consequences, apply decisions consistently or respond quickly to market and cost changes. What failed first was the organization’s ability to understand and coordinate its own pricing. The numbers still existed. Their supervision was falling behind.

The distributor used Price Manager to operationalize AI-derived prices, examine consequences before execution and govern discounts across online and field sales. The revealing detail is the breadth of the repair. A digital sales channel had not removed the pricing problem; it had given the problem somewhere faster to travel.

The model and the machinery

Zilliant’s portfolio divides this work into related jobs. Price IQ evaluates pricing scenarios, makes the tradeoffs among margin, revenue and volume visible, and applies business constraints. A pricing team can ask what happens under different strategies before committing to a change. Explainable recommendations matter because a sales representative needs a reason to trust the answer.

Price Manager coordinates the pricing system: shared logic, global and regional layers, customer prices, cost updates and controlled exceptions. These are different responsibilities. One tool helps decide; the other helps a decision survive contact with the business. In its published use cases, teams can import new costs, test alternative pass-through strategies and publish the chosen scenario.

Deal Manager extends control to customer agreements, from proposal through renewal. Configure, Price, Quote brings pricing into the work of assembling and quoting complex products. Sales Insights and Actions examines transaction and customer patterns to give sellers account-specific next steps. Its published examples include Transgourmet delivering weekly actions to 250 representatives serving 41,000 customers. The destination of the analysis is a person’s next task.

In the market, alternatives include PROS, Pricefx and Vendavo. Zilliant’s particular proposition is the connection among pricing science, agreement control and execution in complex B2B selling. That connection deserves evaluation on a buyer’s own workflows. A label such as “AI-powered” tells you very little about whether your contract price reaches your webshop correctly.

The training behind 134 basis points

A global foodservice distributor in another Zilliant case study had a different version of the coordination problem. Sellers had margin targets but insufficient guidance for individual deals. The company introduced Price IQ alongside educational material, live training and advanced workshops. It also aligned sales objectives with the new approach.

“Success begins with change management.”Senior Director of Pricing Strategy
Foodservice distributor, Zilliant case study

The case reports 134 basis points of seller margin lift, half as many below-floor transactions, more than 80 percent adoption and greater than 20 times ROI during the first 15 months after go-live. Those are customer results published by the vendor, not promises for the next buyer. The account makes no mystery of the human effort involved. Training was part of the intervention.

For scale, 134 basis points means 1.34 percentage points. Applying that change to $100 million in sales would equal $1.34 million, assuming the same relevant revenue base. That is illustrative arithmetic, rather than a disclosed result for this customer. Small-looking changes can become large sums when repeated across enough orders.

Buying the last mile

Zilliant’s December 2023 acquisition of In Mind Cloud added manufacturing-focused CPQ and commerce technology. The logic was straightforward: a pricing decision needs a route to the partner, salesperson or customer who will use it. Configuration and quoting sit directly on that route.

Madison Dearborn Partners, which acquired Zilliant in 2021, subsequently increased its investment by $35 million, announced in March 2024. The money was intended for product enhancements and growth initiatives. The acquisition price for In Mind Cloud was not disclosed in the announcement. The additional investment is financing for Zilliant, not a measure of what a customer pays.

In a company podcast, CEO Pascal Yammine described a CFO’s desire for gauges that let the driver adjust to changing conditions. It is a useful metaphor for Zilliant’s place in enterprise software. ERP and CRM systems carry essential records and processes. Zilliant’s partner ecosystem includes SAP, Salesforce and Oracle; connectors bring pricing into existing commercial applications. Implementation partners include Accenture, Cognizant and SoftServe. Integration is part of the job description.

Thirty days to publish, 180 to make a habit

Pricing Plus, announced in November 2025, addresses companies still relying on spreadsheets, homegrown tools or manual ERP overrides. Its launch materials describe a structured route: governed base prices around day 30, multiple draft scenarios around day 90, and a repeatable pricing rhythm around day 180. Those are deployment targets, not a stopwatch attached to every customer.

The launch version included cost- and value-based templates, draft-and-publish workflows, AI-guided analytics and CSV import/export. Its narrower, structured approach complements Price Manager for more advanced requirements. Zilliant also presented modeled first-year margin protection exceeding $1 million on a $100 million revenue base, conditional on disciplined workflows, cost pass-through and overrides. A model is an argument to test.

The business model is enterprise cloud software with implementation and ongoing support. Buyers are directed to sales for a scoped conversation. The relevant cost comparison therefore includes the subscription, integration work, data preparation and the time required to change selling habits. The published case returns cannot substitute for that calculation.

The useful thing to copy

The lesson a reader can borrow is wonderfully modest: follow a price all the way through. Choose a product and a customer. Trace the cost input, agreement, discount, approval and final transaction. Find where the logic changes, where the answer slows down and where someone must repair it manually. That exercise is this article’s practical inference from the customer accounts.

Then define what success means before deploying a tool. Fewer exceptions, quicker quotes and healthier margins answer different questions. An IDC buyer case hosted by Zilliant emphasizes cross-functional participation and acknowledges that replacing weaker pricing can take three to six months to produce results. The software needs a business willing to revise its routines.

Companies with sparse transaction data, unresolved cost definitions or sellers who disregard guidance will struggle to reproduce these outcomes. A business with a small catalog and simple fixed prices may need far less machinery. The fit improves when pricing complexity is real, the data can describe it and someone owns the decisions after deployment.

Zilliant’s careers page even offers a small cultural footnote: “Zen Days,” a paid half-day on the third Friday of each month. Pricing anxiety has apparently met the calendar. The larger point is more practical. A company can own an impressive price list and still be surprised by its margins. Zilliant’s business is helping the price arrive with its intentions intact.

Explore the pricing room