AI Pricing Boosts Chemical Distributor Revenue by 38% & Cuts Churn by 4%

Context

A global chemical and ingredients distributor operating in more than 70 countries sought to stabilise highly volatile customer ordering patterns across Life Sciences (Food & Nutrition, Beauty & Personal Care, Pharma), Material Sciences (CASE & Construction, Rubber & Polymer Processing, Industrial Applications) and multiple Industrial Sectors (Water Treatment, Energy Services, Lubricants & Additives, Agriculture, Solvents & Cleaning, Automotive). The organisation connects manufacturers and end-users through an extensive supply chain and value-added services. Leadership wanted to optimise the timing and mix of products sold to improve margin performance while reducing customer churn and down‑trading risk using AI-driven decisioning to deliver measurable commercial value.

Challenges

Three core barriers prevented impact: a Board–Sales disconnect where growth, churn and margin were discussed at leadership level but lacked clear definitions or actions for frontline teams; pervasive data distrust and change fatigue following prior failed AI and dashboard initiatives that left sales sceptical and exhausted; and highly volatile ordering behaviour overly reliant on individual salesperson experience rather than scalable insights. Sales incentives exacerbated the problem by rewarding volume rather than timing, margin quality or long‑term customer value, creating misaligned behaviours that undermined pricing and retention objectives.

Implementation

To overcome scepticism and create a clear line of sight from Board KPIs to salesperson actions, a Finance‑owned P&L value case for AI was built that specified what constituted value (EBITDA, gross profit, churn prevention), how it would be measured, and the distinction between realised versus theoretical benefit. Board metrics were translated into sales‑level actions and metrics, creating a shared language across Sales, Finance and leadership. An executive dashboard tracked value versus plan by team, enabling prioritisation, coaching and accountability.

Delivery was reframed around co‑creation. Cross‑functional, agile squads combining Sales, Finance and Data & AI replaced traditional “build and deploy” approaches. Our Fractional Head of AI led the team to deliver an MVP in under 90 days focused on order timing, product selection and margin insight — accepting imperfect data and iterating rapidly to build trust. A suite of ML models was developed to deliver true next‑best‑action sales capabilities with direct P&L impact: predictive order and churn models identified optimal order windows and churn risk for earlier, prioritised engagement; recommendation models surfaced next‑best products, cross‑sell and new product opportunities; and algorithmic margin and price intelligence highlighted margin at risk and suggested optimal price ranges to improve pricing confidence.

To convert insight into sustained behaviour change, individual‑level impact analyses were produced showing each salesperson how AI‑guided actions improved basket size, margin and retention. Commissions were realigned to reward growth, price realisation and churn prevention. Managers were enabled to coach with data, creating a closed loop from insight to action to reward — reframing AI from a top‑down management tool into a personal performance enhancer.

Results

The programme closed the Board–Sales gap and embedded AI as a commercial performance engine. AI‑driven sales and pricing powered smart growth and delivered approximately 90% of the company’s Digital, Data & Excellence transformation value case. Commercial outcomes were substantial: a +38% sales uplift contributing approximately €166M in EBITA, a €6M gross profit improvement attributed to price realisation, and a 4% reduction in churn. Sales capability was materially augmented, margins stabilised, and best practice was scaled rapidly.

Co‑creation and rapid MVP delivery earned sales trust, shifting perception from threat to partner and replacing transformation fatigue with sustained momentum. The solution scaled across roughly 90% of the global footprint within 12 months. Aligning incentives to these insights reinforced pay‑out outcomes, driving rapid adoption and creating sustainable behaviour change that established a repeatable foundation for further AI initiatives.