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Professional woman team member representing Revology Analytics team.

Teodora Matic, PHD

Sr. Data Scientist

About Teodora

Teodora is a Ph.D. researcher who focuses on applied statistics and machine learning. She began her career in market research, where she worked primarily on customer satisfaction, brand communication, product and brand optimization. In her role as a market researcher, Teodora used both traditional methods and newer technologies like eye tracking and facial recognition to collect precise data on consumer behavior and product interactions. This helped her to create more targeted and effective brand strategies.

Later, she transitioned to business intelligence and specialized in data visualization and reporting. Teodora uses tools such as Tableau, Python, and R to transform complex data sets into clear visual reports that aid in business decision-making. This helps provide clear insights into business metrics and strategies, supporting informed decisions.

Teodora has a Ph.D. in Applied Statistics from the University of Ljubljana, Slovenia, and a Master’s degree in Research Psychology from the University of Belgrade, Serbia. She earned her Bachelor’s degree in Psychology from the same university.

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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