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Crunch Analytics

Ghent, Belgium

10-49Contact for ratesFounded 2016
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About

Crunch Analytics is a Ghent data and AI agency working on pricing optimization, demand forecasting and process automation for retail, FMCG and manufacturing clients.

Who They Work With

Retail and manufacturing teams that want pricing, forecasting and assortment calls made by a model their analysts can run.

Based on 5 client engagements with a source URL · researched 10 Sept 2026

Our Take

The published cases are retail and manufacturing decisions handed to a model, each with the client named: end-of-season markdown pricing at the shoe retailer Torfs, promotional pricing for Brico under Maxeda, assortment analytics at Unilin that took an analysis cycle from weeks to days, demand forecasting at the frozen-food group Ardo.

The Torfs work is the one to read, because the result was measured against the old method rather than asserted—an A/B comparison with the retailer's traditional markdown process, reported at up to 30% more revenue and up to 8% better margin in the AI group.

Running against that, the write-ups stay at business level: no model families, no accuracy methodology, no monitoring or retraining design is published, so the engineering has to be assessed in conversation.

The weaker fit is buyers outside retail, FMCG and manufacturing, or teams wanting a language-model product rather than forecasting and pricing decisions.

Key strengths

  • An A/B test against the client's existing process is the strongest form of evidence in this category, and the Torfs markdown case publishes one
  • The markdown assistant was scaled to further product categories after the first deployment, which says the work survived contact with operations
  • Case studies are honest about the boring part: the Ardo write-up argues that model quality follows from product lines, customer concentration and logistics context rather than algorithm choice

Good to know

  • No stack detail is published—ask which models are in production, how accuracy is measured and who retrains them once your assortment changes
  • The team page did not resolve at review time and no headcount is published; ask who is assigned and whether the data engineering and the modeling are the same people
  • No rate is published—anchor the conversation against the European range on our rate index before scoping
Gabor Kiss

Reviewed by Gabor Kiss

Founder & Curator, AIAgencies.eu · 10 Sept 2026

Based on the agency's publicly available portfolio. Own this agency? Claim your profile to provide additional context or request a review update.


How we evaluate agencies

Notable Clients

Every engagement documented in a published case study

Documented engagements: Torfs, Ardo, Brico (Maxeda), Unilin, and Decospan. All 5 carry a source URL on file.

TorfsAI markdown assistant predicting the optimal end-of-season discount per item from sales history, inventory and market trends, A/B tested against the retailer's traditional methodSource
ArdoDemand forecasting built around product lines, customer concentration and growing and logistics constraints, aimed at on-time in-full deliverySource
Brico (Maxeda)Analytics for promotional pricing decisionsSource
UnilinPredictive analytics for assortment decisions, reported to cut the analysis cycle from weeks to daysSource
DecospanAI roadmap identifying applications to pursue before committing to a large buildSource

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