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Rudy Agovic, PhD

Consulting Partner - AI for Sales & Customer Growth

About Rudy

Rudy is the co-founder of Reliancy and Clarity Data Insights, a leading AI/ML solutions firm for Sales & Marketing Enablement.

He is a recognized expert in AI and Machine Learning (including AI & Industry 4.0 Tech), named a 2021 “Key Opinion Leader” by Onalytica.

Rudy has a successful track record of architecting and deploying AI/ML solutions for Sales & Customer Growth projects across various industries, including mid- and large-cap Retail, Industrials, CPG, Healthcare and SaaS.

Specifically, his expertise is in augmenting Sales and Marketing capabilities with AI, including advanced Customer Journey and Path Analytics and incorporating domain-specific, client-side LLMs into Sales and Marketing analytics solutions.

Rudy holds a PhD from the University of Minnesota and has published extensively in top-tier conferences on AI and machine learning.

Education

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

BAKER UNIVERSITY
Bachelor of Business Administration

Publications

Patents

Recent Articles

Modern CPG RGM dashboard by Revology Analytics for data-driven decisions.

Dashboards to Decisions: The Modern CPG RGM Navigator

Most CPG RGM teams don’t have a data problem. They have a navigation problem. Join Armin Kakas and Enrico Sieni for a 60-minute educational webinar on the modern CPG Pricing & RGM Analytics Navigator. Six modules, five narrow AI agents, the 120-day pilot path. Every registrant gets the whitepaper the week after.

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Revenue growth analytics dashboard for plant-based creamer brand.

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

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.

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Data analytics process for strategic pricing in market growth management.

Unlocking Pricing Power for a Global Pharmaceutical Manufacturer in Emerging Markets

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.

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