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Armin Kakas

Founder, Managing Partner

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About Armin

Armin is a high-octane advanced analytics and revenue management expert with an entrepreneurial spirit and hands-on leadership style. His Commercial Analytics advisory work and data commercialization strategies have driven transformational change for companies and opened new data revenue streams.

As Vice President, Head of Advanced Analytics Commercialization at North America’s leading $5.5B consumer durables distributor, Armin co-founded an analytics subsidiary that enabled the parent company to monetize its data while improving its business decision-making capabilities. He grew the business from 0 to over 2,500 retail locations and manufacturers as customers, providing them with innovative SaaS solutions that captured Point-of-Sale transactional data and served up syndicated market insights, profit, sales mix, and inventory optimization capabilities. Armin masterminded and launched ML-enabled Commercial Analytics products for internal groups in Revenue Management, Sales, and Marketing, contributing to an impressive 35% sales increase and 2x EBITDA growth within three years.

Before this role, Armin was the Head of Data Science in the Revenue Management group, where he built and launched a pricing optimization platform within 90 days. He created the company’s first machine learning-enabled pricing markdown optimization solution, unlocking significant liquidity and gross profit opportunities.

Armin’s career spans 15+ years in B2C and B2B Revenue Growth Analytics, with a strong track record of boosting volume and profits while delivering positive customer outcomes.

His analytics career began at a leading Food & Beverage Company, where he transformed a pricing execution team into a data-driven strategic revenue management group. His work continued at a Fortune 100 retailer, building the company’s dynamic pricing capability and deploying it to over 1,000 retail stores.

A trusted authority in the field, Armin maintains a keen awareness of the Commercial Analytics landscape, actively managing a popular newsletter and hosting analytics webinars for anyone seeking to understand and capitalize on the dynamics of Revenue Growth Analytics.

Education

UNIVERSITY OF VIRGINIA – DARDEN SCHOOL OF BUSINESS
MBA – Decision Analytics and Business Ethics Focus

BAKER UNIVERSITY
Bachelor of Business Administration

Certifications & Continued Education

  • Executive Certificate in Technology & Operations, Data Monetization - Massachusetts Institute of Technology (MIT)
  • Graduate Certificate Program in Machine Learning & Artificial Intelligence - MIT
  • Google Cloud Certified Professional Data Engineer (Google)
  • Graduate Certificate Program in Machine Learning - University of Washington Summer Prog
  • Summer Program in Quantitative Methods, Bayesian Modeling - University of Michigan
  • Executive Education Program, Pricing Strategies - The Wharton School (University of Pennsylvania)
  • Specializations in Deep Learning and Data Science

Organizations

  • Promotion Optimization Institute
  • The American Statistical Association
  • Institute for Operations Research and the Management Sciences

Recent Articles

Pricing Intelligence Engine

Rebuilding Pricing and Promotion Analytics for a Global Data-Storage OEM

April 21, 2026

A Fortune 500 global data-storage OEM was bleeding margin in its $200M U.S. B2C hard-drive business. One flagship family had taken a substantial net-pricing hit year-over-year, and roughly 45% of historical promos were returning only 0 to 20% ROI. Revology rebuilt the pricing and promotion analytics from the ground up using causal Double Machine Learning, a retailer-math ROI model, and a three-archetype segmentation framework. The target: $3M to $6M of incremental EBITDA (a 10x to 20x return on the engagement) within 12 months.

Read More »
Project APEX Pricing Power

Unlocking Pricing Power for a Global Pharmaceutical Manufacturer in Emerging Markets

April 21, 2026

A Fortune 500 global pharmaceutical manufacturer was making emerging-market pricing decisions by feel. We built a repeatable Pricing Quick Wins engine across four pilot markets, grounded in causal elasticity modeling, automated competitive equivalence mapping, and price-pack architecture and inflation-aware simulators. The pilots identified around $8M of median revenue opportunity, with a best-case of ~$12M. Local teams now own the engine and can repeat the analysis annually as inflation and the competitive set shift.

Read More »
Automated RGM Engine

Operationalizing Revenue Growth Management Analytics for a Leading Plant-Based Creamer Brand

April 21, 2026

A leading plant-based creamer brand wanted real visibility into more than $13 million of annual trade spend and a credible way to forecast promo ROI before writing checks. We built the Revenue Growth Management analytics engine for them in Python and Power BI, running on their existing stack. The team now refreshes pricing, promo, and revenue/gross profit performance deep dive models in 10 to 20 minutes and catches variance the old process missed by weeks.

Read More »
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